The role of social, economic, and medical marginalization in cancer clinical trial participation inequities: A systematic review.

Introduction

Despite the necessity of representative cancer clinical trials (CCTs) to optimize equitable progress in cancer outcomes, overall CCT participation is remarkably low [ 1 , 2 ]. Strong evidence reveals that these low rates of CCT participation are still further compromised among individuals experiencing social, economic, and/or medical marginalization, particularly among patients of color [ 3 – 7 ] and older adults [ 1 , 8 , 9 ]. Further research increasingly suggests potential underrepresentation in CCTs among other marginalized populations, including sexual and gender minority (SGM) patients [ 10 , 11 ], patients of lower socioeconomic status (SES) [ 12 , 13 ], and patients experiencing greater disability in disease severity, comorbidity, or performance status [ 1 , 14 , 15 ]. However, systematic limitations in data collection and target variables addressed in prior literature render CCT inequities impacting these underserved groups more elusive [ 11 , 16 – 18 ], necessitating further research regarding the effects of these marginalizing characteristics on CCT participation. Considering the disproportionate cancer burden imparted upon groups enduring these forms of marginalization [ 9 , 10 , 15 , 16 , 19 – 23 ], representative CCTs that are generalizable to these populations are of the utmost importance for achieving equitable cancer care outcomes and associated progress across sociodemographic divides.

While prior investigations of CCT participation inequities have explored their effects on various underserved communities in cancer as previously described, these studies have primarily applied a singular perspective to marginalizing characteristics. Specifically, most existing CCT participation literature is limited by inadequate regard for the interactivity of overlapping forms of disadvantage, which serves a critical role in understanding CCT representativeness among the underserved. Intersectionality as a theoretical framework – in its focus on interlocking oppressive systems at the social-structural level and their manifestation in individual experiences [ 24 , 25 ] – is an apt scaffold through which these inequities may be interactively explained. However, despite increasing emphasis on the criticality of an intersectional approach to contextualizing public health outcomes [ 26 ], this framework has yet to be directly applied to CCT participation inequities.

This systematic review aims to provide a more comprehensive, ecologically valid characterization of CCT participation inequities to date across social, economic, and medical vectors of marginalization. In examining their independent and multiplicative influences through an intersectional lens, the authors seek to illustrate how race and ethnicity, age, sex, SGM status, SES, and diverse ability indicators have contributed to inequities in CCT participation across time.

Materials and methods

Search methods

This review adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 27 ]. The first author developed and tailored a systematic search strategy to four databases, following general consultation with library sciences (Supplementary Table 1 ): (1) PubMed, (2) Web of Science, (3) PsycINFO, and (4) CINAHL. An initial search using this strategy was conducted on February 15, 2021, and then replicated on April 8, 2024, for newly published articles given significant time passage since the initial search. Covidence, a web-based collaboration software platform that streamlines the production of systematic and other literature reviews, was utilized to facilitate methodology [ 28 ].

Eligibility criteria

Inclusion criteria for qualitative synthesis of results were (1) original research; (2) focus on CCT participation inequities regarding age, race and/or ethnicity, SES or one of its specific indicators (e.g., income, education, insurance, employment status), sexual identity, sex and/or gender identity, or ability status or relevant indicators (e.g., performance status, comorbidities); (3) peer-reviewed; and (4) full-text availability in English. Exclusion criteria required the removal of original protocols or reviews that (1) address trial participation disparities unrelated or nonspecific to individuals with cancer; (2) do not explicitly comment on CCT participation inequities; (3) encompass scope beyond the focus of this review, including papers exploring underlying barriers to identified inequities, developing solutions, and pediatric populations; (4) are case studies or reviews without quantitative analysis; or (5) are not peer-reviewed, full-text publications. Excluded papers per criterion four were scanned for eligible references unidentified by the search strategy.

Data extraction procedures

Data extraction was standardized across three domains: (1) study characteristics, (2) methodology, and (3) sociodemographic reporting. The first domain specified the cancer population addressed, aims, sample size, intervention type(s), and target marginalizing indicators (Table 1 ). The second domain extracted information regarding study design, recruitment methods and databases, measures, and statistical procedures (Table 2 ). The third domain reported on available study information on sociodemographic characteristics relevant to the modes of marginalization addressed in this review (Table 3 ).

Table 1. Basic study characteristics Authors Year Cancer site Stage Sample size Aim of study Trial type addressed Primary target(s) of disparity Study quality Abbas et al. 2022 Gastrointestinal, hepato-pancreato-biliary Any 10,518 CCT participants (36 CCTs) 2,255,730 CCT-eligible non-participants Examine relationships between patient demographic and socioeconomic indicators, institutional factors, and CCT participation Surgical Age Race/ethnicity SES 5 Abi Jaoude et al. 2020 Any Any 428,560 accruals (600 CCTs) Evaluate (1) characteristics of phase III CCTs that use performance status exclusionary criteria, (2) use of such exclusionary criteria over time, and (3) trial representativeness by performance status. Phase III, multi-arm, explicit supportive care inclusion Ability and comorbidity 5 Acoba, Sumida, and Berenberg 2022 Any Any 1,515 CCT participants 29,982 population controls Examine CCT enrollment at a center prioritizing Asian and Native Hawaiian enrollment Therapeutic, non-therapeutic Race 5 Al Hadidi et al. 2022 Hematologic Any 1057 total participants (7 CCTs) Evaluate the representativeness of Black individuals with hematologic malignancies in CCTs for CAR-T therapies CAR-T Race 5 Aldrighetti et al. 2021 Breast Prostate Lung Colorectal Any 5,867 participants (93 studies) Assess the representativeness of breast, prostate, lung, and colorectal CCTs studying precision medicine Precision oncology Race/ethnicity 4 Ajewole et al. 2021 Lung, breast, prostate Any 142 CCTs total 74 CCTs (total reporting race; 35,933 participants) Evaluate reporting and inclusion of Black Americans in oral chemotherapy CCTs Chemotherapeutic, oral Race/ethnicity 5 Awad et al. 2020 Gynecologic (cervical, endometrial, multiple, ovarian) Any 357 publications 9,492 patients 84 publications reporting race 2,483 patients Describe the longitudinal representation of minority women in phase I, GYN oncology trials Therapeutic, unspecified Race 5 Baldini et al. 2022 Gastrointestinal, hematologic, thoracic Any 1,319 total patients Evaluate the representativeness of older adults (70+) in referrals to early-phase CCTs Systemic, early-phase Age 4 Baquet, Ellison, and Mishra 2009 Breast, colorectal, lung, lymphoma, leukemia, reproductive (sex-specific) Any 2,240 CCT accruals Identify relationships between sociodemographic characteristics and NCI-sponsored therapeutic CCT enrollment Therapeutic, unspecified Age Race Sex SES 5 Behrendt, Hurria, Tumyan, Niland, and Mortimer 2014 Breast I–IV 1,482 total patients 446 accruals Examine the degree to which SES and clinical factors confound disparities in CCT accrual Adjuvant, neoadjuvant, non-adjuvant therapies SES Race/ethnicity 5 Bero et al. 2021 Any (including sex-specific) Any 122 CCTs total Evaluate racial representativeness of radiation therapy CCTs Radiation Race/ethnicity Sex 4 Borad et al. 2020 Multiple myeloma Any 50 (42 provided mean, 15 median) Evaluate age representativeness of phase III, therapeutic multiple myeloma trials Therapeutic, phase III Age 4 Borno et al. 2019 Breast, colorectal, prostate Any 3,580 CCT accruals 20,305 incident CCC cases 341,114 incident catchment area cases Examine whether recruitment inequities were due to inadequate catchment area outreach or lack of representative cancer in the CCC Examine whether CCC data presentation obscures recruitment inequities among different cancer types Therapeutic, unspecified Age Race/ethnicity SES 5 Brierley et al. 2020 Myelodysplastic syndromes Any 449 accruals 1,919 total patients Evaluate baseline characteristics of patients with myelodysplastic syndromes accrued to CCTs Therapeutic, unspecified Age SES Sex Ability 5 Bruno et al. 2022 NSCLC, colorectal, breast Advanced/metastatic Total patients: NSCLC: 14,768 Colorectal: 7,879 Breast: 5,276 Evaluate racial representativeness of lung, breast, and colorectal CCTs and biomarker testing in the US Any, unspecified Race/Ethnicity 3 Bruno, Li, and Hess 2024 Lung Advanced/ metastatic 3,845 total patients Evaluate racial representativeness of CCTs and biomarker testing among individuals with metastatic lung cancer and Medicaid coverage Any, unspecified Race SES 4 Canoui-Poitrine et al. 2019 Colorectal Any 577 Evaluate CCT availability, eligibility, invitation, enrollment, and associated reasons among older adults with colorectal cancer Any therapeutic, diagnostic, or monitoring Age ability and comorbidity 5 Casey et al. 2023 Lymphoma Any/all 33 RCTs Assess demographic and geographic representation of US lymphoma RCTs Drug, therapeutic Race/ethnicity Sex SES 5 Choradia et al. 2024 Any/all Any/all 38,527 total patients Evaluate inequities in demographic representativeness of NCI NIH Clinical Center CCTs Therapeutic, unspecified Race/ethnicity Age Sex 5 Costa, Hari, and Kumar 2016 Multiple myeloma I–III 128 CCTs 8,869 accruals Examine the representativeness of multiple myeloma CCTs in the USA Therapeutic, any Age Race/ethnicity Sex Ability 5 Craig, Gilbery, Herndon, Vogel, and Quinn 2010 Prostate Any 211 accruals 37,216 patients Assess the proportion of older adults with prostate cancer enrolled in Medicare who participated in CCTs Compare characteristics of non-CCT and CCT participants within the older adult Medicare prostate cancer population Any, unspecified Age Race/ethnicity Sex SES Ability 5 Diehl et al. 2011 Breast, thoracic, sarcoma I–IV 10 trials Examine sociodemographic accrual patterns across 10 surgical CCTs Compare characteristics of surgical CCTs successful and unsuccessful at recruiting minority patients Surgical Race/ethnicity 4 Dressler et al. 2015 Breast, Hodgkin’s lymphoma, gastric, colorectal, pancreatic, prostate Any 7 CCTs 8,456 accruals Examine patient- and institution-level factors contributing to participation in pharmacogenomic CCTs Therapeutic, pharmacogenomic Race/ethnicity 5 Du, Gadgeel, and Simon 2006 Lung II–IV 91 accruals 427 total patients Assess factors associated with CCT enrollment among lung cancer patients Therapeutic, unspecified Age Race/ethnicity Sex SES Ability 5 Dudipala et al. 2023 Any/all Any 1121 total patients Examine sociodemographic predictors of clinical trial discussion and enrollment among individuals with lung cancer at Boston Medical Center Therapeutic, primary Age Race/ethnicity 5 Duma et al. 2018 Breast, colorectal, lung, pancreas, prostate, renal, melanoma Any 1,012 CCTs total 210 (CCTs total reporting race/ethnicity) 210 (CCTs total reporting race/ethnicity) Evaluate sex-related, racial, and ethnic representativeness of oncology trials from 2003 to 2016. Therapeutic, any oncology Race/ethnicity Sex 5 Earl et al. 2023 Glioma Any 570 CCT enrollees Evaluate the impact of social determinants of health on CCT participation and their impact on geographical disparities Therapeutic, biobanking SES Geography 4 Elshami et al. 2022 Hepato-pancreato-biliary I–IV 511,639 total patients Evaluate sociodemographic and clinical predictors of CCT enrollment Any Race/ethnicity Age SES Ability and comorbidity 5 Eskander et al. 2022 Pancreatic I–IV 1,127 enrollees 301,240 non-enrollees Evaluate the impact of social determinants of health on CCT enrollment Any Age Race/ethnicity SES (and rurality) Ability and comorbidity 5 Fakhry et al. 2023 Any Any 38 studies to review reporting 15 studies eligible for pt analysis (1,284 pts) Evaluate racial and ethnic representativeness and associated reporting of phase 2, US proton therapy trials Proton therapy Race/ethnicity 5 Fayanju et al. 2019 Breast Any 809,843 total patients 17,214 accruals 792,719 non-accruals Compare cohort of current breast surgical oncology patients enrolled in CCTs and NCDB eligible patient non-accruals Surgical Race/ethnicity SES 5 Freudenburg et al. 2022 Bladder Any 544 studies total 24 studies reporting race Evaluate racial and ethnic representativeness of and associated reporting in bladder CCTs Therapeutic, phase I–III Race/ethnicity 5 Gopishetty, Kota, and Guddati 2020 Breast, colon, lung, DLBCL, AML, ALL Any 103 race-reporting studies 69 age-reporting studies Investigate age, race, and ethnicity distribution in phase III drug trials for the most common solid organ tumors and hematological cancers Drug, therapeutic Age Race/ethnicity 5 Gordis et al. 2022 HPV-associated OPSCC Any 2,995 (32 trials) 14,805 comparison patients Evaluate the representativeness of HPV-associated OPSCC trials relative to US national database Any, unspecified Age Race Sex Ability and Comorbidity 4 Grant et al. 2020 Breast, colorectal, lung, prostate Any 168 trials (96 reporting on race/ethnicity) 34,329 accruals Examine recent phase III US CCT enrollment inequities across race and ethnicity Targeted systemic therapy, cytotoxic chemotherapy, radiation or surgery Race/ethnicity 5 Green et al. 2022 Any/all Any/all 8,360 CCT participants 420,983 non-participants Evaluate the representativeness of older adults with cancer and Medicare FFS coverage in CCTs Therapeutic, unspecified Age SES Race/ethnicity Ability and comorbidity 5 Grette et al. 2021 Breast, gynecologic Any 8,820 CCT participants (53 trials) Evaluate racial representation in breast and gynecologic immunotherapy CCTs Immunotherapy Race 5 Gross, Filardo, Mayne, and Krumholz 2005 Breast Any 737 accruals 7,384 non-accruals Examine the impact of SES on CCT enrollment among older breast cancer patients Drug, therapeutic SES 4 Guerrero et al. 2018 Melanoma, breast, lung Any 208 trials total (reporting race/ethnicity) Evaluate racial and ethnic representativeness and associated reporting practices of various types of cancer research Any, unspecified Race/ethnicity 4 Hantel et al. 2022 Acute leukemia Any 3,734 CCT enrollees Evaluate racial representativeness of CCTs, including companion biobank participation, conducted in Cancer and Leukemia Group B (CALGB/Alliance Cooperative Group Any, unspecified Race/ethnicity SES 4 Hantel et al. 2024 Acute leukemia Any/all 3,698 total patients Evaluate racial and ethnic inequities in access to and enrollment in CCTs conducted at a comprehensive cancer center Therapeutic, unspecified Race/ethnicity SES 5 Hanvey et al. 2022 Gynecologic, gastrointestinal, thoracic Any 692 total approached Evaluate demographic and socioeconomic inequities in psychosocial CCT interest, eligibility, decline, enrollment, and retention Psychosocial/ behavioral Age Race/ethnicity SES 5 Hennessy et al. 2022 Gastro-esophageal Metastatic 66 trials Evaluate age-related representativeness and associated exclusion criteria in metastatic gastroesophageal CCTs from 1995 to 2020 Therapeutic, systemic, phase III Age 5 Hori et al. 2007 Leukemia, lymphoma, esophageal, stomach, intestinal, liver, pancreatic, lung, breast, prostate, head and neck, uterus Any 68 trials Evaluate inequities in age between the Japanese cancer population and patients enrolled in new drug application (NDA) clinical trials Drug, therapeutic Age 5 Housri et al. 2015 Breast In situ – II 264 total patients Identify patient and tumor traits predicting HBRT enrollment among breast cancer patients Radiotherapy Race/ethnicity Sex Ability 5 Huang, Ezenwa, Wilkie, and Judge 2013 Any Any 1,464 total patients 612 eligible patients Assess sex and racial/ethnic differences in referral, eligibility, enrollment, and retention in two CCTs focused on pain and/or fatigue Psychosocial/ behavioral Race/ethnicity Sex 4 Hue et al. 2022 Pancreatic Any 1,110 CCT enrollees 261,483 total Evaluate demographic and clinical representativeness of pancreatic CCTs and associated survival Any, unspecified Race/ethnicity Age SES Sex Ability and comorbidity 5 Jan et al. 2022 Primary liver Any 9749 CCT participants (63 CCTs) To describe racial, ethnic, sex, and age representativeness of primary liver CCTs across the globe Therapeutic, unspecified Race/ethnicity Age Sex 5 Javid et al. 2012 Breast I–IV 1,079 patients Evaluate (1) age-related differences in CCT availability, eligibility, and enrollment and (2) patient- and physician-perceived barriers and facilitators in breast CCTs Therapeutic, systemic Age Ability and comorbidity 5 Javier-DesLoges et al. 2022 Breast, colorectal, lung, prostate Any 242,720 CCT participants Examine racial, ethnic, sex, and age representativeness of NCI CCTs and associated change across time Any Race/ethnicity Sex Age 5 Jayakrishnan et al. 2021 Any Any 261 (total CCTs) 223 (CCTs reporting race) Evaluate age and racial/ethnic representativeness and reporting patterns of FDA CCTs Drug, therapeutic Race/ethnicity Age 4 Kaanders et al. 2022 Head/neck Any 87 RCTs Evaluate the representativeness of head and neck cancer RCTs relative to the clinically treated population Systemic, radiotherapy, surgical, hypothermic Age Ability and comorbidity 5 Kanapuru et al. 2023 Multiple myeloma Any 9325 CCT participants (16 CCTs) Evaluate racial and ethnic disparities in eligibility and enrollment for multiple myeloma drug CCTs Drug, therapeutic Race/ethnicity 4 Kanarek et al. 2010 Brain, breast, gastrointestinal, hematopoietic, prostate, upper aerodigestive, viral/other Any 5,068 accruals 17,637 total patients Examine race/ethnicity and geographic location of residence on CCT enrollment at JH-SKCCC Therapeutic, non-therapeutic Race/ethnicity Geography 5 Keegan 2023 breast Any 98 CCTs Evaluate longitudinal change in racial reporting and representation in breast CCTs Any, unspecified Race/ethnicity (reporting) 5 Khadraoui et al. 2023 Endometrial, ovarian, cervical Any 548 (CCT participants) 562,592 (total patients) Evaluate racial and ethnic representativeness of gynecologic CCTs accounting for other demographic and socioeconomic covariates Any, unspecified Race/ethnicity Age SES Ability and comorbidity 4 Kilic et al. 2023 Lung Any 311 (total CCTs) 9,869 participants for analysis (136 CCTs reporting race/ethnicity) 9,869 participants for analysis (136 CCTs reporting race/ethnicity) Evaluate racial, ethnic, sex, and age representativeness of lung CCTs Any, explicit supportive care inclusion Race/ethnicity Sex Age 5 Ko et al. 2015 CNS, breast, GI, genitourinary, head and neck, lung, other Any 99 trials 847 total screens Identify characteristics of baseline eligibility, enrollment rates, reasons for ineligibility, and reasons for non-enrollment across CCTs Therapeutic, non-therapeutic (explicit inclusion of supportive care) Race/ethnicity SES 4 Kwak et al. 2023 Lung Any 1924 CCT enrollees 1.6 million total patients Evaluate racial, ethnic, and socioeconomic representativeness of lung CCTs Any Race/ethnicity SES 3 Ladbury et al. 2022 Breast, cervical, prostate, uterine Any 77 trials (13,580 participants) Evaluate age, racial, and ethnic representation in CCTs involving brachytherapy Therapeutic, brachytherapy Age Race/ethnicity 5 Langford et al. 2014 Any (primary: breast, colorectal, genitourinary) Any 4509 patient logs Evaluate racial and ethnic differences in CCT enrollment, refusal, eligibility, and desire to participate Any, explicit supportive care (i.e., symptom management) inclusion Race/ethnicity Age Sex Ability and comorbidity 5 Lythgoe, Savage, and Prasad 2021 Prostate Any 18,455 CCT participants (17 CCTs, 9 reporting race) Evaluate racial representativeness and associated reporting in FDA drug approvals for prostate CCTs Drug, therapeutic Race/ethnicity 5 Mishkin, Minasian, Kohn, Noone, and Temkin 2016 Gynecologic (cervical, ovarian, uterine) Any 156 trials 18,913 accruals Examine sociodemographic differences between NCI gynecologic CCT enrollees and incident gynecologic cancer population in the US Therapeutic, unspecified Age Race/ethnicity SES 4 Moloney and Shiely 2022 Breast Any 40 CCTs Assess demographic and socioeconomic inequities in breast CCT participation due to direct and indirect impact of eligibility criteria Drug, therapeutic, phase III Race/ethnicity Age SGM SES Geography Ability and Comorbidity 3 Murthy, Krumholz, and Gross 2004 Breast, lung, colorectal, prostate Any 75,215 accruals Compare CCT enrollees with population-based incidence data on age, sex, race, and ethnicity Determine whether size of sociodemographic inequities varied by age group or cancer type Determine whether racial/ethnic minority representation in CCTs has changed over time (1996–1998 compared to 2000–2002) Therapeutic, nonsurgical Age Race/ethnicity Sex 5 Newman et al. 2004 Breast, thoracic, gastrointestinal All 7 CCTs Evaluate sociodemographic accrual trends in ACOSOG CCTs Surgical Age Race/ethnicity 4 Noor et al. 2013 Any Any 430 referrals 174 CCT accruals 10,784 population controls Examine the effects of SES on the likelihood of referral to phase I CCTs and of enrollment Any, unspecified, phase I 5 Osann et al. 2011 Cervical I–III 380 recruitment letters 50 accruals Use population-based data to identify disparities in accrual and retention of minority and/or low-income patients in a biobehavioral CCT Psychosocial/ behavioral Ethnicity SES Sex 3 Owens-Walton et al. 2022 Prostate, kidney, bladder/urothelial Any 341 CCTs 49,202 CCT enrollees (of 169 CCTs reporting race) Evaluate minority representativeness of urologic CCTs Therapeutic, phase II and III Race/ethnicity 4 Palmer et al. 2021 Prostate I–II 855 total patients Evaluate demographic and socioeconomic representativeness of various types of prostate CCTs based on self-report Any, explicit behavioral inclusion Race/ethnicity Age SES Ability and comorbidity 3 Pang et al. 2016 Lung (NSCLC, SCLC) Any 131 trials 23,006 accruals 578,476 population controls Identify inequities in CCT enrollment across age, race, ethnicity, and sex Therapeutic, unspecified Age Race/ethnicity Sex 5 Patel et al. 2020 Breast 0–II 2,472 invited patients Investigate predictors of invitation to and participation in CCTs Surgical, hormonal, systemic chemotherapy, radiation Age Race/ethnicity Sex SES Ability 4 Patel et al. 2023 Gastrointestinal, head/neck Any 1,446 total Evaluate sociodemographic disparities in CCT eligibility and enrollment Any Race/ethnicity Sex Age SES Ability and comorbidity 5 Patki et al. 2023 Prostate Any/all 138 full-text studies total 54 full-text studies reporting on EDI variables (19,039 participants) Evaluate racial, ethnic, educational, and socioeconomic representativeness of treatment prostrate CCTs and associated reporting in manuscripts Therapeutic, unspecified Race/ethnicity SES 5 Perni, Moy, and Nipp 2021 Any Any 2657 CCTs Evaluate the sociodemographic and clinical representativeness of phase I CCTs, relative to that of phase II and III CCTs Any, phase I–III Race/ethnicity Sex Age SES 4 Pirl et al. 2018 Any Any 18 total CCTs (3,960 patients) 10 patient CCTs reporting race/ethnicity (1,910 patients) Evaluate racial and ethnic representativeness of and associated reporting practices for integrated palliative care CCTs Supportive (palliative) care oncology Race/ethnicity 5 Pittel et al. 2023 Lung, colorectal, breast, pancreatic, multiple myeloma Advanced/metastatic 50,411 patients total (800 care sites) Evaluate recent racial and ethnic representativeness of US CCTs in context of pre- and per-COVID-19 pandemic conditions Drug, therapeutic Race/ethnicity Age Sex Ability and comorbidity 4 Ramamoorthy et al. 2018 Breast, colorectal, lung, prostate Any 2008–2013: 158 CCTs; 22,481 enrollees 2014–2017: 9 CCTs; 3,612 enrollees Evaluate age, sex, racial, and ethnic representativeness of new oncologic FDA-approved products Drug, therapeutic Race/ethnicity Age Sex 5 Reihl et al. 2022 Glioma Any 49,907 CCT participants (662 CCTs) Evaluate racial, ethnic, and sex representativeness of CNS CCTs since NIH Revitalization Act Therapeutic, phase I–IV Race/ethnicity Sex Race and sex reporting 5 Riaz et al. 2023 Prostate Any 104,205 (total CCT participants, global from 286 CCTs) 9,552 CCT participants (race-reporting CCTs in the USA) Evaluate age, racial, and ethnic representativeness of prostate CCTs Any, unspecified Age Race/ethnicity Age, race, and ethnicity reporting 5 Saphner et al. 2021 Any Any 39,968 total patients Evaluate demographic and socioeconomic representativeness of CCTs Any, unspecified Race/ethnicity SES Age Sex 5 Sawaf et al. 2023 Rectal Any 50 CCTs Assess demographic and socioeconomic representativeness of US colorectal CCTs Therapeutic, varied Age Race/ethnicity Sex SES 5 Scalici et al. 2015 Cervical, endometrial, ovarian, sarcoma Any 445 GOG studies 170 GOG studies reporting race 67,568 accruals 45,259 accruals reporting race Determine minority participation proportions in GYN Oncology Group (GOG) CCTs Any, phase I–III, observational, translational Race/ethnicity 4 Sedrak et al. 2022 Any Any 2,298 patients offered CCT Evaluate age-related enrollment, ineligibility, and decline patterns in CCT relative to community cancer population Any, explicit “non-therapeutic” inclusion Age Ability and comorbidity 5 Shah et al. 2022 Melanoma Any 20,912 CCT participants (35 CCTs) Evaluate the sociodemographic representativeness of melanoma CCTs conducted in Europe, New Zealand, and Australian, with a focus on age Therapeutic, phase III Age 5 Shinder et al. 2023 Renal I–IV 681 CCT participants 3,405 matched controls Evaluate predictors of renal CCT participation Any, unspecified Age Race/ethnicity SES Sex Ability and comorbidity 5 Steventon et al. 2024 Gynecologic Any 17,041 CCT participants (26 RCTs) Evaluate racial and ethnic representativeness of gynecologic CCTs on US and global scale Systemic therapies Race/ethnicity (and reporting) Continental origin 5 Stewart, Bertoni, Staten, Levine, and Gross 2007 Breast, colon, lung, prostate Any 13,991 accruals Examine demographic characteristics of surgical CCT enrollment Surgical Age Race/ethnicity Sex 4 Talarico, Chen, and Pazdur 2004 Breast, lung, colorectal, ovarian, pancreatic, CNS, leukemia, lymphoma Any 55 registration trials (28,766 patients) Evaluate age representativeness of CCTs registering new cancer drugs approved by the FDA from 1995 to 2002. Drug, therapeutic Age 4 Tharakan, Zhong, and Galsky 2021 Any Any 35 cancer drug approvals (w/ race reporting) 16,685 CCT enrollees (49 CCTs) 21 cancer drug approvals (w/ race and location) 10,318 CCT enrollees (21 CCTs) Evaluate relationships between racial representativeness of US and global CCTs Drug, therapeutic Race Race reporting 4 Unger et al. 2020 Bladder, breast, colorectal, gastroesophageal, gynecologic, head and neck, leukemia, liver, lung, lymphoma, melanoma, myeloma, pancreas, prostate, renal Any 85 pharmaceutical company trials (46,513 patients) 273 SWOG trials (47,512 patients) Evaluate racial representativeness of pharmaceutical company-sponsored drug CCTs relative to those sponsored by the NCI National Clinical Trials Network (NCTN) and to the US oncologic population Drug, therapeutic Race 5 Unger, Gralow, Albain, Ramsey, and Hershman 2016 Breast, colorectal, lung Any 1,581 patients 1,262 patients with income data Examine effect of income and other sociodemographic covariates in predicting prospective enrollment in CCTs Any, unspecified SES 5 Unger et al. 2013 Breast, colorectal, lung, prostate Any 5,499 evaluable respondents Evaluate socioeconomic and other demographic predictors of CCT enrollment, attitudes, and reasons for decline Any, unspecified SES Age Race/ethnicity Ability and comorbidity 5 VanderWalde et al. 2022 Any Any 66,708 CCT enrollees (237 CCTs) Evaluate underrepresentation of older adults in CCTs in context of trial characteristics Therapeutic, any Age 5 Wagar et al. 2022 Ovarian, fallopian, peritoneal Any/all 15 CCTs (3,414 enrollees) Evaluate racial and ethnic representativeness of phase II and III poly (ADP-ribose) polymerase (PARP) inhibitor CCTs for ovarian cancer Therapeutic, PARP inhibitor Race/ethnicity 4 Yekedūz et al. 2021 Solid tumors Any/all 105,397 CCT enrollees (142 CCTs) Evaluate sociodemographic inequities in CCT participation for solid organ tumor drug trials Drug, therapeutic Ability & comorbidity 5 Yonemori et al. 2010 CNS, oral/pharyngeal, lung, gastric, liver, gallbladder, colon, kidney, bladder, pancreas, skin, breast, uterine, ovarian, prostate, lymphoma, myeloma, leukemia Any 234 trials Evaluate older adult CCT participation for NDAs or extension of indications for oncology drugs or supportive care Drug, therapeutic, explicit supportive care inclusion, phase I Age Ability 5 Zafar et al. 2011 Any Any 216 patients Describe sociodemographic, disease, treatment characteristics of older patients presenting to Phase I Clinical Trial service Drug, therapeutic Age Ability 3 Zhao et al. 2024 Breast, prostate, colorectal, lung Any 7747 total CCTs Evaluate the sociodemographic representativeness of common CCTs, with a focus on older adults Therapeutic, phase III Age 5 Zullig et al. 2016 Lung, colorectal, breast, prostate Any 13,795 accruals 588,317 incident cases Evaluate sociodemographic characteristics of CCT enrollment in North Carolina Therapeutic, unspecified Race/ethnicity 4 Zuniga et al. 2020 Prostate Localized, Advanced 26 trials 2316 accruals 608,006 incident cases Describe reporting of race and race-specific analyses of Black prostate cancer patients in lifestyle intervention CCTs Evaluate distribution of Black patients in lifestyle CCTs compared to Black patients with prostate cancer in the USA Psychosocial/ behavioral Race Sex 4 Note: Abbreviations included in this table are utilized as follows, listed alphabetically: ACOSOG = Alliance for Clinical Trials in Oncology; CALGB = Cancer and Leukemia Group B; CAR-T = chimeric antigen receptor T-cell; CCC = comprehensive cancer center; CCT = cancer clinical trial; EDI = Equity, Diversity, and Inclusion; FDA = Food and Drug Administration; HBRT = hypofractionated breast radiotherapy trials; HPV = human papillomavirus; JH-SKCCC = Johns Hopkins Sidney Kimmel Comprehensive Cancer Center; NCDB = National Cancer Database; NCI = National Cancer Institute; NIH = National Institutes of Health; NR = not reported; NSCLC = non-small cell lung carcinoma; OPSCC = oropharyngeal squamous cell carcinoma; SES = socioeconomic status.

Table 2. Methodology of studies Authors Year Study design Recruitment Databases Measures Analysis Abbas et al. 2022 Case-control study Archival database ClinicalTrials.gov, NCI Cancer Therapy Evaluation Program (CTEP, 2000–2019) National Cancer Database (NCDB, 2004–2017) Patient: Dichotomized age (@65) Race/Ethnicity (NHW, NHB, AAPI, H) Insurance coverage Cancer site Residential ZIP code (median household income, HS educational attainment) Institutional: CCT slot Facility location Enrollment fraction (EF) Preliminary chi-square and t-tests Multivariate logistic regression Abi Jaoude et al. 2020 Meta-analysis Archival database ClinicalTrials.gov Presence of exclusionary criteria Performance status: ECOG score Chi-square tests Binary logistic regression Acoba, Sumida, and Berenberg 2022 Case-control study Archival database UHCC OnCore Hawaii Tumor Registry Race (White, Chinese, Filipino, Japanese, Native Hawaiian) EF Non-parametric descriptive inferential testing Ajewole et al. 2021 Cohort study Archival database FDA Hematology/Oncology Approvals (2009–2019) Race reporting Race (and ethnicity): White, Asian, Black, Hispanic Descriptive statistics Al Hadidi et al. 2022 Case-control study Archival database Drugs@FDA (CAR-T therapies 2017–2021) Enrollment proportion Prevalence statistics (from DeSantis et al. (2019)) Participant-to-prevalence ratios Aldrighetti et al. 2021 Meta-analysis Archival database ClinicalTrials.gov (through April 2021) Surveillance, Epidemiology, and End Results (SEER) US Census Race/ethnicity (NHW, B , AAPI, AI/AN, H) O:E ratios for enrollment relative to incident population Meta-Analysis of O:E enrollment ratios Awad et al. 2020 Meta-analysis Literature search, archival database PubMed (1985–2018), US CDC (1999–2015) CDC age-adjusted incidence Age Race Tumor type Publication year Age-adjusted incidence by type (US CDC) Expected enrollment ratio (White [W]:Black [B]) Expected:Observed ratios T-tests Chi-square tests ANOVAs Baldini et al. 2022 Case-control study Archival database, internal clinical infrastructure EGALICAN-2 survey (11 early-phase units) GLOBOCAN Population-based incidence rates (2020) Preliminary chi-square and Fisher’s exact tests One sample z-test Logistic regression Baquet, Ellison, and Mishra 2009 Case-control study Archival database Cancer Therapy Evaluation Program (NCI CTGC, 1999–2002) Maryland Cancer Registry (1999–2002) Patient level : Cancer site 10-year age group, Race (W, B , Other) Sex Residential ZIP code Insurance status (private, Medicaid or Medicare, self-pay, military) County level: Material deprivation (%poverty, households w/o car, 16+ unemployed, owner-unoccupied housing) Social class (% 25+ HS graduates, grad/professional degrees, white-collar occupations, median household income, population composition) Urban/rural (Beale classification system) Preliminary chi-square tests Logistic regression Behrendt, Hurria, Tumyan, Niland, and Mortimer 2014 Cohort study Internal treatment center, archival database City of Hope Comprehensive Care Center (2004–2009) US Census Bureau American Community Survey (2007–2011) Primary: birthplace/race/ethnicity (African, Asian, Latin American, Eastern European, Middle Eastern, Other Caucasian) Accrual status Covariates Patient level Primary language Tumor (stage, HR status, HER2/neu status, year of first visit, time since Dx) Oncologist level PI status Duration of practice Linguistic fluency ZIP code level Median household income (12 months) % w/o HS education among 25+ women Preliminary bivariate correlation Logistic regression Bero et al. 2021 Case-control study Archival database ClinicalTrials.gov (1996–2019) US Census (2018) EF Chi-square analysis Borad et al. 2020 Cohort study Archival database ClinicalTrials.gov (8/2000–2/2020) Mean and median age Trial treatment type Trial country Descriptive statistics Borno et al. 2019 Case-control study Internal treatment center, archival database CTMS, UCSF, Helen Diller Family CCC California Cancer Registry, UCSF catchment area (2010–2014) Dichotomized age (@65) Race/ethnicity (W, B , AAPI, Latino, Other) Chi-square tests Brierley et al. 2020 Case-control study Archival database US MDS CRC (1991–2017, data from 5/6 institutions) SEER-Medicare International Working Group for Prognosis in MDS Age Sex Race/ethnicity Distance to treatment center Blood counts and creatinine MDS subtype ECOG PS Therapy-related disease Zip code (income proxy: total income/# inhabitants) Preliminary Kruskal–Wallis tests, Chi-square or Fisher’s exact test Logistic regression Bruno, Li, and Hess 2024 Cohort study Archival database Merative MarketScan Medicaid claims database (2017–2019) Race (W, B , Other) Age Sex Staging CCT participation likelihood Preliminary chi-square and t-tests Logistic regression Bruno et al. 2022 Cohort study Archival database Flatiron Health Electronic Health Record (2011–2017) Age Race (W, B , Asian, Other, Unknown) Ethnicity (NH, H) Stage Insurance Functional status (ECOG) Cancer covariates Institutional covariates CCT participation (use of the clinical trial drug during the period of observation) Preliminary chi-square analyses Stepwise linear regression Canoui-Poitrine et al. 2019 Cohort study Archival database Sujets AGes dans les Essais Cliniques (SAGE; Older Subjects in Clinical Trials, 2012–2016) Age: 65–69, 70–74, 75–79, 80+ Sex Disease site and stage Performance status Comorbidity MMSE, NCD history, ADL score, mini-GDS, polymedication, incontinence, mini-Nutritional Assessment Test Trial sponsor, phase, treatment CCT eligibility, invitation, reasons for ineligibility, non-invitation, non-inclusion Chi-square, Fischer, and Kruskal–Wallis tests Multivariate logistic regression Multivariate logistic regression Casey et al. 2023 Case-control study Archival database FDA “Oncology/Hematologic Malignancies approval notifications” (2011–2021) FDA “Novel Drug Approvals” (2011–2021) SEER Explorer (2014–2018) County Health Rankings and Roadmaps Small Area Health Insurance Estimates (2020) Race (AI/AN, AAPI, B , W, Oth) Ethnicity (NH, H) Sex Age ZIP Code (CCT representation fraction relative to population burden estimates Chi-square and Fisher’s exact tests Choradia et al. 2024 Case-control study Archival database Biomedical Translational Research System (BTRIS, 2005–2020) SEER (2018) Cancer in North America (CiNA) database (2018) North American Association of Central Cancer Registries Dichotomized age (@65) Race (W, B , AAPI, AI/AN, multiracial, unknown) Ethnicity (NH, H) Sex State Country Enrollment fraction Preliminary chi-square tests Logistic regression Costa, Hari, and Kumar 2016 Meta-analysis Literature search, archival database PubMed (2007–2014) SEER-18 ISS (1981–2002) Mayo (2001–2010) Study level : Study phase Tx status Study size Sponsor type Patient level: Age Sex Stage Race/ethnicity (dichotomized NHW vs. racial and/or ethnic minority) Preliminary chi-square and Fisher’s exact tests, Mann–Whitney tests Byar approximations for ratios Craig, Gilbery, Herndon, Vogel, and Quinn 2010 Case-control study Archival database SEER-Medicare (Sep 2000–Dec 2002) SES: Median income using IQR of zip code to categorize neighborhoods into low, middle, high; ZIP codes US Dept. Agricultural rural–urban continuum Census region: Northeast, South, Midwest, West Tumor characteristics: grade, PSA status, stage Race/ethnicity: W, B , Hispanic, Other Education: < HS, HS, some college, college graduate Preliminary Wilcoxon–Mann–Whitney U, chi-square tests Logistic regression Diehl et al. 2011 Cross-sectional study Archival database ACOSOG trials (1999–2009) Race/ethnicity via patient report at trial registration Predictors: randomization, staging (early vs. advanced), design (drug vs. surgical) Success level: successful, modestly successful, unsuccessful measured by the proportion of AA and HA participants based on general and oncologic population characteristic ASOSOG recommendations for accrual targets: early-stage breast: AA 11+%. HA 5+% regionally advanced breast: AA 14+%, HA 5+% Non-metastatic lung: AA 10+%, HA 2+% Metastatic lung: AA 12+%, HA 2+% Proportions relative to the general population and oncologic population Dressler et al. 2015 Cohort study Archival database Cancer and Leukemia Group B (Alliance for Clinical Trials in Oncology, after 2003) Alliance Statistics and Data Center Clinical Trials Support Unit Patient characteristics: Age Sex Race (dichotomized) Cancer type Institutional characteristics : Site registration Accrual patterns Accrual patterns specific to pharmacogenomic component Exploratory institutional diversity via minority participation fraction Probability of consent to pharmacogenomic studies Preliminary chi-square and Wilcoxon rank-sum tests Logistic regression Du, Gadgeel, and Simon 2006 Cohort study Internal treatment center, archival database Karmanos Cancer Institute (Jan 1, 1994–Dec 31, 1998) SEER (MDCSS) Sex Age at Dx Race dichotomized Insurance coverage (commercial, Medicaid, Medicare only, Medicare Plus) SES rank Stage Histology SWOG PS Comorbidities Preliminary chi-square and t-tests Logistic regression Dudipala et al. 2023 Cohort study Archival database Electronic Medical Records (EMRs) (1/2015–12/2020) Age Race Ethnicity Sex City Primary language Median household income Insurance Education Stratified proportion CCT discussed Stratified proportion CCT enrolled Preliminary chi-square and Fisher’s exact tests Multivariate logistic regression Duma et al. 2018 Meta-analysis Archival database ClinicalTrials.gov (2003–2016) SEER (2013) Race/ethnicity Sex EF Race/ethnicity reporting Time period (1996–2002, 2003–2016) Race/ethnicity reporting Time period (1996–2002, 2003–2016) Chi-square tests Earl et al. 2023 Case-control study Archival database Huntsman Cancer Institute (HCI) Research Informatics Shared Resource (May 2012–May 2022) HCI Clinical Trial Office Utah Cancer Registry (Jan 2010–Dec 2019) Rurality (county: frontier, rural, urban) Household per capita income (2019) County % HS education+ County glioma incidence estimates Enrollment fraction One-way ANOVA (Tukey post hoc) Chi-square analysis Elshami et al. 2022 Cohort study Archival database NCDB (2004–2017) Age Sex Race Ethnicity Education Median income Insurance (primary) Facility type, distance Staging Comorbidity score Histology Rate of CCT enrollment Preliminary chi-square tests Multivariate logistic regression Eskander et al. 2022 Cohort study Archival database NCDB Age Race Ethnicity ZIP-code median income and %HS edu Insurance coverage Facility distance, type, and location Charlson-Deyo comorbidity score Preliminary chi-square and Wilcoxon rank sum tests Multivariate logistic regression Fakhry et al. 2023 Meta-analysis Archival database PubMed, Embase, World of Science, Cochrane (through 7/27/2021); US Census Data (2020) Race/ethnicity report Race/ethnicity representation (W, B , AI/AN, Asian, NH/PI, Multi, H) Population-based incident estimates Descriptive proportions Fayanju et al. 2019 Case-control study Archival database NCI Cancer Therapy Evaluation Program (CTEP) National Cancer Database (1998–2012) ClinicalTrials.gov (2000–2012) Age at Dx (<40, 40–64, 65+) Year of enrollment Race/ethnicity (NHW, NHW, API, Hispanic, Native American, Other) ZIP-code level Median household income % HS graduates Enrollment decision Preliminary chi-square and t-tests Logistic regression Freudenburg et al. 2022 Meta-analysis Archival database MEDLINE (1/1/1970–2/29/2020) Clinicaltrials.gov (1997–2020) Race reporting (C, AA, Other, Asian, H , NA) Descriptive proportions Qualitative synthesis Gopishetty, Kota, and Guddati 2020 Case-control study Archival database NIH trials (Jan 1, 1999–Jan 1, 2019) US Cancer Statistics Age- and race-adjusted incidence by type CCT enrollment Chi-square tests Gordis et al. 2022 Meta-analysis Archival database PubMed, Scopus, CINAHL, Cochrane Library (through 2/2/2022) NCDB Age Sex Race Cancer history Tumor site Behavioral health history (smoking, alcohol) Meta-analysis with Freeman-Tukey weighted-summary proportion Grant et al. 2020 Case-control study Archival database ClinicalTrials.gov SEER (dates unspecified, 5-year increments) Difference in incidence by race/ethnicity between CCT and SEER incident cases Ratio of incidence by race/ethnicity via median ratio of CCT and SEER incident cases Preliminary Mann–Whitney U and Kruskal–Wallis ANOVAs Wilcoxon signed-rank test for comparing D-IRE to 0 and R-IRE to 1 Green et al. 2022 Cohort study Archival database Medicare FFS claims data Clinicaltrials.gov (1/1/2015–6/30/2020) Dichotomized age (@65) ZIP code (median income) CCT enrollment Descriptive proportions Grette et al. 2021 Case-control study Archival database Clinicaltrials.gov CDC (age-adjusted rates) Race reporting Participant race (W, B , Asian, Other) Tumor site Age-adjusted incidence rates Chi-square analyses Gross, Filardo, Mayne, and Krumholz 2005 Case-control study Archival database NCI CTEP (1996–2001) SEER-Medicare SES: % below poverty level (zip), % unemployed (county), insurance (private, Medicare, Medicaid, Medicare + private, Medicare + Medicaid, VA, self-pay, uninsured, other) Age: 65–59, 70–74, 75–79, 80–84, 85+ Race/ethnicity: W, NHB, Hispanic, API Distance between home and site Preliminary chi-square and t-tests Logistic regression Guerrero et al. 2018 Meta-analysis Archival database PubMed Presence of race/ethnicity reporting Race/ethnicity Descriptive statistics Hantel et al. 2024 Cohort study Archival database Dana-Farber/Harvard Cancer Center (DF-HCC) cancer and clinical trials registries Massachusetts Cancer Registry (MCR) 1/1/2010–12/31/2019 Race/ethnicity (NHW, NHB, NHA, HW, Other) Insurance Marital status Driving distance State Yost Index (sYI) Age Sex Subtype Access (treatment at a DF-HCC hospital) CCT enrollment Preliminary chi-square, Fisher’s exact, and Kruskal–Wallis tests Multivariate logistic regression Hantel et al. 2022 Cohort study Archival database CALGB/Alliance Statistics and Data Management Center (through 8/26/2021; enrollment 1998–2013) SEER and 2010 US Census data Race/ethnicity SES Age Sex ZIP-code Consent forms Enrollment fraction Incidence estimates Preliminary chi-square, Fisher’s exact, and Wilcoxon rank-sum tests Multivariate logistic regression Hanvey et al. 2022 Cohort study Archival database CBTi.p. intervention (2009–2017) Yoga intervention (2017–present) Dichotomized age (@60) Dichotomized race, ethnicity, and racial/ethnic minority status SES composite (income, education, employment 0–7) Dichotomized rurality (large metro vs. other) Psychosocial symptom scores: BDI-II, STAI, MPQ, PSQI Eligibility Decline Reasons for decline Eligible enrollment Voluntary attrition/death Preliminary chi-square tests Logistic regression Survival analysis with GDTMs Hennessy et al. 2022 Meta-analysis Archival database Embase, PubMed, Cochrane Library (1/1/1995–11/18/2020) Age Age restriction Study location Time (10-year period) Binary logistic regression Hori et al. 2007 Case-control study Archival database Review reports submitted as NDA trials from Pharmaceuticals and Medical Devices Agency (Sep 1999–Apr 2005) Cancer Statistics in Japan (2003) Median age (or mean of median group ages) across entire enrolled CCT samples calculated Age-specific incidence rates by cancer type Comparisons of median ages between patient population and CCT accruals by type (unspecified) Housri et al. 2015 Cohort study Internal treatment center, archival database Rutgers Cancer Institute of New Jersey (Jun 2009–Dec 2012) Demographics, stage, grade, receptor status, family history of breast cancer in 1st degree relative, radiation dose, concurrent Tx, site of initial consultation Preliminary chi-square or Fisher’s Exact Logistic regression Huang, Ezenwa, Wilkie, and Judge 2013 Cohort study Internal treatment center, ongoing database “ResearchTracking” (University of Washington Cancer Center, Seattle Cancer Care Alliance) Age Sex Eligibility status Reasons for ineligibility Enrollment status Completion status Withdrawal reasons ANOVAs, Fisher’s exact tests Hue et al. 2022 Case-control study Archival database NCDB (2004–2016) Race (NHW, NHB, Other) ZIP-code median income, %HS edu Age Sez Insurance primary Charlson-Deyo score Stage Preliminary chi-square and Wilcoxon rank-sum tests Multivariable logistic regression Kaplan-Meier and Cox regression survival analyses Jan et al. 2022 Meta-analysis Archival database Clinicaltrials.gov (through 7/19/2019) US Cancer Statistics database GLOBOCAN Race (W, B , AAPI, AI/AN, multi, unknown) Ethnicity (NH, H) Dichotomized age (@65) Sex EF Chi-square and Fisher’s exact tests Javid et al. 2012 Cross-sectional study Multiple NR (survey administration) Demographics: marital status, education, travel, transportation, income Patient Participation/Refusal Questionnaires (reasons) Reasons for ineligibility Trial availability, eligibility, and enrollment Chi-square tests Logistic regression Javier-DesLoges et al. 2022 Cohort study Archival database NCI Clinical Data Update System (2000–2019) Cancer Incidence Data (CDC US Cancer Statistics, 2000–2017) Race/ethnicity (W, B , H, AAPI) Sex Age Diagnostic site Incident population values Multivariate logistic regression Jayakrishnan et al. 2021 Case-control study Archival database FDA drug approvals (7/2007–6/2019) cancer.org, seer.cancer.org (8/1/2020) Age Race (reporting) Chi-square tests, t-tests, MANOVAs Kaanders et al. 2022 Meta-analysis Archival database MEDLINE, Epub Ahead of Print, Embase, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov (2009–2019) Age Performance status Recruitment rate Chi-square and Mann–Whitney U Kanapuru et al. 2023 Case-control study Archival database FDA drug approvals (2006–2019) Race (W, B , Asian, NH/PI, AI/AN, Other, Unknown) Ethnicity (NH, H , Unknown) Age (<65, 65–75, 75+ Sex Country Eligibility Reasons for eligibility Enrollment Pooled descriptive statistics Kanarek et al. 2010 Case-control study Internal treatment center, archival database Johns Hopkins Cancer Registry JH-SKCCC Clinical Research Office (2005–2007) Accrual to cancer case ratio (ACR) to determine ACR “relative risk” for each demographic subgroup to reference group Place of residence via zip codes: Baltimore City, non-Baltimore City catchment area, non-catchment area Race: White, Black, other (including Hispanic individuals) Covariates: age (<20, 20–64, >64), sex, county poverty level (% of individuals at or below poverty in 2003), cancer site (high: hematologic, medium: prostate and gastrointestinal, low: other) Preliminary ANOVAs Poisson regression VIF statistic (multicollinearity SES, race) Keegan et al. 2023 Cohort study Archival database Clinicaltrials.gov Year Reporting quarter Race reporting Quarterly trend in race reporting proportion Frequencies and proportion with SE and CIs Linear regression Khadraoui et al. 2023 Cohort study Archival database SEER, NCDB (2004–2019) Race/ethnicity (W, B , H, Asian, NH/PI, AI/AN) Age Insurance Charlson-Deyo comorbidity Area SES (income, % without HS educational, metropolitan status) Facility variables: location, type Clinical variables: stage, treatment history, grade CCT enrollment Participation-to-prevalence ratios Multivariate logistic regression Kilic et al. 2023 Case-control study Archival database US National Library of Medicine / ClinicalTrials.gov (2004–2021) SEER Race/ethnicity (and reporting; NHW, NHB, NHAPI, NHAIAN, NHUR, Hispanic) Dichotomized age (@65) Sex Enrollment t-tests, Kruskal–Wallis tests Multivariate logistic regression Ko et al. 2015 Cohort study Internal treatment center, archival database Boston Medical Center Clinical Trials Office: BMC Cancer Center (Jan 1, 2010–Dec 31, 2010) Sociodemographic (EMR): age, race/ethnicity, sex, employment, primary spoken language, country of birth, primary insurance, highest education level, marital status Eligibility: dichotomized Ineligibility reason further dichotomized: no open trial vs. not eligible for open trial Enrollment: dichotomized Non-enrollment reason further dichotomized (patient vs. provider decline) Chi-square and t-tests Kwak et al. 2023 Case-control study Archival database NCDB (2004–2018) Race/ethnicity (NHW, NHB, H) Facility type Insurance coverage Preliminary chi-square and Wilcoxon rank sum Multivariate logistic regression Kaplan-Meier survival and Cox regression Ladbury et al. 2022 Case-control study Archival database ClinicalTrials.gov (through 1/4/2020) SEER (2000–2016) Age Race Ethnicity Cancer type Age reporting Race/ethnicity reporting Enrollment incidence disparity Enrollment incidence ratio (EIR) T- and chi-square tests Langford et al. 2014 Cohort study Archival database NCI Community Cancer Centers Program (NCCCP) Clinical Trial Screening and Accrual Log (3/2009–5/2012) Demographic: race/ethnicity, age, sex, country region Consent length, readability CCT refusal, lack of desire to participate, enrollment, physical/medical conditions Consent length, readability CCT refusal, lack of desire to participate, enrollment, physical/medical conditions Preliminary chi-square tests Binary logistic regression Lythgoe, Savage, and Prasad 2021 Case-control study Archival database FDA licensing (1/2006–7/2020) Race (W, B , Asian, AI/AN, Other/multiracial, unknown/missing) Race reporting Descriptive proportions Mishkin, Minasian, Kohn, Noone, and Temkin 2016 Case-control study Archival database CTEP Clinical Data Update Service (2003–2012) SEER (2003–2012) US Census (2010) Demographic variables: race (American Indian, API, Black, White, unknown); ethnicity (Hispanic, non-Hispanic, unknown), age (time of trial registration), insurance (private, Medicaid, uninsured, unknown, 2007–2012; 65+ excluded due to Medicare) Population-based incidence: SEER incidence rates * 2010 Census population within each category Did not use inferential statistics due to the use of complete accrual population Relative differences within subgroups assessed (5%+ differences considered clinically important) Moloney and Shiely 2022 Meta-analysis Archival database MEDLINE (2010–2020) Eligibility criteria imposed Clinical/scientific rationale for criteria imposed Descriptive proportions Qualitative synthesis Murthy, Krumholz, and Gross 2004 Case-control study Archival database CDUS (1996–2002) NCI PDQ Database of Clinical Trials (50 largest trials) SEER (1995–1999) EF: # CCT enrollees/estimated # US cases (adjusted for age and racial/ethnic group) Race/ethnicity: Enrollees Cancer Therapy Evaluation Program categories (1996–2001) – White, Black, API, AI/AN, Hispanic; 2002 – Hispanic ethnicity as separate category for Population Data NHW, NHB, NH-API, NH-AI/AN, Hispanic Cancer incidence: rates determined for each 5-year age range, race, sex è # SEER cases/population SEER county è rates applied to US population Chi-square tests Crude odds ratios Polytomous logistic regression Huber-White robust variance Newman et al. 2004 Case-control study Archival database ACOSOG, SWOG, NCI (Oct, Nov 2003) SEER Proportion by race, by age dichotomized at 65 Descriptive statistics (otherwise NR) Noor et al. 2013 Case-control study Internal treatment center, archival database Thames Cancer Registry Guy’s Hospital phase I clinic Patient data from referrals, notes, Rx records: age at referral, primary tumor, sex, ethnicity, postal code, dichotomized enrollment Population incident cases: TCR SES: Index of Multiple Deprivation: calculated from income, employment, health, education, crime, access, living environment scores assigned to geographic areas; patients assigned scores based on postal code Preliminary crude odds ratios Logistic regression Osann et al. 2011 Cross-sectional study Community outreach CSPOC, LACCSP cancer registries Race/ethnicity: cancer registry; all non-Hispanic individuals grouped as 1 Enrollment/refusal rates Chi-square tests Logistic regression MANOVAs Owens-Walton et al. 2022 Cohort study Archival database ClinicalTrials.gov (2000–2017) SEER (2000–2017) Race/ethnicity (W, B , AAPI, AI/AN, H , multi, unknown/NR) Representation quotient Descriptive representation quotients Palmer et al. 2021 Cross-sectional study Archival database, mail, phone California Cancer Registry Race (African American, Asian American, Latino, White) Age (50–54, 55–64, 65+) Marital status Education Region Language Insurance Health literacy Health status Comorbidities endorsed Treatment history CCT participation (any, behavioral, bio/clinical, none) Multivariate logistic regression Pang et al. 2016 Case-control study Archival database NCI-sponsored cooperative groups trials (1990–2012) SEER (1990–2012) Elderly = 70+ Enrollment disparity difference: absolute difference between est. group proportion in US lung cancer population and that of trial participants Enrollment disparity ratio: group proportion in US lung cancer population divided by that of trial participants Annual percentage of change (APC) in subgroup enrollment APC Joinpoint regression Patel et al. 2023 Cohort study Archival database University of Michigan Health Rogel Cancer Center clinical trials database EMR Age Sex Race Marital/family status Employment Insurance Charlson Comorbidity Index Clinical factors: type, stage, histology CCT Eligibility Offered CCT CCT enrollment Preliminary chi-square tests Multivariate logistic regression Patel et al. 2020 Cross-sectional study Archival database iCanCare Study ClinicalTrials.gov SEER (Georgia, Louisiana, 2013–2014) Age: −50, 51–65, >65 Comorbidities: 0 vs. 1+ Surgeries, chemo, radiation Stage (0–II) White, Black, Latina, Asian, Other/unknown Acculturation: high vs. low Marital status Education: −HS, some college, technical vs. college+ Income: <$40,000 vs. $40,000+ Insurance: none, Medicaid, other public, Medicare, private Geographic site Distance from treatment center: −30, 31+ Employment and flexibility (dichotomized) Decision-making style: 5-point Likert scale (intuitive to rational) Outcomes dichotomized Preliminary chi-square tests Logistic regression Patki et al. 2023 Meta-analysis Archival database CENTRAL, MEDLINE, Embase (through 2010–4/24/2020) Race, ethnicity, SES, and educational attainment reporting Descriptive proportions of CCT participant race, ethnicity, SES Additional outcomes where reported: Age Stage SES group Education Eligibility criteria Study outcomes Descriptive statistics and qualitative synthesis Perni, Moy, and Nipp 2021 Cohort study Archival database Massachusetts General Hospital Cancer Center EHRs (10/1/2011–11/30/2014) Race/ethnicity Sex Age Insurance status Marital status Income (median ZIP code) CCT phase I, II, and III enrollment Preliminary chi-square and Wilcoxon rank-sum tests Multivariate logistic regression Pirl et al. 2018 Meta-analysis Archival database 2012, 2017 ASCO statements on palliative care in oncology PubMed Race/ethnicity Race/ethnicity reporting Other demographic data reporting: age, sex, marital status, education, income, religion Trial setting Language eligibility requirements Descriptive statistics Pittell et al. 2023 Cohort study Archival database Flatiron Health Inc. (1/2017–12/31/2022) Age Race/ethnicity (W, B , L) Cancer type Pre/post-COVID ECOG Region Practice type Sex CCT participation Stratified hazard models Ramamoorthy et al. 2018 Case-control study Archival database CDER, FDA (Drugs@FDA) Race/ethnicity Age Sex Time period (2008–2013; 2014–2017) Descriptive statistics (proportions) Reihl et al. 2022 Meta-analysis Archival database PubMed (1/1/2000–12/31/2019) ClinicalTrials.gov Central Brain Tumor Registry of the US (CBTRUS (2000–2017) SEER-18 (2000–2017) Sex Race/ethnicity (W, Asian, B , H) CCT enrollment Survival Stratified, population-based incidence and mortality rates Chi-square and Fisher’s exact tests Riaz et al. 2023 Meta-analysis Archival database MEDLINE (through 2/2021) Global Burden of Disease SEER-21 (2000–2018) Dichotomized age (@65) Race/ethnicity (AA/B, AAPI, W) Outcomes using population-based incident estimates: Enrollment incidence ratios Demographic trial proportions Meta-regression with random effects Saphner et al. 2021 Case-control study Archival database Aurora Health Care Cancer Registry (8/1/2013–7/31/2019) American Community Survey (2014–2018) Age Sex Race (W, B , Asian, NA/AN, HI/PI) Ethnicity Area SES -Median household income, standardized to range from 0 to 1 -Percentage of people below the federally defined poverty line -Median value of owner-occupied values, standardized to range from 0 to 1 -Percentage of people aged 16 years or older in the labor force who are unemployed (and actively seeking work) -Percentage of people aged 25 years or older with at least 4 years of college -Percentage of people aged 25 years or older with less than a 12th grade -Percentage of households containing one or more person per room CCT participation Preliminary chi-square and Mann–Whitney tests Multivariate logistic regression Sawaf et al. 2023 Meta-analysis Archival database PubMed (through 12/2019) NCDB (2010–2019) Age Sex Race/ethnicity Rurality Facility type, location Demographic and socioeconomic reporting Qualitative synthesis Chi-square and one-sample t-tests where quantification possible Scalici et al. 2015 Case-control study Archival database GOG website (1985–2013 publications) CDC Type of study CDC age-adjusted incidence for comparison between expected and observed cases by race (ratio W:B) Race/ethnicity: B, W Tumor site: ovary, endometrium, cervix, sarcoma Year published: 1993 and lower, 1994–2002, 2003–2008, and 2009–2013) Chi-square and t-tests ANOVAs Sedrak et al. 2022 Cohort study Archival database NCI Community Oncology Research Program (NCORP, 1/1/2016–12/31/2019) Primary: Age Reasons for ineligibility Reasons for decline Enrollment Sociodemographic covariates: sex, marital status, ethnicity, SES indicators, comorbidity types Chi-square analyses Shah et al. 2022 Meta-analysis Archival database ClinicalTrials.gov Weighted mean/median age Weight mean/median calculation Shinder et al. 2023 Case-control study Archival database NCDB (2004–2014) Age Race/ethnicity Sex Insurance Stage Charlson-Deyo comorbidity Area median income Area % HS education Facility location, type CCT participation Multivariate logistic regression Steventon et al. 2024 Meta-analysis Archival database Licensed systemic anti-cancer therapies (1/11/2012–1/11/2022) Race/ethnicity Continent Descriptive statistics Stewart, Bertoni, Staten, Levine, and Gross 2007 Case-control study Archival database NCI CDUS, NCI CTEP (2000–2002) SEER (2000–2002) US Census (2000) Race/ethnicity: NHW, NHB, API, AI/AN, Hispanic from Census (2000) Age: 5-year intervals 20–74, 75+ from Census (2000) Cancer incidence rates: SEER EF: # enrollees/estimated # US cancer type cases Logistic regression Talarico, Chen, and Pazdur 2004 Case-control study Archival database FDA (1995–2002) SEER-11 (1995–1999) Age: %65+, %70+, %75+ Chi-square tests Tharakan, Zhong, and Galsky 2021 Case-control study Archival database FDA cancer drug approvals (2015–2018) American Cancer Society (2012–2016) Racial enrollment distribution per CCT Geographic location per CCT Disparity score per CCT (#Black enrollees/US incidence per cancer) Pearson correlation Unger et al. 2020 Case-control study Archival database FDA drug approvals (2008–2018) NCTN data (SWOG Cancer Research Network) SEER % Black race Trial sponsorship: pharmaceutical company, SWOG Cancer type Tests of proportions Unger, Gralow, Albain, Ramsey, and Hershman 2016 Cohort study Internal treatment centers (8), archival database NR Age Race/ethnicity Sex Income (@ $50k) Education Distance from clinic Disease status Logistic regression Unger et al. 2013 Cross-sectional study Community outreach NexCura treatment decision tool SES (income, education) Age Race Comorbidity score Discussion of CCT with provider CCT beliefs and attitudes CCT enrollment Discussion of CCT with provider CCT beliefs and attitudes CCT enrollment Multivariate logistic regression VanderWalde et al. 2022 Case-control study Archival database Alliance for Clinical Trials in Oncology SEER Age Trial characteristics: disease site, trial phase, # trial modalities Enrollment disparity difference Linear regression Wagar et al. 2022 Case-control study Archival database ClinicalTrials.gov SEER (1992–2018) Race/ethnicity Sex Age Cancer type Enrollment fraction Enrollment fractions with odds ratios Yekedūz et al. 2021 Case-control study Archival database FDA drug approvals (1/1/2006–6/30/2020) ClinicalTrials.gov SEER Age Sex Race/ethnicity Comorbidity presence (including HBV, HBC, HIV) Organ dysfunction Brain metastases ECOG CCT reporting on the above variables CCTs reporting certain characteristics as exclusion criteria FDA phase III CCTs/MEDLINE (1/1/2006–6/30/2020) SEER Yonemori et al. 2010 Case-control study Archival database NDA trials (1999–2008) Ministry of Health, Labor, Welfare) SEER (2002–2006) Median age of enrollees and proportion of those >65 by cancer site, drug, and application Age-specific incidence from Cancer Statistics in Japan (2013) * age-specific population (MHLW) to estimate age-specific new cases SEER for age-specific accrual information Comparison of age median in US and Japanese populations to that of enrollees Comparison of proportion >65 in US and Japanese populations to that of enrollees Zafar et al. 2011 Cohort study Internal treatment center, archival database KCI Phase I clinical trial service (1995–2005) Via retrospective medical review: Demographics: age, gender, race Tumor type, PS, Tx status, enrollment status, Tx details, referring physician Three orthogonal groups: considered not enrolled (PC), enrolled but not treated (PE), treated (PT) Fisher’s exact test Zhao et al. 2024 Meta-analysis Archival database Clinicaltrials.gov (through 9/13/2022) Difference in median age (CCT v. population) Age reporting Annual percent change Joinpoint regression Mann–Whitney U and Kruskal–Wallis test Zullig et al. 2016 Case-control study Archival database CTEP (1996–2009) NCCCR (1996–2009) Incidence data: North Carolina Central Cancer Registry (NCCCR) Trial accrual data via CTEP Area Health Resource Files for certain demographic characteristics Accrual rate: #annual enrollment/# new cases, stratified by race, sex, county, and year Preliminary chi-square tests Logistic regression Zuniga et al. 2020 Case-control study Archival database ClinicalTrials.gov (Feb 2000–Feb 2019) SEER (2001–2015) American Joint Committee on Cancer (6e) TNM staging data (2004–2015) Study representation proportion Identification of targets One-sample proportion tests Note: Abbreviations included in this table are utilized as follows, listed alphabetically: AA = African American; AAPI = Asian American or Pacific Islander; ACOSOG = American College of Surgeons Oncology Group; AI/AN = American Indian/Alaska Native; ANOVA = analysis of variances; API = Asian or Pacific Islander; B = Black; BMC = Boston Medical Center; CBTRUS = Central Brain Tumor Registry of the United States; CCC = comprehensive cancer center; CCT = cancer clinical trial; CCR = California Cancer Registry; CCSG = Cancer Center Support Grant; CDC = Centers for Disease Control and Prevention; CDUS = Clinical Data Update Service; CI = confidence interval; CINAHL = Cumulative Index of Nursing and Allied Health Literature; CSPOC = Cancer Surveillance Program of Orange County; CTED = Clinical Trials on Chronic Thromboembolic Disease; CTEP = Clinical Trial Evaluation Program; CTMS = Clinical Trials Management System; DF/HCC = Dana-Farber/Harvard Cancer Center; ECOG = Eastern Cooperative Oncology Group; EMPacT = Enhancing Minority Participation in Cancer Clinical Trials; EH/MR = electronic health/medical record; FDA = Food and Drug Administration; FFS = fee-for-service; GLOBOCAN = Global Cancer Observatory; GOG = Gynecologic Oncology Group; H = Hispanic; HS = high school; JH-SKCCC = Johns Hopkins Sidney Kimmel Comprehensive Cancer Center; ISS = International Staging System; KCI = Karmanos Cancer Institute; L = Latine; LACCSP = Los Angeles County Cancer Surveillance Program; MDCSS = Metropolitan Detroit Cancer Surveillance System; MDS = myelodysplastic syndromes; MHLW = Ministry of Health and Labor, Welfare; NCDB = National Cancer Database; NCI = National Cancer Institute; NDA = new drug application; NH = non-Hispanic; NIH = National Institutes of Health; O:E = observed:expected; NR = not reported; PDQ = Physician Data Query; PS = performance status; SEER = Surveillance, Epidemiology, and End Results; SE = standard error; SES = socioeconomic status; SWOG = Southwest Oncology Group; TCR = Thames Cancer Registry; TNM = Tumor Nodes Metastases; UCSF = University of California – San Francisco; W = White.

Table 3. Social, economic, and medical indicators of marginalization Authors Year Age Race/ethnicity Sex SGM status SES Ability & Comorbidities Abbas et al. 2022 Among accruals: 65+: 32.1% Among population controls: 65+: 59.1% Among accruals: NHW: 80.9% NHB: 7.6% AAPI: 3.3% H: 5.5% Other: 2.8% Among population controls: NHW: 77.5% NHB: 11.9% AAPI: 3.2% H: 5.6% Other: 1.7% NR NR Among accruals: Income <$40k: 15.7% Private insurance: 57.5% ZIP HS edu<79%: 16.2% Among population controls: Income <$40k: 19.6% Private insurance: 34.3% ZIP HS edu<79%: 21.8% NR Abi Jaoude et al. 2020 NR NR NR NR NR All trials: ECOG 0–1: 96.4% ECOG 2–4: 3.6% Acoba, Sumida, and Berenberg 2022 NR Of accruals: White: 35% Chinese: 6% Filipino: 16% Japanese: 27% Native Hawaiian: 16% Of population controls: White: 31% Chinese: 7% Filipino: 11% Japanese: 29% Native Hawaiian: 22% NR NR NR NR Ajewole et al. 2021 NR Of all participants: White: 71.5% Asian: 16.9% Black: 2.5% Hispanic: 2.3% NR NR NR NR Al Hadidi et al. 2022 NR 2–5% (per study) NR NR NR NR Aldrighetti et al. 2021 Used age-adjusted incidence rates Of accruals: NHW: 82.3% B: 10.0% AAPI: 4.1% H: 3.4% AI/AN: 0.3% NR NR NR NR Awad et al. 2020 Address via age-adjusted incidence CCT participants (1995–2018) W: 79% B: 6% Other: 16% Women NR Briefly address potential role of SES NR Baldini et al. 2022 Of participants: <70: 82.3% 70+: 17.7% NR Of <70 survey participants: F: 55.5 Of 70+ survey participants: F: 47.6% NR Of <70 survey participants: <HS: 60.4% FDI: −0.4 Of 70+ survey participants: <HS: 46.9% FDI: -0.3 NR Baquet, Ellison, and Mishra 2009 Among accruals: 0–19: 13.8% 20–59: 48.3% 60+: 37.9% Among accruals: (1999–2002, by sex) WM: 29.5% BM: 9.6% WF: 45.6% BF: 10.3% OM: 2.4% OF: 4.2% Among accruals: F: 59.2% NR % of accrued patients among age-adjusted incidence within each category Lowest quartile material deprivation: 2.91% (F), 1.48% (M) Highest quartile material deprivation: 1.58% (F), 1.62% (M) Lowest quartile social class: 1.67% (F), 1.46% (M) Highest quartile social class: 3.15% (F), 1.85% (M) Insurance comparisons within accruals and incidence population % uninsured Accruals: 3.4% Population: 13.4% % Medicaid Accruals: 3.2% Population: 6.5% % Private Accruals: 65.4% Population: 77% Briefly discuss potential role of comorbidity in compromising diverse representation Behrendt, Hurria, Tumyan, Niland, and Mortimer 2014 Of total patients: M = 55.7 Of total patients: Other Caucasian: 42.2% African: 5.3% Asian: 16.3% Eastern European: 1.3% Latin American: 28.3% Middle Eastern: 6.5% Women NR Of total patients: ZIP-code median income: <$45,000: 14.4% $45,500–$65,499: 37.4% $65,500–$85,499: 32.9% $85,000+: 15.3% Zip-code %racial/ethnicity-matched women 25+ without HS edu <5%: 20.9% 5–30%: 60.3% 30+%: 18.8% NR, comment on lack of availability in limitations Bero et al. 2021 NR Race Of US CCT participants: W: 84.8% B: 11.8% Asian: 2.9% Other: 0.5% Of population: W: 72.2% B: 12.7% Asian: 5.6% Other: 9.5% Ethnicity Of US CCT participants: H: 9.8% Of population: H: 18.1% Of US CCT participants: F: 41.5% NR NR NR Borad et al. 2020 Of CCT enrollees: Mean: 65.8 Average Median: 63.3 MM epidemiology: Mean: 71.5 Average Median: 71.5 MM epidemiology: Mean: 71.5 Average Median: 71.5 NR NR NR NR NR Borno et al. 2019 Of accruals: 0–64: 70% 65+: 30% Of accruals: NHW: 72% NHB: 4% Asian: 12% Hispanic: 10% Other: 2% Of accruals: F: 46% NR Of accruals: Medicaid: 8% Medicare: 31% Private: 40% Other: 1% Missing: 20% Uninsured: 0% NR Brierley et al. 2020 Of non-accruals: Median: 69 (IQR: 61–76) Of accruals: Median: 68 (IQR: 61–73 years) Of non-accruals: W: 87% B: 5.2% Asian: 1% Other: 6.9% Hispanic: 5.4% Of accruals: W: 88% B: 4.2% Asian: 1.6% Other: 6.2% Hispanic: 3.8% Of non-accruals: F: 39% Of accruals: F: 29% NR Of non-accruals: <$48,138: 26.6% $48,138–$63,083: 25.4% $63,083–$90,412: 24.4% $90,412+: 23.5% Of accruals: <$48,138: 19.6% $48,138–$63,083: 23.5% $63,083–$90,412: 27.4% $90,412+: 29.5% Report on comorbidity, functional status, and underrepresented disease as focus Bruno, Li, and Hess 2024 Mean: 59.5 % Black (total): 25.2% Total: F: 47.3% NR Applied to Medicaid-exclusive population Report on disease characteristics Bruno et al. 2022 Total means: NSCLC: 68.9 NS-NSCLC: 68.3 CRC: 63.1 Breast: 63.8 % of White participants (relative to all White patients):: NSCLC: 3.9% NS-NSCLC: 3.9% CRC: 2.9% Breast: 5.8% % of Black participants (relative to all Black patients): NSCLC: 1.9% NS-NSCLC: 1.2% CRC: 2.9% Breast: 4.4% Total % F: NSCLC: 48.1% NS-NSCLC: 52.6% CRC: 43.5% Breast: 99.0% NR Reported insurance status across patients, clinic practice volume, and practice type stratified by diagnostic site and dichotomized race Reported staging and ECOG stratified by diagnostic site and dichotomized race Canoui-Poitrine et al. 2019 % group CCT invited: 65–69: 39% 70–74: 30% 75–79: 24% 80+: 7% Of SAGE population: 65–69: 27% 70–74: 23% 75–79: 23% 80+: 27% Of SAGE population: 65–69: 27% 70–74: 23% 75–79: 23% 80+: 27% NR % group CCT invited: M: 55% Of SAGE population: M: 56% Of SAGE population: M: 56% NR Of SAGE population: Higher education: 34% % group CCT invited: Comorbidity: 67% Performance status 2+: 8% Of SAGE population: Comorbidity: 73% Performance status 3–4: 4% Of SAGE population: Comorbidity: 73% Performance status 3–4: 4% Casey et al. 2023 Of RCT participants: Mean: 57.3 Of RCT participants: W: 83.2% AAPI: 6.3% B: 3.2% H: 6% Of RCT participants: F: 40.5% NR Commented on geographical distribution of RCTs and intersection of county-level insurance coverage with race Briefly address impact of staging and comorbidities Costa, Hari, and Kumar 2016 Of non-accruals: Median = 69 Of accruals: Median = 61 Expected: %minority accruals: 36.7% Observed: %minority accruals: 19.1% Expected male% accruals: 58.4% Observed male% accruals: 56.9% NR NR Reported on higher enrollment of lower risk patients by stage I: 37.1% II: 39% III: 24.8% Choradia et al. 2024 Of participants: 65+: 22.9% Of participants: W: 76.1% B: 12.0 AAPI: 4.6% AI/AN: 0.3% H: 7.1% Of participants: F: 41.7% NR NR NR Craig, Gilbery, Herndon, Vogel, and Quinn 2010 Of non-accruals: Median (IQR): 73 (69–78) Of accruals: Median (IQR): 72 (68–76) Of non-accruals: White: 80% Black: 9% Hispanic: 4% Other: 6% Of accruals: White: 85% Black: 6% Hispanic: 4% Other: 5% Men NR Of non-accruals: Median income (IQR): $46,273 ($35,351–$61,363) Of accruals: Median income (IQR): $51,656 ($38,763–$69,754) Of non-accruals: Comorbidity index 0: 75% Of accruals: Comorbidity index 0: 78% Diehl et al. 2011 NR Range of proportions, of accruals: early-stage breast: AA 6.4–14.0% HA 2.7–4.0% regionally advanced breast: AA 14.0–15.2% HA 4.2–4.8% non-metastatic lung: AA 8.0–11.0% HA 2.7–2.3% metastatic lung: AA 11.3% HA 2.6% NR NR Briefly report on SES in introduction, scarcely address in discussion Briefly report on early-stage eligibility criteria prohibiting diverse representation Dressler et al. 2015 Of accruals: Age median (range): 58.3 (18.8–93.5) Of accruals: White: 83.0% AA: 11.1% Asian: 2.5% Other: 1.0% Unknown: 2.4% White: 85.1% non-White: 14.9% Of accruals: F: 59.3% NR NR NR Du, Gadgeel, and Simon 2006 Of non-accruals: 70+: 24% Of accruals: 70+: 10% Of non-accruals: AA: 45% non-AA: 55% Of accruals: AA: 25% non-AA: 75% Of non-accruals: F: 43% Of accruals: F: 32% NR Of non-accruals: Low: 52% Medium: 28% High: 21% noncommercial insurance: 63% Of accruals: Low: 37% Medium: 30% High: 33% non-commercial insurance: 45% Of non-accruals: PS = 0: 31% Heart disease: 18% Diabetes: 13% COPD: 16% Comorbidities >0: 39% Of accruals: PS = 0: 36% Heart disease: 16% Diabetes: 9% COPD: 13% Comorbidities >0: 31% Dudipala et al. 2023 Of total cohort assessed: M: 70 Of total cohort assessed: B: 35.1% W: 47.5% H: 9.9% Of total cohort assessed: F: 47.5% NR Of total patients: HS edu or <: 77.9% <$84k median household income: 70.6% Accounted for staging/subtype (25%) comorbidities/low functional status (17.6%) as potential limiting factor for enrollment among CCT discussed subsample Duma et al. 2018 Of current trial participants: 65+: 36.0% 2013 SEER: 65+: 60.0% Of current trial participants: NHW: 83.4% AA: 6.0% H: 2.6% AAPI: 5.3% AI/AN: 0.3% Other: 2.4% 2013 SEER: NHW: 79.0% AA: 10.0% H: 7.0% AAPI: 3.3% AI/AN: 0.3% Other: NR Of current trial participants: F: 41.0% 2013 SEER: F: 50.0% NR NR NR Earl et al. 2023 NR Of enrollees: W: 93.2% B: 0.9% Asian: 1.2% NH/PI: 0.4% AI/AN: 0.0% O: 2.8% Of enrollees: F: 42.6% NR Sex, race, and ethnicity outcomes stratified by county classification County income and edu utilized as secondary analysis predictors NR Elshami et al. 2022 Of total patients: 70+: 41.0% Of total patients: NHW: 70.0% NHB: 12.4% H: 7.8% O: 9.8% Of total patients: F: 41.5% NR Of total patients: <$53,353: 40.0% “Less educated:” 46.5% Private insurance: 31.5% Distance 11.6 mi+: 47.4% Of total patients: Charlson-Deyo score 2+: 14.7% Stage 4: 40.1% Eskander et al. 2022 Of enrollees: M: 64.0 Of non-enrollees: M: 69.0 Of enrollees: W: 90.1% NW: 9.9% Of non-enrollees: W: 83.2% NW: 16.8% Of enrollees: %F: 46.0% Of non-enrollees: %F: 48.9% NR Of enrollees: Private insurance: 49.4% Median income <$38k: 11.8% <HS 21%+: 9.3% Non-metropolitan: 14.5% Of non-enrollees: Private insurance: 30.9% Median income <$38k: 17.7% <HS 21%+: 16.9% Non-metropolitan: 15.5% Of enrollees: Charlson-Deyo 1+: 22.5% Stage 4: 65.8% Of non-enrollees: Charlson-Deyo 1+: 34.7% Stage 4: 52.0% Fakhry et al. 2023 NR Of cumulative enrollees in all studies: W: 83.7% B: 5.1% AI/AN: 0.0% Asian: 0.14% NH/PI: 0.0% Multiracial: 0.0% H: 2.2% Briefly address sex/gender reporting NR Addresses intersectionality between racial/ethnic representation and low socioeconomic strain NR Fayanju et al. 2019 Non-accruals: <40: 5% 40–64: 67.1% 65+: 27.9% Accruals: <40: 5.6% 40–64: 56.3% 65+: 38.1%% Non-accruals: NHW: 73.7% NHB: 10.7% API: 3% Native American: 0.3% Hispanic: 5% Other: 6.4% Accruals: NHW: 83.5% NHB: 7.3% API: 2.4% Native American: 0.2% Hispanic: 4% Other: 2.6% Women NR Non-accruals: <$38,000: 15.4% $38,000–47,999: 21.1% $48,000–62,999: 26.2% $63,000+: 35.6% >93% of area HS grad: 27.4% Accruals: <$38,000: 12.9% $38,000–47,999: 19.8% $48,000–62,999: 24.8% $63,000+: 33% >93% of area HS grad: 32.5% Explicitly reported on race/ethnicity*SES intersection Briefly discuss comorbidities and effects of ECOG performance status on age and racial underrepresentation Freudenburg et al. 2022 Reported per study included Of study participants: W: 81–98% AA: 2–8% H: 2–5% Reported per study included NR NR NR Gopishetty, Kota, and Guddati 2020 Of accruals: Colon %65+: 28.8% Lung %65+: 38.8% Breast %65+: 14.7% DLBCL %65+: 39.2% AML %65+: 29.0% ALL %65+: 9.6% Of accruals: Colon Asian: 21.2% AA: 2.6% W: 74.3% Other: 2.0% Lung Asian: 26.1% AA: 30.6% W: 39.7% Other: 3.7% Breast Asian: 17.4% AA: 3.6% W: 73.8% Other: 5.2% DLBCL Asian: 16.6% AA: 1.5% W: 77.7% Other: 4.2% AML Asian: 2.3% AA: 2.3% W: 92.9% Other: 2.5% ALL Asian: 5.9% AA: 6.7% W: 77.5% Other: 9.9% NR NR NR Contextualize age-related disparities in comorbidity risk and ineligibility Gordis et al. 2022 Participants: M: 59 years NCDB: M: 58.4 years Participants: W: 88.2% AA: 4.8% H: 1.8% AAPI: 0.3% Other: 2.5% NCDB: W: 67.7% Participants: F: 11.8% NCDB: F: 32.1% NCDB: F: 32.1% NR NCDB only: High SES: 65.2% Participants: No smoking Hx: 50% No alcohol use: 28.7% Primary tongue site: 41.4% NCDB: Primary tongue site: 65.2% NCDB: Primary tongue site: 65.2% Grant et al. 2020 Briefly mention possible effects of age in disparities Report explicitly on racial/ethnic representativeness of CCTs NR NR Briefly mention possible effects of SES factors in disparities NR Green et al. 2022 CCT participants: 75+: 85+: Non-participants: 75+: 85+: CCT participants: Asian: 1.5% B: 5.8% W: 86.7% Oth: 6.0% Non-participants: Asian: 1.5% B: 8.0% W: 86.0% Oth: 4.5% CCT participants: M: 55.3% Non-participants: M: 49.5% NR CCT participants: Median income $60,430+: 57.0% Metro: 87.2% Non-participants: Median income $60,430+: 47.4% Metro: 81.7% CCT participants: Charlson score 2+: 13.1% Non-participants: Charlson score 2+: 26.1% Grette et al. 2021 Accounted for age-adjustment in comparisons Of CCT participants: W: 70% B: 5% Asian: 20% Other: 6% Primarily AFAB (i.e., breast, GYN) NR NR NR Gross, Filardo, Mayne, and Krumholz 2005 Restricted sample to 65+ Of accruals: 65–69: 43.4% 70–74: 29.2% 75–79: 21.0% 80+: 6.4% Of non-accruals: 65–69: 25.4% 70–74: 26.5% 75–79: 23.0% 80+: 25.1% Of accruals: White: 86.7% AA: 4.9% Asian: 5.4% Hispanic: 3.0% Of non-accruals: White: 88.3% AA: 7.0% Asian: 3.0% Hispanic: 1.7% Women NR Of accruals: %Medicaid: 2% 0.13%+ below poverty level: 20.9% % unemployment 5.6+: 18.7% Of non-accruals: %Medicaid: 10% 0.13%+ below poverty level: 24.9% % unemployment 5.6+: 25.1% Speculate on relationships between SES and later staging Guerrero et al. 2018 NR NR: 67.0% W: 25.9% Asian: 5.0% AA: 1.1% H: 0.2% Other: 0.9% NR NR NR NR Hantel et al. 2024 Total: Median: 67 Total: NHW: 85.9% NHB: 4.3% NHA: 3.7% HW: 4.5% Oth: 1.3% Total: F: 45% NR Total: sYI: 6/10 Distance: 50 km Private insurance: 30.6% Briefly comment on limited availability of such data and potential role Hantel et al. 2022 Of enrollees: 60–79: 38.8% 80+: 2.5% Of enrollees: NHW: 81.7% NHB: 7.5% NH-NA: 0.88% NH-Asian: 2/44% H: 5.33% Oth: 2.17% Of enrollees: F: 42.4% NR Of enrollees: Area deprivation index 76–100%ile: 18.10% Urban: 76.4% CCC: 62.5% NR Hanvey et al. 2022 Of total: 60+: 56.2% Of total: Non-White: 15.9% Hispanic: 5.1% POC: 20.3% All AFAB NR Examined as longitudinal attrition predictor Depression, anxiety, pain, and sleep examined as longitudinal attrition predictor Hennessy et al. 2022 Median age: 62 y.o. Age restriction: 32% Median age restriction: 75 NR NR NR NR NR Hori et al. 2007 Of all Japanese cancer population: Median(range) = 69 (54–75) %65+: 64% Of Japanese CCT accruals (68 trials): Median difference compared to population: 7 (−16–33) %trials median age < population: 88.2% Report explicitly on underrepresentation of older (65+) cancer patients Japanese nationality (no further specification) NR NR NR Contextualized findings within comorbidity, functional status, and eligibility criteria Housri et al. 2015 Of accruals: <60: 60% 65+: 40% Of non-accruals: <60: 55.3% 65+: 44.7% Of accruals: Dichotomized W: 74.6% NW: 25.4% Full categories: NHW: 74.6% Black: 13.1% Asian: 6.9% Hispanic: 5.4% Of non-accruals: Dichotomized W: 59.8% NW: 40.2% Full categories: NHW: 59.8% Black: 15.2% Asian: 12.9% Hispanic: 12.1% Women NR NR Staging Of accruals: Tis = 22.3% T1 = 69.2% T2 = 8.5% Of non-accruals: Tis = 18.2% T1 = 59.8% T2 = 22% Huang, Ezenwa, Wilkie, and Judge 2013 Of total pain referrals: M = 53.6 Of total symptom referrals: M = 52.9 Of total referrals: NHW: 79% Minority: 13% Unknown: 8% Of total referrals: M: 41% F: 59% NR NR NR Hue et al. 2022 Of CCT enrollees: Stage I–III: 64 Stage IV mean: 63 Of non-enrollees: Stage I–III: 69 Stage IV mean: 68 Of CCT enrollees: Stage I–III: NHW: 86.3% NHB: 5.7% Oth: 8.0% Stage IV: NHW: 85.9% NHB: 4.8% Oth: 9.3% Of non-enrollees: Stage I–III: NHW: 75.9% NHB: 10.9% Oth: 13.2% Stage IV: NHW: 73.9% NHB: 12.1% Oth:14.0% Of CCT enrollees: Stage I–III: F: 49.5% Stage IV: F: 44.5% Of non-enrollees: Stage III: F: 50.4 Stage IV: F: 46.9% NR Of CCT enrollees: Stage I–III: Median ZIP income <$40,227: 13.4% ZIP w/o HS Edu 17.6%+: 12.9% Private insurance: 47.5% Stage IV: Median ZIP income <$40,227: 11.4% ZIP w/o HS edu 17.6%+: 11.6% Private insurance: 51.7% Of non-enrollees: Stage I–III: Median ZIP income <$40,227: 18.6% ZIP w/o HS Edu 17.6%+: 20.9% Private insurance: 31.3% Stage IV: Median ZIP income <$40,227: 19.1% ZIP w/o HS Edu 17.6%+: 20.6% Private insurance: 32.5% Of CCT enrollees: Stage III: Charlson-Deyo 3+: 1.2% Stage IV: Charlson-Deyo 3+: 0.7% Of non-enrollees: Stage III: Charlson-Deyo 3+: 2.9% Stage IV: Charlson-Deyo 3+: 3.5% Jan et al. 2022 Of all CCT participants: 65+: 46.7% Of all CCT participants: W: 44.3% B: 3.6% AAPI: 47.4% Unk: 4.4% Of all CCT participants: NR NR NR Javid et al. 2012 Among eligible respondents: %65+ trial available: Yes: 27% No: 30% %65+ trial eligible: Yes: 24% No: 37% %65+ trial enrolled: Yes: 21% No: 26% %65+ trial eligible: Yes: 24% No: 37% NR AFAB-exclusive NR % Distance >50 mi, trial enrolled: Yes: 23% No: 34% Addressed at item level regarding reasons for ineligibility and intersection with age (dichotomized 65+) Javier-DesLoges et al. 2022 Of CCT participants: 65+: 33.8% US rate: 65+: 44.1% Of CCT participants: NHW: 81.3% B: 8.7% H: 4.8% AAPI: 2.8% NA: 0.3% Oth: 2.0% US rate: NHW: 78.5% B: 11.6% H: 5.9% AAPI: 2.6% NA: 0.5% Oth: 0.9% Of CCT participants: F: 71.7% US rate: F: 49.2% NR NR NR Jayakrishnan et al. 2021 Of CCT participants: M: 61 Race reporting only: 85.4% NR NR Briefly mention potential role in explaining findings Briefly mention potential role in explaining findings Kaanders et al. 2022 Age restriction: 42% CCT participants: Median: 57 years Clinical population: 64 years NR NR NR NR >70 Karnofsky restriction: 18% CCT participants: >70%: 0–1 PS or 90–100 Karnofsky WHO/ECOG/ Zubrod restriction 0–1: 21% CCT participants: Kanapuru et al. 2023 Of screened patients: 65–75: 41% 75+: 19% Of screened patients: W: 83% Asian: 7% B: 4% Oth: 2% H: 4% Of screened patients: F: 45% NR NR Briefly address potential role of comorbidity Kanarek et al. 2010 Of non-accruals: Baltimore: <20: 3.1% 20–64: 58.8% 65+: 38.1% Non-Baltimore: <20: 2.8% 20–64: 64.4% 65+: 32.8% Non-catchment area: <20: 2.2% 20–64: 68.8% 65+: 29.0% Of accruals: Therapeutic: <20: 9.9% 20–64: 61.7% 65+: 25.5% Non-therapeutic: <20: 9.7% 20–64: 66.9% 65+: 20.1% Of non-accruals: Baltimore: W: 43.0% B: 55.4% O: 1.6% Non-Baltimore: W: 85% B: 11.0% O: 4.0% Non-catchment area: W: 91.6% B: 5.4% O: 3.0% Of accruals: Therapeutic: W: 85.4% B: 10.9% O: 3.6% Non-therapeutic: W: 83.1% B: 13.8% O: 2.7% Of non-accruals: Baltimore: M: 49.8% F: 50.2% Non-Baltimore: M: 58.5% F: 41.5% Non-catchment area: M: 72.9% F: 27.1% Of accruals: Therapeutic: M: 57.5% F: 42.5% Non-therapeutic: M: 54.7% F: 45.3% County poverty quartiles: Of non-accruals: Baltimore: Least poor: 0% 2: 0% 3: 0% Poorest: 100% Non-Baltimore: Least poor: 87.6% 2: 8.9% 3: 0.5% Poorest: 3.0% Non-catchment area: Least poor: 30.2% 2: 23.6% 3: 20.2% Poorest: 9.6% Of accruals: Therapeutic: Least poor: 69.4% 2: 10.9% 3: 4.7% Poorest: 12.6% Non-therapeutic: Least poor: 68.9% 2: 9.1% 3: 4.7% Poorest: 14.5% NR Keegan et al. 2023 NR Race reporting: 73.4% studies reported race/ethnicity NR NR NR NR Khadraoui et al. 2023 Of CCT enrollees: M: 60.4 Of non-enrollees: M: 62.9 Of CCT enrollees: W: 85.8% B: 7.1% H: 3.8% Asian: 2.2% NH/PI: 0.2% AI/AN: 0.6% Oth: 9.7% Of non-enrollees: W: 78.7% B: 10.0% H: 6.8% Asian: 3.3% NH/PI: 0.3% AI/AN: 0.3% Oth: 11.3% All AFAB NR Of CCT enrollees: Private insurance: 58.2% Median income <$46,277: 12.4% %w/o HS edu 15.3%+: 12.2% Rural: 1.6% Of non-enrollees: Private insurance: 45.8% Median income <$46,277: 16.9% %w/o HS edu 15.3%+: 21.5% Rural: 1.6% Of CCT enrollees: Charlson-Deyo 2+: 2.7% Stage IV: 26.6% Of non-enrollees: Charlson-Deyo 2+: 5.7% Stage IV: 12.4% Kilic et al. 2023 Of age-reporting CCTs (avg): 65+: 51% Of race-reporting CCTs (avg): NHW: 82% NHB: 9% NHAPI: 4% NHAIAN: 0.3% NHUR: 3 H: 2% Of sex-reporting CCTs (avg): F: 44% NR Briefly discuss potential role of SES NR Ko et al. 2015 Of total screens: M = 61 Of total screens: NHW: 44% NHB: 40% Hispanic: 9% Asian: 3% Other: 4% Of total screens: M: 39% F: 61% NR Of total screens: Insurance Public: 66% Private: 24% Uninsured: 10% Education HS: 26% <HS: 21% >HS: 13% Employment: Employed: 21% Unemployed: 31% Retired: 35% Disabled: 12% Accounted for ability and comorbidities as reasons for ineligibility and non-enrollment Kwak et al. 2023 Of CCT enrollees: M: 63.7 Of non-enrollees: M: 68.4 Of CCT enrollees: NHW: 81.9% NHB: 7.2% H: 2.2% Oth: 8.8% Of non-enrollees: NHW: 78.5% NHB: 10.3% H: 2.9% Oth: 8.3% Of CCT enrollees: F: 53.8% Of non-enrollees: F: 47.8% NR Of CCT enrollees: Private insurance: 42.2% Distance traveled: 55.8 mi. Lowest SES sector: 6.6% Of non-enrollees: Private insurance: 26.2% Distance traveled: 27.2 mi. Lowest SES sector: 11.0% Of CCT enrollees: Charlson Deyo 3+: 2.9% Stage IV: 67.3% Of non-enrollees: Charlson Deyo 3+: 4.9% Stage IV: 40.2% Ladbury et al. 2022 Mean age difference (participants vs. SEER): −2.29 years EIR (participants vs. SEER) W: 1.06 B: 0.86 Asian: 0.51 AI/AN: 0.74 H: 0.89 H: 0.89 NR NR NR NR Langford et al. 2014 Of all patients: M: 62 65+: 43% % enrollment rate within racial/ethnic group: NHW: 20% NHB: 18% Hispanic: 22% Asian: 10% Other: 14% Proportion of all patients: NHW: 78% NHB: 13% Hispanic: 4% Asian: 4% Other: 1% F: 68% NR NR Addressed demographic characteristics as predictors of comorbidity Lythgoe, Savage, and Prasad 2021 NR Of race-reporting CCTs: W; 76.3% B: 2.9% Asian: 7.9% AI/AN: 0.5% Oth: 1.8% Unknown/missing: 10.5% NR NR NR NR Mishkin, Minasian, Kohn, Noone, and Temkin 2016 Of accruals: 75–84: 7.1% 85+: 0.4% Population estimates: 75–84: 18.5% 85+: 10.4%% Of accruals: White: 87.8% Black: 8.3% AI/AN: 0.9% API: 3.0% Hispanic: 5.9% Non-Hispanic: 94.1% Population estimates: White: 81.7% Black: 13.4% AI/AN: 0.6% API: 4.3% Hispanic: 14.7% Non-Hispanic: 85.3% Women NR Of accruals: Private (ovarian): 85.8% Medicaid: 5.5% Uninsured (cervical): 15.8% Population estimates: Private (ovarian): 76.1% Medicaid: 13.9% Uninsured (cervical): 8.9% Comment on intersection between age, race/ethnicity, SES, and ability Moloney and Shiely 2022 Addressed disproportionate impact of eligibility criteria (i.e., ECOG, complications) on older adult underrepresentation Addressed disproportionate impact of eligibility criteria (i.e., differences in organ functioning, comorbidities) on underrepresentation of Black and Hispanic participation Primary AFAB focus Addressed disproportionate impact of eligibility criteria (i.e., blood-borne virus and associated treatment) on LGBTQ + underrepresentation Addressed disproportionate impact of eligibility criteria (i.e., blood-borne virus and associated treatment, differences in organ functioning, comorbidities) on underrepresentation of individuals with lower SES Addressed disproportionate impact of eligibility criteria on individuals experiencing physical, cognitive, or psychiatric comorbidity; or on individuals experiencing treatment complications, metastases, or poorer functional status Murthy, Krumholz, and Gross 2004 Of accruals: 30–64: 68% 65–74: 23.7% 70+: 8.3% Population estimates: 30–64: 37.5% 65–74: 31.4% 75+: 31.2% CCT enrollees White: 85.6% Black: 9.2% API: 1.9% AI/AN: 0.3% Hispanic: 3.1% Population estimates: White: 83.1% Black: 10.9% API: 2% AI/AN: 0.2% Hispanic: 3.8% Of accruals: M: 32.1% F: 67.9% Population estimates: M: 51% F: 49% NR Report briefly on potential SES intersection with race/ethnicity in compromising participation) Briefly alluded to potential comorbidity intersection with age and race/ethnicity in compromising participation Newman et al. 2004 Of ACOSOG accruals: <65: 56% 65+: 44% Population estimates: <65: 42.8% 65+: 57.2% Of all accruals: AA: 10.5% Hispanic: <1% Population estimates: AA: 9.4% Hispanic: 3.4% Elaborate in discussion on interactions between race, ethnicity, and sex NR Elaborate in discussion on interactions between race, ethnicity, and SES Directly account for more advanced staging among minority patients at initial presentation; refers to eligibility limitations in discussion for older adults Noor et al. 2013 Of referrals: <67: 68.4% 67+: 31.6% Of comparators: <67: 44.9% 67+: 55.1% Of referrals: W: 74.2% NW: 13.7% Unspecified: 12.1% Of comparators: NR Of referrals: M: 54.7% F: 45.3% Of comparators: M: 51.9% F: 41.8% NR Of referrals: IMD 1: 15.8% IMD 2: 14.7% IMD 3: 20.7% IMD 4: 27% IMD 5: 21.9% Of comparators: IMD 1: 13% IMD 2: 14.2% IMD 3: 16.3% IMD 4: 29% IMD 5: 27.4% Allude briefly to intersection of age, SES, and ability via discussion of comorbidities Osann et al. 2011 Of accruals: NH M = 48.1 H M = 50.8 Of accruals: NH: 60% H: 40% 70% Hispanic enrollees: speak Spanish at home Women NR Of accruals: Education (College+): NH: 80% H: 25% Income ($25k+): NH: 83.3% H: 37.5% NR Owens-Walton et al. 2022 Briefly addresses intersecting role of age in underpinning CCT disparities Primary focus of representativeness (proportions NR, only relative representation) NR NR Briefly addresses intersecting role of SES in underpinning CCT disparities Briefly addresses intersecting role of comorbidities in underpinning CCT disparities Palmer et al. 2021 % participating in any cancer research 65+: 21.9% Exclusion: 75+ % participating in any cancer research African American: 47.6% Asian American: 16.7% Latino: 17.0% White: 26.2% AMAB only NR % participating in any cancer research HS or less: 18.7% Private insurance: 27.8% Low health literacy: 15.5% Health status <very good: 24.1% Comorbidity 2+: 29.2% Exclusion: no physical, cognitive, mental disability Pang et al. 2016 Of accruals: <70: 74.7% 70+: 25.3% Of accruals: White: 87.4% Black: 7.7% AI/AN: 1.0% API: 1.3% Hispanic: 1.7% Non-Hispanic: 92.8% Of accruals: M: 59.1% F: 40.1% NR Report partially on intersection between minorities, SES indicators, and access to clinic NR Patel et al. 2023 Of GI total: 65–74: 30% 75+: 18% Of HN total: 65–74: 19% 75+: 12% Of GI total: W: 87% B: 7% Asian: 2% Oth: 2% Missing/unk: 1% Of HN total: W: 92% B: 3% Asian: 3% Oth: 2% Missing/unk: 1% Of GI total: F: 40% Of HN total: F: 46% NR Of GI total: Not working: 19% Private insurance: 35% Of HN total: Not working: 14% Private insurance: 42% Of GI total: <5 CCI: 29% Stage IV: 27% Of HN total: <5 CCI: 63% Stage IV: 40% Patel et al. 2020 Of total sample: 50 and younger: 24% 51–65: 46% 65+: 30% Of total sample: White: 56% Black: 18% Latina: 18% Asian: 9% High acculturation: 85% Women NR Of total sample: Education HS or less: 29% Some college or technical: 32% College+: 39% Income <$40,000: 37% $40,00: 63% Insurance None: 1% Medicaid: 14% Medicare: 29% Other public: 1% Private: 55% Employment Unemployed: 61% Of total sample: Comorbidity 0: 71% 1+: 29% Patki et al. 2023 NR Of CCT participants: W: 82.6% B: 9.8% Asian: 5.7% (greatest underrepresentation) H: 7.9% AMAB only NR # reporting SES: 1 # reporting edu attainment: 3 Comment on lack of available data for reporting Briefly comment on intersection between race, ethnicity, SES, and ineligibility Perni, Moy, and Nipp 2021 Phase I: Median: 60 Phase II–III: Median: 61 Phase I: W: 93% B: 2% Asian: 6% Phase II–III: W: 93% B: 4% Asian: 3% Phase I: F: 57% Phase II–III: F: 44% NR Phase I: Median income <$50k: 14% Distance <50: 57% Private insurance: 67% Phase II–III: Median income <$50k: 16% Distance <50: 72% Private insurance: 69% Phase I: Metastatic: 79% Phase II–III: Metastatic: 59% Pittel et al. 2023 Of patient total: 65–74: 32.7% 75 + 26.8% % of group participating in CCTs: W: 7.2% B: 4.4% L: 4.2% Of total: W: 78.4% B: 13.7% L: 7.9% Of total patients: F: 57.3% NR NR Of total patients: ECOG 2+: 15.2% Pirl et al. 2018 Note reporting across studies Among race/ethnicity-reporting trials: W: 73.2% AA: 5.7% Asian: 9.9% Hispanic/Latine: 8.8% Note reporting across studies NR Note reported SES variables for each study NR Ramamoorthy et al. 2018 Among CCT participants: 2008–2013: 65+: 41% 2014–2017: 65+: 39% 2014–2017: 65+: 39% Among CCT participants: 2008–2013: W: 80% Asian: 12% B: 4% Hispanic: 4% Outside US: 74% 2014–2017: W: 71% Asian: 22% B: 1% Among CCT participants: 2008–2013: F: 44% 2014–2017: F: 52% NR NR NR Riaz et al. 2023 Of CCT participants: 65+: 71.1% Of CCT participants: B/AA: 10.8% AAPI: 1.5% W: 78.5% H: 4.4% AMAB only NR NR NR Reihl et al. 2022 Age-adjusted comparison rates (cohort age NR) Of CCT participants: W: 91.7% Asian: 1.5% B: 2.6% H: 1.7% Of CCT participants: F: 37.5% NR NR NR Saphner et al. 2021 CCT enrollees: 65+:38.3% CCT enrollees: W: 90.4% B: 6.6% NH Other: 1% H: 1.9% CCT enrollees: F: 62.2% NR CCT enrollees: Median income: 0.25/1.00 Below PL: 6.3% Owner values: 0.18/1.00 Unemployed: 2.8% College: 27.2% <HS: 4.2% Crowding: 0 NR Sawaf et al. 2023 Primarily addressed underrepresentation of older participants per trial Primarily addressed relative underrepresentation of Black and Hispanic patients per trial Described significant underreporting of Asian, NH/PI, and AI/AN races Primarily addressed underrepresentation of females per trial NR Address lack of CCT reporting SES, education, and rurality Address lack of CCT reporting on comorbidity scores, limited ECOG, BMI, and smoking reporting Scalici et al. 2015 Apply age-adjusted rates Of accruals: White: 83% Black: 8% Other: 9% NR NR NR NR Sedrak et al. 2022 Offered CCT: 50–69 y.o.: 74% 70+: 26% Enrolled in CCT: 50–69 y.o.: 68% 70+: 85% Enrolled in CCT: 50–69 y.o.: 68% 70+: 85% Ethnicity (%Hispanic) 50–69 y.o.: 6% 70+ y.o.: 3% F: 50–69 y.o.: 80% 70+ y.o.: 64% NR Income 50–69 y.o. <$50K: 34% 70+ y.o. <$50K: 47% Education 50–69 y.o. <HS: 6% 70+ y.o. <HS: 9% Rurality: 50–69 y.o. rural site: 21% 70+ y.o. rural site: 24% Education 50–69 y.o. <HS: 6% 70+ y.o. <HS: 9% Rurality: 50–69 y.o. rural site: 21% 70+ y.o. rural site: 24% # Comorbidities 50–69 y.o., 2+: 301% 70+ y.o., 2+: 51% Shinder et al. 2023 CCT participants: M: 56.4 Matched controls: M: 63.5 CCT participants: W: 90.3% B: 4.3% Oth: 3.7% Matched controls: W: 86.0% B: 10.3% Oth: 2.9% CCT participants: F: 29.1% Matched controls: F: 37.2% CCT participants: <$38k median income: 13.2% W/o HS edu 21%+: 11.2% Private insurance: 67.3% Matched controls: <$38k median income: 19.0% W/o HS edu 21%+: 17.9% Private insurance: 41.0% CCT participants: Distance: 61.1 mi Matched controls: Distance: 32.9 mi CCT participants: Stage IV: 20.7% Charlson-Deyo = 0: 81.6% Matched controls: Stage IV: 20.7% Charlson-Deyo = 0: 69.8% Steventon et al. 2024 NR % of CCT enrollees: AI/AN: 0.1% East Asian: 9.1% Asian (Oth, NOS): 0.5% B/AA: 3.7% Hispanic/Latino: 0.6% H/Unk/Unsp: 0.1% NH/PI: 0.1% Oth/unk: 6.1% Caucasian: 79.8% % of CCT enrollees by continent: North America: 80.1% (US: 78.1% total) Europe: 13.0% East Asia: 3.4% Middle East: 1.3% South American: 1.3% Australasia: 0.7% NR NR NR Briefly address potential contributing role of comorbidity Stewart, Bertoni, Staten, Levine, and Gross 2007 Of accruals: 21–44: 16.53% 45–54: 28.23% 55–64: 28.08% 65–74: 20.61% 75+: 6.55% Population estimates: 21–44: 4.91% 45–54: 11.82% 55–64: 20.84% 65–74: 30.78% 75+: 31.64% Of accruals: NHW: 86.57% Hispanic: 3.4% AA: 7.92% API: 1.86% AI/AN: 0.25% Population estimates: NHW: 82.15% Hispanic: 4.24% AA: 11.23% API: 2.16% AI/AN: 0.22% Of accruals: M: 16.05% F: 83.95% Population estimates: M: 48.97% F: 51.03% NR Comment on intersection between minority status and SES Comment on intersection between minority status and disqualifying cardiovascular comorbidities Talarico, Chen, and Pazdur 2004 Of participants: 65+: 36% 70+: 20% 75+: 9% Of SEER: 65+: 60% 70+: 46% 75+: 31% Reported “no imbalance by […] ethnicity” Reported “no imbalance by sex” NR NR NR Tharakan, Zhong, and Galsky 2021 NR % CCT enrollees overall: Black: 2.5% % CCT enrollees overall w/ location data: Black: 3.2% NR NR Briefly address role of national SES NR Unger et al. 2020 NR Pharmaceutical company: B: 2.9% SWOG: B: 9.0% SEER: B: 12.1% SWOG: NR NR NR NR Unger, Gralow, Albain, Ramsey, and Hershman 2016 <65: 71% 65+: 29% AA: 7% All other: 93% M: 16% F: 84% NR Income <$20,000: 22% $20,000-49,999: 30% $50,000+: 48% Education <2-year college: 55% 2-year college+: 45% Distance from clinic <13 miles: 28% 13+ mi: 72% NR Unger et al. 2013 % group enrolled onto CCT: 65+: 5.4% Of evaluable respondents: 65+: 22% Of evaluable respondents: 65+: 22% % group enrolled onto CCT: White/other: 9.0% AA: 11.1% Of evaluable respondents: W: 94.4% AA: 2.5% AAPI: 1.1% NA: 0.4% Other: 1.6% Of evaluable respondents: W: 94.4% AA: 2.5% AAPI: 1.1% NA: 0.4% Other: 1.6% % group enrolled onto CCT: M: 5.6% F: 11.1% Of evaluable respondents: F: 62% Of evaluable respondents: F: 62% NR % group enrolled onto CCT: <$50K: 7.6% $50K+: 10.0% <college: 7.9% college+: 9.6% Of evaluable respondents: <$50K: 32% <2-year. college degree: 34% Of evaluable respondents: <$50K: 32% <2-year college degree: 34% % group enrolled onto CCT: 0-1: 10.1% 2+: 7.5% Of evaluable respondents: 0-1: 59% 2+: 41% Of evaluable respondents: 0–1: 59% 2+: 41% VanderWalde et al. (2022) 2022 CCT enrollees: Median: 60 %65+: 39% NR NR NR NR Account for intersecting role of disease site and # trial modalities Wagar et al. 2022 Of enrollees: M: 60 Enrollment fraction by group: NHW: 1.519% NHB: 0.473% Hispanic: 0.338% AAPI: 2.379% AFAB NR NR NR Yonemori et al. 2010 Median (Japan trials) = 59 Median (US trials) = 55 Median (Japan pop) = 59 Proportion >65 in Japan accruals: 35% Proportion >65 in US accruals: 28% Japan USA (otherwise NR) NR NR Briefly report on effects of SES intersecting with older patient underrepresentation Report on effects of physical and psychological comorbidity impairing older patients disproportionately Yekedūz et al. 2021 NR Of CCT enrollees: Black: 2.1% Asian/Other: 19.4% Of population: Black: 9.8% Asian/Other: 8.1% Of CCT enrollees: F: 36.0% Of population: F: 49.6% NR NR Of CCT enrollees: HBV: 1.3% HCV: 0.8% HIV: NR Brain metastases: 1.6% ECOG <2: 82% Zafar et al. 2011 Median: 71 Caucasian: 87% AA: 12% Other: 1% M: 63% F: 37% NR NR PS 0: 13% 1: 59% 2: 16% 3: 11% 4: 1% Comorbidities CV: 66% Renal: 6% Hepatic: 1% Hematologic: 3% Endocrine: 30% Zhao et al. 2024 Total DMA: −8.15 NR NR NR Briefly mention intersecting role of financial strain Address intersecting role of comorbidities and disease site Zullig et al. 2016 Of accruals: M = 57.8 Of accruals: White: 2.37% enrollment out of new cases Minority: 2.21% enrollment out of new cases Of accruals: M: 1.46% enrollment out of new cases F: 3.25% enrollment out of new cases NR Of accruals: Q1 (fewest uninsured): 2.22%% enrollment out of new cases Q2: 2.43% enrollment out of new cases Q3: 2.49% enrollment out of new cases Q4 (most uninsured): 2.16% enrollment out of new cases NR Zuniga et al. 2020 NR Of accruals: W: 80% B: 17% Other: 4% Of incident cases: W: 80% B: 15% Other: 5% Men NR NR Report briefly on intersection between race and access to resources NR Note: Abbreviations included in this table are utilized as follows, listed alphabetically: AA = African American; AAPI = Asian American or Pacific Islander; ACOSOG = American College of Surgeons Oncology Group; AFAB = assigned female at birth; AI/AN = American Indian/Alaska Native; AMAB = assigned male at birth; AML = acute myeloid leukemia; ALL = acute lymphocytic leukemia; API = Asian or Pacific Islander; B = Black; CCC = comprehensive cancer center; CCT = cancer clinical trial; COPD = chronic obstructive pulmonary disease; CV = cardiovascular; DLBCL = diffuse large B-cell lymphoma; ECOG = Eastern Cooperative Oncology Group; edu = education; F = female; IQR = interquartile range; M = male; NCI = National Cancer Institute; NH = non-Hispanic; NIH = National Institutes of Health; NR = not reported; O = Other; PCa = prostate cancer; PL = poverty line; PS = performance status; SES = socioeconomic status; SGM = sexual and/or gender minority; W = White; WTP = willingness to participate; y.o. = years old.

Quality and bias assessment

The Mixed-Methods Appraisal Tool (MMAT) [ 29 ] was applied across studies to ensure uniform quality ratings across while affording flexibility appropriate to specific article type. The MMAT includes five sets of five-item criteria, with one set applied to each article reviewed contingent on its specific study design. Fulfillment of each of the five criteria for a given study design yields one point. As such, scores range from “0” to “5,” with higher ratings indicating stronger evidence quality. Case-control, cohort, cross-sectional, and meta-analytic studies were assessed using MMAT criteria directed toward nonintervention, descriptive analyses. While this iteration of the MMAT has not been applied to reviews specific to CCT representation, multiple versions of the MMAT have been utilized in recent reviews addressing cancer health disparities [ 30 – 32 ].

Results

Article selection

The combined search strategies yielded an initial 1,812 articles. Nine hundred ninety-three duplicates were removed, including articles from the 2021 search identified in the 2024 search. Eight hundred nineteen titles and abstracts were reviewed for relevance. Two hundred ninety-five articles underwent full-text screening, with 194 studies excluded as detailed in the PRISMA flow diagram (Figure 1 ). A resulting total of 101 articles were included in the review.

Figure 1. PRISMA flow diagram of selected articles.

Study information

Approximately 66% of included studies ( n = 67) primarily addressed tumor-directed, therapeutic trials, with 39.6% providing specific information on intervention types studied ( n = 40). Only 12.8% of studies ( n = 13) explicitly addressed trials with at least one supportive care, psychosocial, or behavioral component, with 5.0% of all studies ( n = 5) exclusively focused on such CCTs. Approximately 18.8% of studies provided minimal detail on trial type eligibility criteria ( n = 19). This information is summarized in Table 1 .

Case-control studies – that is, studies examining differences between participants and non-participants using patient data repositories – constituted 44.6% ( n = 45) of articles, with most utilizing population data to compare characteristics between CCT participants and corresponding oncologic populations. Nearly 29% of studies were conceptualized as cohort designs ( n = 29, i.e., using patient data to evaluate predictors of CCT enrollment over time), and 7.5% ( n = 7) were cross-sectional studies. Twenty-one studies were meta-analyses of aggregate demographic, socioeconomic, or medical characteristics across published trials (20.8%). Where classification according to these descriptions was ambiguous, our authors relied on self-identification of study design by the cited authors. This information is detailed in Table 2 .

Approximately 81% ( n = 82) of studies included race and/or ethnicity as a primary focus. In comparison, 54.4% ( n = 55) addressed age, 35.6% ( n = 36) addressed at least one socioeconomic indicator, 30.7% addressed sex or gender ( n = 31), and 26.7% ( n = 27) addressed at least one indicator of disability as CCT inequity targets. Only one eligible study addressed SGM status (0.99%) even following several modifications of advanced search strategies (Supplementary Table 1 ). The availability of social, economic, and medical characteristics across studies is detailed in Table 3 .

Quality assessment

Across all 101 studies, the quality mean MMAT score calculated was 4.59, with a median of 5. Score distribution was as follows: 5: 65.3% ( n = 66), 4: 28.7% ( n = 29), 3: 5.9% ( n = 6), 2: 0.0% ( n = 0), 1: 0.0% ( n = 0). Quality ratings are summarized in Table 1 .

Synthesis of findings

Race and ethnicity

Extant literature reflects robust evidence of CCT underrepresentation among patients of color, with mixed findings on representativeness across specific racial and ethnic minority groups. Early studies reflect lower enrollment among patients of color across multiple diagnostic sites, including in therapeutic lung, breast, colorectal, lymphoma, leukemia, and reproductive system CCTs [ 33 ], with some revealing decreased participation among patients of color across time (e.g., Baquet: 8.9% annual decrease among Black patients) [ 34 ]. Similar early trends are documented in surgical breast, colorectal, and thoracic CCTs [ 35 ]. Across the 50 largest National Cancer Institute (NCI) CCTs from 1996 to 2002, Black, Hispanic, and Asian American or Pacific Islander (AAPI) patients were all less likely to enroll in lung and colorectal CCTs, with Black and Hispanic women also less likely to enroll in breast trials [ 36 ]. These data indicated the poorest representation among Hispanic patients overall, and lower prostate CCT enrollment – a disparity not observed among other minority groups. This case-control study also showed a proportional decline in CCT enrollment among patients of color despite increased overall CCT participation from 1998 to 2002 [ 36 ]. While other evidence supports attenuation of some of these inequities with clinical cooperative group efforts (e.g., Newman: % Black CCT participants vs. cancer population: 10.5% and 9.4%) [ 37 ], early research consistently reflects national CCT underrepresentation among patients of color across various cancers.

Studies from the following decade demonstrate continued CCT underrepresentation among patients of color, adjusting for other relevant characteristics [ 38 , 39 ]. Longitudinal data emphasize stagnant therapeutic lung CCT enrollment among Black, Hispanic, and AAPI patients from 1990 to 2012, even with NCI cooperative group support [ 40 ]. Similar studies indicate worsening representation of Black women in gynecologic CCTs up to 2013, demonstrating 4.5–15 times lower enrollment than expected [ 41 ]. A meta-analysis from this period suggests still poorer trends, reporting 6.5 and 18.5 times lower enrollment than expected for Black women in cervical and ovarian trials, respectively, with representation worse from 2015 to 2018 compared to the late 1990s [ 4 ]. Other studies corroborate underrepresentation among patients of color in prostate, breast, colorectal, pancreatic gastric, hematologic, myelodysplastic, and varied sample CCTs at the catchment area level [ 42 , 43 ], in multi-site and multi-trial pharmacologic studies [ 44 , 45 ], Food and Drug Administration (FDA) CCTs with pharmaceutical sponsors [ 46 ], and in NIH CCTs from 1999 to 2019 [ 5 ]. Meta-analytic studies corroborate persistence of these inequities, reflecting poorest representation among Black and Hispanic patients in various therapeutic breast, colorectal, lung, prostate, pancreatic, renal, melanoma, and multiple myeloma CCTs, with such data collectively spanning 1981 to 2017 (e.g., Guerrero et al.: Not Reported, White, Black, and Hispanic CCT enrollment fractions [EF], respectively: 66.95%, 25.94%, 1.08%, 0.16%).[ 47 , 48 ]. Other national gynecologic CCT data not only accentuate Black and Hispanic underrepresentation but also larger disproportionate effects on Hispanic women with uterine and cervical cancers [ 49 ]. State-level studies reveal similar trends, with women of color less likely to enroll in early-stage breast radiotherapy CCTs overall, with Hispanic, then AAPI, then Black women, respectively, showing the lowest representation [ 50 ]. However, other findings during this period indicate the highest relative underrepresentation among AAPI, then Hispanic, then Black patients across breast, prostate, colorectal, and lung CCTs in national databases [ 6 ].

A few studies prior to 2021 suggest minimal inequities in CCT representation among patients of color with certain diagnoses, locations, and trial types. One national study reports no racial or ethnic differences in opportunities to participate in breast CCTs from 2013 to 2014 [ 51 ], with similar findings regarding prostate CCTs in earlier years [ 33 , 35 ]. A case-control analysis of FDA-approved therapies for breast, lung, colorectal, and prostate cancers showed persisting underrepresentation among patients of color relative to non-Hispanic White patients, though with recent improvements (% participants of color, 2008–2013: 20%; 2014–2017: 29%) [ 45 ]. Other evidence emphasizes representative accrual to surgical breast, thoracic, and sarcoma CCTs among Black and Hispanic patients [ 52 ], as is observed in NCI Community Cancer Centers Program CCTs overall [ 53 ]. Some findings during this period suggest equitable representation among patients of color in therapeutic lung CCTs, despite participation inequities in five other diagnostic sites [ 5 ]. Nonetheless, nonsurgical breast CCTs reliably demonstrate worsening representation among patients of color despite progress in other cancers (e.g., Zullig: 1996: < 1% vs. 2009: 3.5% enrollment difference between White and minority women, p < .001) [ 54 ]. Other studies reporting nonsignificant participation differences in some areas emphasize persisting trends toward underrepresentation among patients of color where typically observed [ 33 ].

Studies published within the past three years corroborate the intractability of CCT underrepresentation among patients of color while providing further nuance surrounding these inequities. State and national cohort, case-control, and meta-analytic studies of overall CCT representation evidence participation inequities that disproportionately impact Black [ 55 – 59 ] and/or Hispanic [ 47 , 48 , 56 , 57 , 59 , 60 ] patients in phase I [ 57 ], II [ 61 ], and III [ 59 ]; radiation [ 56 , 61 ]; drug [ 55 , 58 , 59 ]; brachytherapy [ 62 ]; and general CCTs [ 48 , 60 ] utilizing updated datasets and study repositories (e.g., Bero: Black proton participants vs. population 6.0% vs. 12.7%; Choradia: Hispanic participants vs. population: 7.1% vs. 13%; ). While some studies note mild representative improvement among Black [ 60 , 63 ] and Hispanic patients (e.g., Saphner: no significant inequities in White, Black, and Hispanic accrual: 90.4%, 6.6%, 1.9%; p = .078) [ 63 ], others demonstrate worsened representation in common cancers over time (e.g., 2009 vs. 2011–2015) [ 47 ]. Other case-control and meta-analyses emphasize underrepresentation among AAPI, Native Hawaiian, and American Indian/Alaska Native patients, in recent, CCTs for various prevalent cancers [ 48 , 56 , 64 ]. Still other findings evidence minimal underrepresentation among patients of color [ 63 ] and demonstrate even higher CCT participation among Asian patients, though such results have been primarily limited to singular institutions diagnostic sites, or trial types (e.g., Wagar: polymerase inhibitor CCT EF: White: 1.5%, Black: 0.47%, Hispanic: 0.33%, AAPI: 2.38%) [ 47 , 57 , 59 , 63 ].

Contemporary, cancer-specific studies reveal the importance of tumor site in dictating such inequities. Recent cohort, case-control, and meta-analytic studies of the most prevalent cancers continue to demonstrate underrepresentation among Black [ 62 , 65 – 72 ], Hispanic [ 62 , 65 – 70 , 72 ], Asian [ 62 , 72 , 73 ], and American Indian and Alaskan Native [ 62 , 67 , 69 ] individuals in breast [ 62 , 66 – 68 , 71 , 74 ], lung [ 65 , 67 – 71 ], and prostate CCTs (e.g., Ajewole: FDA oral chemotherapy CCT enrollment composition, 2009–2019: White: 71.5%, Black: 2.5%, Hispanic: 2.3%; Ladbury.: brachytherapy CCTs, enrollment incident disparity: Asian: −2.65%) [ 62 , 65 , 67 , 71 , 72 , 75 – 77 ]. Similar patterns are observed in understudied cancers, with CCT underrepresentation among Black [ 68 , 72 , 78 – 87 ], Hispanic [ 68 , 72 , 78 – 80 , 82 , 83 , 86 ], and Asian [ 72 , 80 , 86 ] patients with gastrointestinal [ 65 , 67 , 68 , 73 , 88 ], hepato-biliary [ 78 , 79 ], pancreatic [ 68 , 78 , 89 , 90 ], gynecologic [ 62 , 80 , 91 ], HPV-associated oropharyngeal [ 92 ], renal and urologic [ 72 , 87 , 93 ], hematologic [ 68 , 81 – 85 ], and neurologic [ 86 ] malignancies. Some evidence suggests potential mitigation of such inequities for certain cancers in recent years [ 65 , 80 , 86 , 94 – 97 ], particularly among Asian individuals (e.g., Javier-DesLoges: breast, colorectal, lung, and prostate participation odds ratios [OR], 2000–2004 vs. 2015–2019: Black: 2.19, 1.15, 1.54, 1.14; Hispanic: 3.32, 2.46, 2.21, 1.70; Asian: 1.94, 2.48, 3.88, 1.64) [ 47 , 65 , 67 , 85 ]. Nonetheless, such findings are primarily limited to studies with strong infrastructural support or smaller, singular institutional studies, while other contemporary studies reveal stagnation or worsened disparities over time (e.g., Owens-Walton: unchanging representation quotients from 2000 to 2017) [ 72 , 74 ].

Limited data reflect mixed findings regarding representation among patients of color in psychosocial CCTs. Some such evidence suggests minimal enrollment inequities between non-Hispanic and Hispanic women; however, even these data reflect higher attrition risk for Hispanic and immigrant women [ 98 ]. An institutional study of all cancers identified no racial/ethnic participation inequities among patients who were eligible for two pain and symptom-focused CCTs; however, patients of color were more likely to be ineligible [ 99 ]. Recent analyses suggest that psychosocial CCT representation among patients of color may be particularly contingent on intervention type, target population, and funding. For example, national evidence indicates Black underrepresentation in prostate exercise, advanced disease, and nongovernmental CCTs; adequate representation in dietary and multi-component trials; and disproportionately higher participation in pelvic floor muscle training, localized disease, and government-funded trials relative to their non-Black counterparts [ 100 ]. While observing poor representation among patients of color overall, a meta-analysis of integrated palliative CCTs suggests mitigated underrepresentation among Black patients compared to therapeutic CCTs (EF: 5.7% vs. 3.0%) [ 101 ], with similar, state-level results observed among Black men in behavioral CCTs [ 94 ]. Analyses of two psychosocial CCTs among women with gynecologic, gastrointestinal, and thoracic cancers demonstrate parallel trends, with even higher enrollment among Hispanic patients [ 102 ]. Nonetheless, other evidence investigating breast, lung, prostate, and colorectal CCTs reveals trends toward poorer representation among Black patients in supportive care trials compared to tumor-directed studies [ 6 ].

Age

Strong evidence demonstrates CCT underrepresentation among older adults across time. Early such inequities are observed in NCI Cooperative Group trials in prevalent cancers, with patients 65 to 74 and patients older than 75 years old, respectively, exhibiting progressively lower accrual to nonsurgical, therapeutic trials compared to younger patients [ 36 ]. Such findings are replicated in later general CCT samples [ 13 , 34 ], surgical CCTs [ 35 ], and NCI, state-specific data further classifying older age subgroups [ 33 , 34 ]. Early large studies corroborate these trends across cancer types and within drug-specific trials, with underrepresentation among older adults relative to their incident populations[ 45 , 103 – 105 ] and lower likelihood of CCT enrollment with age [ 53 ], with progressively greater underrepresentation (e.g., Talarico: participants vs. population, respectively: 65+: 25% vs. 60%; 75+: 4% vs. 31%) [ 105 ].

Contemporary literature corroborates these findings, reflecting continued CCT underrepresentation among older adults over time. Recent institutional, state, and national cohort, case-control, and meta-analytic studies reveal persisting underrepresentation among older adults in surgical [ 39 ], drug [ 42 , 66 , 106 ], brachytherapy [ 62 ], and other trial types [ 65 , 94 , 51 ]; phase I [ 57 ], II [ 107 ], and III[ 108 – 110 ] trials; and multimodal [ 107 ] CCTs in general (e.g., Baldini: CCT referral vs. population 70 +: 17.7% vs. 50%) [ 42 , 57 , 58 , 63 , 106 , 107 , 111 , 112 ]. Such findings are replicated in specific cancers, including breast [ 42 , 65 , 66 , 39 , 108 , 113 ], gynecologic [ 49 , 51 ], lung [ 65 , 96 , 108 ], prostate [ 65 , 76 , 94 , 108 ], pancreatic [ 89 , 90 ], hepatic [ 79 ], gastroesophageal [ 114 ], gastrointestinal [ 42 , 65 , 73 , 108 , 115 ], renal [ 87 ], skin [ 109 ], head and neck [ 116 ], other solid organ [ 5 , 107 ], and hematologic cancers [ 5 , 110 , 117 ], with further evidence of greater inequities among the oldest groups [ 115 ].

Nonetheless, other recent studies report no age differences in CCT enrollment, especially controlling for relevant covariates (e.g., Dudipala: OR: 1.023) [ 44 , 50 , 92 , 97 , 118 , 119 ]. However, these findings have primarily been exclusive to one institution, diagnosis, or state. Further, evidence of more equitable age representation overall is qualified in persistent inequities relative to the incident population for that specific cancer[ 40 ], or among patients initially referred to [ 40 ], eligible for [ 102 , 113 ], or discussed for such trials [ 97 , 112 ]. Furthermore, other longitudinal and population-based studies demonstrate stagnated or worsened age inequities in CCT participation over time, particularly among the oldest patients (e.g., Zhao et al. median age difference [DMA] between participant and incident disease median age: −8.15; US DMA before 2017 vs. after 2017: −5.90, −8.00) [ 49 , 108 , 111 ].

Socioeconomic status (SES)

Early national case-control analyses reflect breast CCT underrepresentation among low-SES patients by multiple indicators, including area poverty, unemployment, income, education, and individual government insurance [ 120 ]. Other site-specific studies document similar findings in various cancers, with lower CCT participation associated with higher material deprivation and lower social class (e.g., Mohd Noor.: Index of Multiple Deprivation [IMD] = 5 enrollment OR: 0.53, relative to least deprived IMD = 1) [ 34 , 119 ]. Another national, cross-sectional study revealed strongly prohibitive effects of low income on breast, colorectal, prostate, and lung CCT participation, controlling for other variables (< $50,000 income vs. $50,000+: OR: 0.73) [ 13 ], with progressively larger disparities among patients with the lowest incomes [ 13 , 118 ]. State analyses extend similar findings to area income in breast, genitourinary, gastrointestinal, and myelodysplastic CCT enrollment (e.g., Brierley et al.: average median income, participants vs. non-participants: $68,896 vs. $61,241) [ 43 , 121 ]. Other earlier studies reveal how unemployment, lower educational attainment [ 13 , 122 ], and governmental insurance [ 42 , 49 ] predict CCT underrepresentation in breast and other common cancers.

Contemporary studies within the past three years have increasingly focused on and further substantiated CCT underrepresentation among lower SES patients. Multilevel cohort, case-control, and meta-analytic studies evidence the effects of lower area income (e.g., Hue: stage IV participants vs. non-participants < $40,227: 11.4% vs. 19.1%) [ 63 , 87 , 89 , 112 , 123 ], education (e.g., Eskander: CCT participation, higher vs. lower high school attainment OR: 2.0) [ 73 , 78 , 80 , 87 , 89 , 90 , 94 , 112 ], insurance (e.g., Shinder: CCT participation, uninsured, Medicaid, or Medicare vs. private insurance ORs, respectively: 0.57, 0.43, 0.59) [ 70 , 73 , 78 , 87 , 90 , 96 ], or overall SES (e.g., Kwak: CCT participation, lowest [ 1 ] vs. median [ 4 ] SES group OR: 0.60) [ 63 , 70 , 82 , 96 ] on breast [ 66 ], prostate [ 77 , 94 ], lung,[ 70 , 96 ] gastrointestinal [ 73 ], pancreatic [ 78 , 89 , 90 ], hepatic [ 73 , 78 ], gynecologic [ 80 ], renal [ 87 ], brain [ 123 ], hematologic [ 83 ], and mixed CCT underrepresentation [ 57 ]. Other meta-analyses emphasize how limited SES reporting in CCTs significantly compromises research regarding its effects on representation [ 77 , 88 ].

Nonetheless, other studies present contrasting findings. data have shown higher breast CCT enrollment among Medicaid-eligible and lower-education patients [ 38 ]. Other studies have reflected higher surgical breast CCT participation with higher area education, but lower income [ 39 ], with similar income findings in gynecologic trials [ 80 ]. Some contemporary studies have observed no SES impact on CCT enrollment (e.g., Perni et al. participation OR, $100,000 median income vs. < $50,000: 1.28) [ 57 ] or attenuated effects in multivariate models [ 63 , 87 , 89 ], though these studies only examined socioeconomic factors as covariates. While the most equivocal evidence appears in the relationship between income and CCT participation, recent authors conceptualize such findings in reliance on area, rather than patient, indicators due to systemic data deficiencies [ 80 ]. Despite the nuances observed in these mixed findings, the literature provides growing evidence of socioeconomic CCT inequities by various indicators.

Sex

Mixed literature on sex-related CCT inequities suggests contingency of representation on cancer and trial type. For example, early national data suggest higher therapeutic CCT enrollment among men with colorectal and lung cancers (participation, men vs. women OR: colorectal, lung, respectively: 1.30, 1.23) [ 36 ] with similar results replicated in center-specific analyses [ 124 ]. However, other early evidence regarding surgical CCTs reflects the reversal of this trend, with women five times more likely than men to enroll overall in a combined, national breast, colorectal, lung, and prostate sample [ 35 ]. Other data provide further insight into contrasting results, suggesting greater overall CCT participation among men, though lower enrollment compared to women when examining sex-specific cancers [ 34 ].

More recent studies have observed more equitable CCT representativeness across sexes. National cohort and meta-analytic studies addressing various cancers, including sex-specific [ 44 ] and rare diagnoses [ 117 ], reflect minimal sex differences in representation (e.g., Costa: observed-expected ratio, % male participants: 1.03). Similar evidence has emerged in psychosocial CCTs, revealing no sex differences in participation (e.g., Huang: % eligible enrolled in symptom CCT, within each sex: women: 75%, men: 78%) [ 99 ]. Longitudinal analyses reveal improvement in lung CCT representation over time among women younger than 65 years old (overall enrollment disparity difference between sexes reduced 0.07 to 0.03, 1994–2012) [ 40 ], as is consistent with equitable sex representation among younger patients in earlier lung and other CCTs [ 36 ]. Some state-specific evidence reflects even higher therapeutic lung, colorectal, and sex-specific CCT enrollment among women relative to men [ 54 ], as with the aforementioned surgical CCT findings [ 35 ]. Nonetheless, women’s underrepresentation persists in certain rarer cancers, such as myelodysplastic syndrome [ 43 ] or HPV-associated oropharyngeal CCTs (e.g., Gordis: % total female enrollees: 11.8%) [ 92 ]. Conversely, other data reflect disadvantages for men for certain CCT types across cancers, such as eligibility for chemoradiation trials [ 125 ] and participation in sex-related CCTs [ 34 ]. FDA approvals between 2008 and 2017 similarly demonstrate attenuated inequities when including sex-related CCTs, while simultaneously revealing worsened women’s representation over time when exclusively examining trials for cancers affecting all sexes (% women: 2008 to 2013: 47%, 2014 to 2017: 37%) [ 45 ].

Studies within the past three years continue to reveal minimal sex-related CCT inequities. Multiple institutional, state, and national cohort and case-control studies suggest equitable CCT participation across sexes in colorectal [ 68 ], lung [ 68 – 70 ], pancreatic [ 68 , 89 ], neurologic [ 123 ], hematologic [ 68 , 83 , 85 ], and mixed samples [ 63 ], with some analyses suggesting higher representation among women (e.g., Saphner: participation OR, men vs. women: 0.70) [ 63 , 70 ]. However, some of these findings are restricted to specific institutions, with their results challenged by more nationally representative analyses suggesting persistent underrepresentation among women in colorectal [ 65 , 88 ], lung [ 65 ], neurologic [ 86 ], and hematologic CCTs [ 84 ]. Additional studies document lower participation among women in hepatic [ 79 ], head and neck [ 95 ], and renal CCTs [ 87 ], in addition to women’s underrepresentation in overall therapeutic [ 60 ], radiation [ 56 ], phase II and III [ 57 ], non-sex- [ 63 ], and sex-specific diagnostic CCTs [ 60 ]. Though recent evidence of improved representation among women is qualified by these contrasting findings, contemporary results suggest partial mitigation of such inequities over time for certain diagnostic sites (e.g., Javier-DesLoges: women’s participation OR, 2015–2019 vs. 2000–2014: 1.38, with remaining inequities relative to men [OR: 0.89]) [ 65 , 86 ].

Ability, staging, and functional status

Until the past three years, few studies had examined indicators of ability status as direct contributors to CCT participation, typically focusing on staging (i.e., measured by tumor size, lymph node presence, and/or metastases) [ 126 ], comorbidity, and more rarely, performance status ratings. Earlier findings evidence higher participation in breast [ 50 , 51 , 113 , 127 ], colorectal, lung, prostate [ 13 ], and multiple myeloma CCTs [ 117 ] among patients with lower staging or fewer comorbidities (e.g., Unger: participation OR, comorbidity score: 0.81), though primarily examine such indicators as covariates. Some institutional analyses characterize exclusionary comorbidities as restrictive to CCT participation across multiple cancers [ 122 ], while other data document positive relationships between symptom risk and therapeutic CCT enrollment in rarer cancers (e.g., Brierley: participation OR, high vs. very low risk: 1.88) [ 43 ]. Still, other investigators report no association between disease characteristics, comorbidities, and CCT participation [ 33 ], though these early studies still conceptualize such ability proxies as covariates, rather than key predictors.

While evidence remains scarce compared to other marginalizing indicators, contemporary studies have increasingly documented relationships among comorbidity, functional impairment, and CCT participation. National cohort, case-control, and meta-analytic studies reveal the potentially restrictive impact of comorbidity burden or associated lower performance status on pancreatic,[ 78 , 89 , 90 ], breast [ 66 ], lung [ 128 ], hepatic [ 78 ], gynecologic [ 80 ], other gastrointestinal and genitourinary [ 128 ], renal [ 87 ], head and neck [ 116 ], solid organ [ 129 ], and overall CCT representativeness (e.g., Green: % comorbidity score = 0, participants vs. non-participants: 69.2% vs. 51.6%) [ 58 , 112 ]. Other analyses, while not directly centering ability proxies as enrollment predictors, evidence the covarying impact of performance status on CCT participation (e.g., Bruno: lung participation OR, Eastern Cooperative Oncology Group [ECOG] score, 2 vs. 0: 0.27) [ 130 ]. Still other recent results evidence positive relationships between comorbidity burden and CCT participation, though these findings are exclusive to one state and disease site [ 95 ].

Intersectionality in CCT participation inequities

The above-summarized data provide robust evidence of persistent CCT underrepresentation among patients of color and older adults, with mixed evidence of changing representativeness over time across diagnostic sites and trial types. Recent evidence reveals similar relationships between SES and CCT participation, demonstrating how lower education, inadequate insurance, and to a smaller extent, lower income, may further stifle CCT representativeness. While sex disparities have negatively impacted CCT participation depending upon cancer type, some contemporary studies evidence more equitable CCT representation in common cancers. While the singular impacts of such factors quantitatively vary, the interactivity among these social, economic, and medical marginalizing indicators further complexifies CCT representativeness.

This review characterizes the nexus among race, ethnicity, and SES as one of the most intricate intersections in determining CCT representation. Early breast CCTs have revealed diminishing underrepresentation among Black patients after considering area poverty, unemployment, and Medicaid coverage (participation OR, Black vs. White: 0.99) [ 120 ]. Later population data corroborate such findings, illustrating partial attenuation of Black and Hispanic underrepresentation in surgical breast CCTs when accounting for income and education [ 39 ], as well as insurance [ 131 ]. Institutional analyses of multiple cancers have demonstrated resolution in CCT underrepresentation among patients of color after accounting for age, sex, and deprivation index [ 119 ]. However, other evidence reveals underrepresentation among higher income and privately insured Black and Hispanic women compared to their less affluent counterparts in gynecologic [ 49 , 98 ] and breast CCTs (e.g., Fayanju: participation OR, Black and Hispanic, respectively, median income $63,000+ vs. < $38,000: 0.45, 0.19) [ 39 ]. These findings constitute a reversal of typically observed relationships, wherein racial, ethnic, and socioeconomic marginalization multiplicatively serve to restrict CCT participation with concurrent marginalization, rather than poorer participation among higher SES women of color. A meta-analysis of FDA approvals, regardless of SES, emphasizes the intersection among sex and minoritized identity, with the greatest underrepresentation observed among women of color in prevalent cancers (i.e., % Black participants breast sample: 2%) [ 45 ].

Studies within the last three years have increased explicit efforts to explore the interactive influences of racial, ethnic, and socioeconomic marginalizing indicators on CCT participation, while similarly indicating nuanced results across diagnostic sites. Multilevel cohort, case-control, and meta-analytic studies demonstrate the simultaneous impact of minoritized race/ethnicity, lower area SES, and inadequate insurance coverage in limiting breast [ 66 ], gynecologic [ 80 ], pancreatic [ 90 ], and renal [ 87 ] CCT participation (e.g., Khadraoui: participation ORs, racial/ethnic minority vs. White: Black: 0.70, Hispanic: 0.53, Asian: 0.44, Other: 0.48; education, 15.3%+ vs. < 5.0% without high school education: 0.41). Similar studies demonstrate partial contingency of hematologic CCT underrepresentation among people of color on lower area income or insurance coverage [ 82 ]. Still, other recent studies corroborate persistent CCT inequities that disproportionately affect among women of color regardless of income, in gastrointestinal trials [ 73 ], as is consistent with earlier breast and gynecologic CCTs [ 49 , 39 ].

Studies investigating relationships among race, ethnicity, and SES in determining CCT representation have increasingly revealed potential contributions of disease characteristics, comorbidity burden, and performance status. For instance, early analyses demonstrate how controlling for advanced disease diminishes otherwise observed racial CCT inequities [ 37 , 50 ]. Similar interactive relationships have been observed in early case-control studies regarding lung CCTs, interpreting underrepresentation among Black and other patients of color within the intersections among race, SES, insurance, comorbidity, and performance status [ 124 ]. Other national data corroborate higher comorbidity among Black patients considered for CCTs (medical comorbidity presence, OR: 1.53) [ 53 ]. More recent analyses directly explore how ability indicators color the intersectional effects of race, ethnicity, and SES on CCT representation [ 66 , 80 , 87 , 94 , 129 ]. While some such studies reveal how higher staging and comorbidity may further limit CCT participation among minoritized or lower SES patients (e.g., Yekeduz: % Black participants vs. population: 2.1% vs. 9.8%, with 82% total sample with ECOG 0–1) [ 66 , 72 , 80 , 87 , 129 ], others offer opposing evidence among certain underserved populations. Specifically, some studies indicate increased CCT participation among patients of color with higher comorbidity burden and staging, such as Hispanic men with prostate cancer [ 94 ]. Still others indirectly examine complex, intersectional influences of comorbidity, illness characteristics, and ability on CCT representativeness, suggesting poorer overall CCT participation due to the COVID-19 pandemic, though with unexpected impacts on participation inequities (e.g., Choradia et al.: participation ORs, 2005–2020, each vs. White patients: Hispanic: 0.52, American Indian: 0.41, AAPI: 0.81; peak participation among these underserved in 2020, despite lowest year of enrollment across population) [ 60 , 68 ].

Such patterns are further influenced by age and sex, especially among older adults of color with an increased comorbidity burden. Early analyses demonstrate how older age compromises breast, colorectal, thoracic, and prostate CCT participation across racial and ethnic groups, though drives underrepresentation otherwise unobserved in younger patients among women of color [ 36 ]. Other investigators demonstrate how older age heightens gynecologic CCT attrition risk for Hispanic, but not for non-Hispanic, women [ 98 ]. Recent national cohort, case-control, and meta-analytic studies strengthen evidence of simultaneous underrepresentation regarding older age, comorbidity, performance status, and other marginalizing factors underpinning CCT underrepresentation (e.g., Kaanders: % participants with World Health Organization [WHO] 0–1 or Karnofsky performance score 90–100: 70%; median age, participant vs. population: 57, 64 [ 58 , 107 , 109 , 112 , 116 ], with some evidence emphasizing how trial characteristics themselves may limit participation among older adults with higher disease burden [ 107 ].

Regarding intersecting sex influences, some early state studies indicate elevated racial disparities among men relative to women in therapeutic trials for common cancers [ 34 , 54 ], with recent studies similarly accentuating how cancer sex-specificity may underpin racial and ethnic representativeness in radiation CCTs (i.e., Black underrepresentation observed in all CCT types except sex-specific female [13.1% sample] and male [18.4% sample] US trials) [ 56 ]. While quantitatively unexamined to date, contemporary studies have begun to comment on how relationships among these marginalizing factors may be furthermore impacted by sexual minoritization, through its influence on preexisting health and CCT eligibility [ 66 ]. Overall, relationships among social, economic, and medical marginalizing indicators in underpinning CCT inequities have gained increasing attention in recent years, with more investigators explicitly exploring the structural, intersectional context of such factors when interpreting their findings regarding CCT representativeness [ 72 , 39 ].

Discussion

This review sought to describe CCT participation inequities via multiple modes of social, economic, and medical marginalization, including race, ethnicity, age, sex, SGM identity, SES, and ability. Its findings contribute novel insights regarding the impact of such factors on CCT inequities, including strengthened evidence for national CCT underrepresentation among racial and ethnic minority groups and older adults across various cancers and trial types. To a lesser, albeit increasing extent, these results reveal compromised CCT participation among lower SES patients across various metrics, especially education and insurance; however, these findings are dependent on aggregate, rather than individual, SES indicators. This review further offers insights into the effects of ability status on CCT participation, with a growing focus on comorbidity burden in recent years.

These findings reflect minimal to modest evidence of improvement in representativeness across the past several decades. While exhibiting some progress in racial, ethnic, and sex representativeness in certain intervention types, CCT inequities are observed across most cancers and study designs in recent large-scale analyses. Studies focused on CCT representation among the underserved have more than doubled within the past three years, while accentuating a persisting absence of data investigating such inequities among SGM patients. Nonetheless, while bolstering evidence of intractable CCT inequities across various other marginalizing indicators and cancers, contemporary investigations have increasingly provided more nuanced insights into their complex interplay in determining CCT representativeness.

More important than enduring inequities observed in a singular examination of each marginalizing indicator, however, is the intersection among these social, economic, and medical characteristics and their effects on CCT inequities. These results demonstrate the partial underpinning of CCT underrepresentation among patients of color by parallel preexisting socioeconomic and health disparities. Further, the literature illustrates how the intersection among racial/ethnic minority status, SES, and other marginalizing indicators may interactively predispose individuals with cancer to more aggressive disease, higher comorbidity, or poorer performance status, thus compromising CCT participation among the underserved. These conditions are further influenced by the strong relationship between age and higher ineligibility risk due to similar preexisting health inequities, and their heightened impact on CCT representation in their intersectional context with other marginalizing indicators. Despite an increased focus on these relationships in recent CCT literature, few articles explicitly allude to their intersectional, structural nature, with most studies addressing multiple marginalizing indicators as potential confounding covariates at best.

This review is the first to conceptualize existing CCT inequities across several modes of social, economic, and medical marginalization through an intersectional perspective. These findings accentuate how numerous marginalizing indicators limit CCT representativeness with multiplicative implications, further preventing equitable participation among those with overlapping experiences of social, economic, and medical oppression. Further, this review is uniquely underpinned by a central recognition of social inequality, context, power, and justice using intersectionality as a theoretical scaffold for understanding public health [ 25 , 26 ].

Limitations

This review is limited in its absence of articles addressing CCT participation among SGM individuals, yielding only one study that transiently mentioned SGM identity as one factor affecting CCT participation while interpreting its results. While this may indicate limitations in the search strategies applied to this review, this absence of SGM studies persisted with extensive adjustments, thus likely reflecting large deficits in the literature itself. Another limitation is a lack of explicit investigation regarding the impacts of rurality on CCT participation – a crescent area of research important to understanding CCT representation through an intersectional perspective.

Other limitations consist in a low number of articles that specifically address (1) supportive care, psychosocial, behavioral, or quality of life interventions and (2) longitudinal retention in studies. Further, few included articles directly investigate relationships between social, economic, and medical marginalization through an explicitly intersectional perspective, primarily examining such interactive influences through reductive, additive models that merely control for covarying factors. These results are also qualified by the limitations in article quality evaluation. While the use of the MMAT for quality assessment accommodated the diversity of articles included, this flexibility inversely limits the standardization of ratings across various article types. Further, while intersectionality constitutes a necessary lens through which investigators must accurately view health inequities, optimal practices for quantification of such outcomes through this theoretical paradigm remain tenuous.

Implications and future directions

This review characterizes the current state of the literature quantifying CCT participation inequities that disproportionately impact the underserved in cancer care. Its description of such inequities reveals little ambiguity in CCT underrepresentation among certain marginalized groups, especially among older adults, racial/ethnic minorities, and by some indicators, patients originating in lower SES areas or with greater disability. This review thus constitutes a strong foundation to further investigate underpinning barriers that sustain these inequities and potential solutions to dismantle them. Its findings accentuate the necessity of future research focused on (1) mixed evidence regarding specific social, economic, and medical indicators in determining CCT participation, (2) the role of intersectionality and underlying mechanisms in explaining such inequities, and (3) persistently understudied marginalized populations in the investigation of CCT representation, especially patients who are SGMs, of lower SES or rural origin, or live with comorbid disabilities. Additional research is necessary to understand the generalizability of such findings to CCTs beyond those that are tumor-directed and longitudinal participation patterns.

This review accentuates the persistence of CCT participation inequities across various vectors of social, economic, and medical marginalization through an intersectional perspective across the past four decades. As such, these findings emphasize the urgency of identifying and dismantling barriers that sustain these inequities. Through such efforts, investigators and clinicians may strive toward the eradication of inequities in cancer outcomes and equitable benefits from advancements in cancer care among the underserved.

Supporting information

Hanvey et al. supplementary material

Hanvey et al. supplementary material

Acknowledgments

The authors thank Covidence – a web-based collaboration software platform that streamlines the production of systematic and other literature reviews – for facilitating article screening, organization, and data extraction of the review process.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/cts.2024.677 .

Author contributions

Dr Grace Ann Hanvey takes responsibility for the manuscript, including the conception and design of the work, data collection, conduct and interpretation of analyses, and drafting of the manuscript. Ms. Hannah Johnson served as the secondary rater for article quality assessment, thus making significant contributions to data analysis and interpretation. Drs. Gabriel Cartagena, Duane Dede, Kathryn Ross, and Janice Krieger contributed to the review and revision of the initial conception and design of the work. Dr Deidre Pereira served as the supervising and corresponding author of the work, thus providing foundational intellectual and infrastructural support for all aspects of publication including conception; data collection, analysis, and interpretation; and drafting the manuscript.

Funding statement

The authors have no financial support to report for the present work.

Competing interests

There are no conflicts of interest to report for the present manuscript.

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