Adequate assessment yields appropriate care-the role of geriatric assessment and management in older adults with cancer: a position paper from the ESMO/SIOG Cancer in the Elderly Working Group.

Introduction

Worldwide, there will be an estimated 28.4 million new cancer cases in 2040, representing a 47% increase compared to 2020. 1 In the next few decades, older adults will constitute a growing proportion of the new cancer cases. 2 , 3 Along with advances in cancer therapeutics that are more tolerable and improve outcomes, more older adults will receive and benefit from cancer-directed treatments. 4 , 5 Given the heterogeneous health status among older adults and their susceptibility to aging-related vulnerabilities, understanding their diversity and its implications becomes increasingly crucial for prognostication and guiding diagnostics, treatment decisions, and follow-up, as well as informing supportive care interventions. 6 Geriatric assessment and management (GAM) refers to the comprehensive evaluation of an individual’s health status with subsequent management plans focusing on both oncologic and non-oncologic interventions. Over the past decade, several large, randomized trials have investigated the effects of GAM on outcomes.

In 2019, the European Society for Medical Oncology (ESMO) and the International Society of Geriatric Oncology (SIOG) established the ESMO/SIOG Cancer in the Elderly Working Group. The aims are to improve the management of older patients with cancer, enhance education for oncology professionals on issues pertinent to this demographic, and raise awareness regarding their specific needs and management requirements. This position paper reflects the recommendations of the working group and summarizes the existing evidence with a focus on recent key trials, allowing us to propose several recommendations and future directions.

Geriatric assessment and management (GAM)

Geriatric assessment (GA) evaluates multiple domains that influence prognosis and treatment decisions in older adults. 1 , 7 The most common domains include, but are not limited to, functional status, comorbidities, cognitive function, psychological status, social functioning and support, nutritional status, and medications ( Table 1 ). Suggested tools used to assess these domains are highlighted. Assessing all domains is more important than using multiple tools within each domain, with the choice of tools depending on local resources and expertise. Completing a GA alone is not sufficient, as clinicians should utilize this data to inform management decisions [i.e. GAM or comprehensive geriatric assessment (CGA)]. The assessment can also guide referrals to health care professionals specific to the identified deficit. Additionally, a one-time assessment may overlook changes in the patient’s clinical status over time. For example, treatment regimens that include platinum or 5-flurouracil frequently cause nausea and loss of appetite, leading to impaired nutritional status. On the other hand, patients may have improvement in cancer symptoms because of treatments. Therefore, reassessment at intervals, upon progression or changes in health status, can facilitate dynamic decision making in cancer care for older adults, including treatment changes (e.g. dose intensification, reduction, dose delays) and supportive care interventions. Table 1 Geriatric assessment domains and tools Geriatric assessment domain Tools a Interventions for positive finding Functional status • Self-reported: ○ Activities of daily living ○ Instrumental activities of daily living ○ Falls • Objective tests: ○ Timed up and go test ○ Gait speed ○ Short physical performance battery 1. Mobility and health aids 2. Home safety equipment 3. Promote physical activity 4. Physical therapy and rehabilitation Comorbidity • Charlson Comorbidity Index • Cumulative Index Rating Scale-Geriatric • Adult Comorbidity Evaluation-27 1. Comorbidity management 2. Referral to a geriatrician or other specialists 3. Clarify goals of care Social functioning and support • Medical Outcomes Study survey • RAND-36 Healthcare Survey 1. Consult social work 2. Consult financial services Cognition • Blessed Orientation Memory Concentration test • Mini Cog • Mini Mental State Examination • Montreal Cognitive Assessment 1. Counseling 2. Assess inappropriate medications 3. Evaluate decisional capacity 4. Referral to geriatric neuropsychologist Psychological status • Distress Thermometer • Geriatric Depression Scale (several versions available) • Mental Health Inventory • Patient Health Questionnaire (several versions available) 1. Cognitive behavioral therapy 2. Non-pharmacological approaches (meditation) 3. Anti-depressants 4. Referral to a geriatric psychiatrist 5. Communicate with primary care team Nutrition • Weight loss • Body mass index • Mini Nutritional Assessment • Malnutrition Universal Screening Tool 1. Address factors contributing to malnutrition 2. Address chemotherapy-induced adverse effects like nausea/vomiting 3. Oral care 4. Supplemental nutrition 5. Refer to dietitian Polypharmacy • Beers Criteria • Medication Appropriateness Index • STOPP/START criteria 1. Medication reconciliation 2. Evaluate adherence 3. Evaluate drug interactions 4. Deprescribing 5. Home health for medication management START, Screening Tool to Alert to Right Treatment; STOPP, Screening Tool of Older Persons’ Prescriptions. a At a minimum, consider one tool from the domains of functional status (instrumental activities of daily living), cognition (Mini Cog or Blessed Orientation Memory Concentration), and psychological status (PHQ-2); assess weight loss, comorbidity, and medications from the medical records; and inquire about source of social support from the patient.

Evidence from randomized trials of GAM

In this section, we discuss and summarize results of selected randomized trials testing GAM for older adults with cancer ( Tables 2 and 3 ). Table 2 Study design and settings for pivotal CGA-guided trials Study Study acronym Country Study type Trial population Key inclusion criteria Model of care/involved teams Setting (academic versus community) Intervention arm Standard-of-care arm Mohile et al., 2020 8 COACH USA RCT (cluster-randomized), multisite Patients: n = 541; meanA = 76.6 years; Caregivers: n = 414; meanA = 66.5 years Age ≥70 years; advanced solid cancer or lymphoma and ≥1 GA impairment at baseline; 1 caregiver of patients’ choice (optional) Consultation Community centers Community oncology received GA and tailored recommendations for interventions GA was carried out without reporting to oncologist, exception: alerts for depression/cognitive impairment Mohile et al., 2021 6 GAP70+ USA RCT (cluster-randomized), multisite n = 718; meanA = 77.2 years Age ≥70 years; incurable solid cancer or lymphoma and ≥ 1 GA impairment at baseline Consultation Community centers Community oncology received GA and tailored recommendations for interventions GA was carried out without reporting to oncologist, exception: alerts for depression/cognitive impairment Li et al., 2021 24 GAIN USA RCT, single site n = 613; mdA = 71 years Age ≥65 years; solid cancer, new therapy line intended Consultation Academic CGA GA results sent to oncologist for consideration; alerts for depression/cognitive impairment send with urgency Soo et al., 2022 9 INTEGERATE Australia RCT, multisite n = 154; mdA = 75.5 years Age ≥70 years; solid cancer, or DLBCL; chemo-, immune-, or targeted therapy intended Integrated oncogeriatric care Academic CGA, geriatric follow-up No CGA, referral to geriatrician possible if requested by oncologist Puts et al., 2023 11 5C Canada RCT, multisite n = 340; meanA = 76 years Age ≥70 years; solid cancer, lymphoma, or myeloma; chemo-, immune-, or targeted therapy intended Co-management CGA, geriatric follow-up as needed No CGA Lund et al., 2021 12 GERICO Denmark RCT, single site n = 142; mdA = 75 years Age ≥70 years; first diagnosis of CRC stage II-IV; adjuvant or palliative chemotherapy intended; G8 score ≤14 Co-management Academic and community centers Pre-therapeutic CGA, regular geriatric follow-up as needed No CGA Paillaud et al., 2022 25 EGeSOR France RCT, multisite n = 475; mdA = 75.3 years Age ≥65 years; first diagnosis or late relapse of HN pre-treatment Co-management Academic + community centers Pre-therapeutic CGA, geriatric follow-up for 24 months Standard of care, no initial GA DuMontier et al., 2022 13 — USA RCT, single center n = 160 (IA: n = 100; SA: n = 60); meanA = 80.4 years Age ≥75 years, initial consultation for multiple myeloma, lymphoma, or leukemia; transplant-ineligible; (pre-) frail Consultation Academic Initial GA; geriatric consultation twice-weekly, geriatric interventions initiated GA initially carried out, results blinded to oncologist, no geriatric consultations or interventions Orum et al., 2021 26 — Denmark RCT, single center n = 301; mdA = 75 years Age ≥70 years, newly diagnosed solid cancer (LC, GI, HN), planned radiation or systemic cancer therapy Consultation Academic CGA at study initiation with recommendations for interventions, further follow-up, and adaptation of interventions by the geriatric team CGA at study initiation with recommendations for interventions without further follow-up or adaptation of interventions by the geriatric team Nipp et al., 2020 14 — USA Pilot RCT, single center n = 62; mdA = 72.3 years; LC: 43.55%; GI: 56.45% Age ≥65 years, incurable GI cancer or LC Co-management Academic Two in-person consultations with geriatrician, evaluation, and management of geriatric and palliative symptoms Usual care without geriatric consultations Nipp et al., 2022 27 — USA RCT, single center n = 160 ( n = 137 in PP analysis); mdA = 72 years Age ≥65 years; GI, planned cancer surgery Consultation Academic Preoperative geriatric consultation with CGA, one follow-up visit post-operative No CGA, standard care Nadaraja et al., 2020 28 — Denmark RCT, single center n = 96; mA (IA) = 73.9 years; mdA (SA) = 76.8 years Age ≥70 years; primary sites: GI, GU, GYN, or NSCLC; staring new line of systemic cancer therapy Consultation Academic Screening with G8; if G8 < 14, CGA was carried out and treatment intensity discussed with MDT based on GA results; interventions initiated Treatment as indicated, treatment decision based on the oncologist's clinical judgment Jeppesen et al., 2018 29 — Denmark Pilot RCT, single center n = 51; mdA = 72 years Localized NSCLC, intended for SBRT, no age restriction Consultation Academic SBRT +CGA SBRT − CGA Hempenius et al., 2016, 2013 30 , 31 LIFE Netherlands RCT, multicenter n = 260; meanA = 77.4 years Age ≥65 years; GFI <3; planned surgery for solid cancer Co-management Academic and community Preoperative assessment of risk for delirium by the geriatric team, ongoing geriatric co-management after surgery Usual care without geriatric co-management CGA, comprehensive geriatric assessment; CRC, colorectal cancer; DLBCL, diffuse large B-cell lymphoma; GA, geriatric assessment; GFI, Groningen Frailty Indicator; GI, gastrointestinal cancer; GU, genitourinary cancer; GYN, gynecological cancer; HN, head and neck cancer; IA, intervention arm; LC, lung cancer; meanA, mean age; mdA, median age; MDT, multidisciplinary team; NSCLC, non-small-cell lung cancer; PP, per protocol; RCT, randomized controlled trial; SA, standard arm; SBRT, stereotactic body radiotherapy. Table 3 Outcomes of pivotal CGA-guided trials Study Primary endpoint Primary outcome Selection of secondary endpoints (instrument) Secondary outcomes Cost-effectiveness data Strengths and limitations Mohile et al., 2020 8 Patient satisfaction with communication about aging-related concerns (mHCCQ), measured after the first oncology visit after the GA Greater satisfaction with communication about aging-related concerns in IA (difference in mean score, 1.09 points; 95% CI 0.05-2.13 points, P = 0.04) Number of aging-related concerns discussed during oncology visit, QoL (FACT-G), caregiver satisfaction Number of aging-related concerns discussed during oncology visit higher in IA (difference, 3.59; 95% CI 2.22-4.95, P < 0.001); no difference in QoL; caregivers in IA were more satisfied with communication (difference, 1.05; 95% CI 0.12-1.98, P = 0.03) NA S: involvement of caregivers; involvement of community centers Mohile et al., 2022 6 % of participants with toxicities CTCAE ≥III within 3 months 51% (IA) versus 71% (SA), RR 0.74 (95% CI 0.64-0.86, P = 0.0001) 6 month-OS, DI #1, RDI, falls 6 m-OS 72% (IA) versus 75% (SA), P = 0.38; DI #1↓ 49% (IA) versus 35% (SA), RR 1.38 (95% CI 1.06-1.78, P = 0.015); Falls: 12% (IA) versus 21% (SA), RR = 0.58 (95% CI 0.40-0,84, P = 0.0035) NA S: involvement of community centers Li et al., 2021 24 % of participants with toxicities CTCAE ≥III within 6 months 50.5% (IA; 95% CI 45.6% to 55.4%) versus 60.6% (SA; 95% CI 53.9% to 67.3%), P = 0.02) Advance directive completion, emergency department visits, unplanned hospitalizations, average length of stay, unplanned hospital readmissions, chemotherapy dose modifications, early discontinuation, and OS Advance directive completion: 28.4% (IA) versus 13.3% (SA), P < 0.001; no significant differences in emergency department visits, unplanned hospitalizations, average length of stay, unplanned readmissions, chemotherapy dose modifications or discontinuations, and OS NA S: GA results available for IA and SA, geriatric impairments well balanced between both arms Soo et al., 2022 9 Longitudinal change of QoL over 24 weeks (ELFI) Better adjusted ELFI change scores over 24 weeks in IA ( P = 0.039, effect size = 0.38) Unplanned hospital admissions, OS Fewer unplanned hospital admissions at 24 weeks (multivariable-adjusted incidence rate ratio 0.60; 95% CI 0.42-0.87, P = 0.0066); no difference in OS NA L: 96% received CGA after treatment initiation - no modification of DI#1; no data on toxicities available Puts et al., 2023 11 , 32 QoL at 6 months (measured by EORTC QLQ C 30 questionnaire, global score) No significant difference Treatment-related toxicities CTCAE ≥III, functional status (IADL), unplanned health care use, OS, patient satisfaction, cancer treatment plan modification, adherence to the intervention No significant differences in toxicities, functional status, unplanned health care use, patient satisfaction, cancer treatment plan modification, and OS. Adherence to interventions (selection): 42%/physiotherapy, 89%/specialist referral, 42%/rehabilitation, 72%/dietician CGA cost-effective for patients treated with curative intent, not cost-effective for palliative intent L: CGA was mostly carried out after treatment decision was made and no modification on DI#1 was possible. 1/3 of participants had a G8 score >14 and might not have benefitted from interventions Lund et al., 2021 12 % of patients completing chemotherapy as intended 45% (IA) versus 28% (SA), P = 0.0366; no statistical significance in palliative situation ( P = 0.751), effect most prominent in patients with G8 score ≤11 (OR, 3.76, 95% CI 1.19-13.45) Treatment-related toxicities CTCAE ≥III, dose reductions, PFS, OS, QoL Toxicities: 28% (IA) versus 39% (SA), P = 0.156; DI#1: 60%, no difference between IA and SA; secondary dose reductions: 28% (IA) versus 45% (SA), P = 0.037; no difference in PFS and OS NA L: no GA in SA, imbalance in impairments between groups possible S: homogenous population Paillaud et al., 2022 25 Composite endpoint: 6 month mortality, ADL decline ≥2 points, weight loss ≥10% No significant differences in composite endpoint (in ITT and PP analysis); total events: 41.0% (IA) versus 38.0% (SA), P = 0.53; mortality: 13% (IA) versus 11.4% (SA), P = 0.48; ADL decline: 3.8% (IA) versus 5.5% (SA), P = 0.35; weight loss: 29% (IA) versus 27.4% (SA), P = 0.73 — — NA L: high drop-out rate in IA (73.9%) due to missing GA or discontinuation of geriatric interventions, possible bias DuMontier et al., 2022 13 1-year OS No significant difference; IA: 81.7% (95% CI 71.0% to 90.2%), SA: 78.8% (95% CI 69.7% to 85.7%), P = 0.65 Unplanned care utilization within 6 months; documented EOL goals-of-care discussions; clinician acceptability of model (survey) No significant differences in unplanned care utilizations between IA and SA; EOL discussion↑ in IA (OR = 3.12, 95% CI 1.03-9.41); geriatric consultations highly valued by clinicians NA L: 20% in IA did not receive their geriatric consultation, possible underestimation of effect in IA Orum et al., 2021 26 Completion of initially proposed anticancer treatment within 90 days No significant difference: 61% (IA) versus 52% (SA), RR = 1.16 (95% CI 0.95-1.42), P = 0.14 90 days ADL, physical activity, and hospitalization over time No significant difference in ADL and physical activity; hospitalization: 47% (IA) versus 55% (SA), RR = 0.86 (95% CI 0.69-1.07), P = 0.19 NA Nipp et al., 2020 14 Feasibility outcomes: enrolment rate ≥70%; completion of visits and survey ≥75%; survey on patient’s confidence Endpoints achieved At baseline+12 weeks: QoL (FACT-G), symptoms (ESAS-r), depression (GDS), functioning (ADL, IADL), illness perception (IPQ), communication confidence (EPPI) IA: Less decrement in QoL (mean change−0.77 versus −3.84; ES = 0.21); number of moderate-severe ESAS Symptoms ↓ (mean change, −0.69 versus 11.04; ES = 0.58); less depression (GDS scores mean change, −0.47 versus 10.58; ES = 0.36); communication confidence↑ (mean change, 11.06 versus −0.80; ES = 0.38) NA L: feasibility trial, additional endpoints not powered Nipp et al., 2022 27 Length of post-operative hospitalization PP analysis: primary endpoint reached: 5.90 (IA) versus 8.21 (SA) days, P = 0.024; in ITT analyses: primary endpoint not reached; 7.23 (IA) versus 8.21 (SA) days, P = 0.374 Post-operative ICU use, 90-day hospital readmission rates, complication rates ITT analysis: ICU use: 23.2% (IA) versus 32.4% (SA), P = 0.257; 90-day hospital readmission rates: 21.7% (IA) versus 25.0% (SA), P = 0.690; complication rates: 17.4% (IA) versus 20.6% (SA), P = 0.668; PP analysis: non-significant differences NA S: comparison of ITT and PP analyses allows estimation of impact of the intervention Nadaraja et al., 2020 28 Completion rate of cancer therapy as intended No significant differences: completion rate 48% (IA) versus 54% (SA), P = 0.208 Incidence of treatment-related toxicities CTCAE III-IV, time from randomization to start of treatment, PFS, OS No significant differences between IA and SA. Toxicities: 20% (IA) versus 38% (SA), P = 0.055; mOS: 19.1 months (IA) versus 14.1 months (SA), P = 0.911; mPFS: 7.1 months (IA) versus 9.0 months (SA), P = 0.838 NA Jeppesen et al., 2018 29 Differences in QoL (EQ-5D) after SBRT No significant differences between IA and SA OS and unplanned hospitalizations 1-year OS: 92% (IA) versus 72% (SA), 2-year OS: 69% (IA) versus 59% (SA), P = 0.32; unplanned hospital admission: 46% (IA) versus 52% (SA), P = 0.68 NA Hempenius et al., 2031, 2016 30 , 31 Incidence of delirium within 10 days post-surgery (DOS) No significant differences between IA and SA Severity of delirium, length of hospital stays, complications, mortality, care dependency, QoL (PCS, MCS of SF-36), return to an independent preoperative living situation (ADL) No significant differences between IA and SA in secondary outcomes NA ADL, activities of daily living; CGA, comprehensive geriatric assessment; CI, confidence interval; CTCAE, National Cancer Common Terminology Criteria for Adverse Event; DI #1, dose intensity during cycle 1; DOS, Delirium Observation Scale; ELFI, Elderly Functional Index; EOL, end-of-life; EORTC QLQ, European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire; EPPI, 10-item perceived efficacy in patient-physician interactions questionnaire; ES, effect size; ESAS-r, Edmonton Symptom Assessment System – Revised; FACT-G, Functional Assessment of Cancer Therapy General; GA, geriatric assessment; GDS, Geriatric Depression Scale; IA, intervention arm; IADL, instrumental activities of daily living; ICU, intensive care unit; IPQ, Brief Illness Perception Questionnaire; ITT, intention-to-treat; L, limitations; MCS, mental component summary measure; mHCCQ, modified Health Care Climate Questionnaire; mOS, median overall survival; NA, not available; OR, odds ratio; OS, overall survival; PCS, physical component summary measure; PFS, progression-free survival; PP, per protocol; QoL, quality of life; RDI, relative dose intensity; RR, relative risk; S, strength; SA, standard arm; SBRT, stereotactic body radiotherapy; SF-36, Short Form-36.

The Improving Communication in Older Cancer Patients and Their Caregivers (COACH) cluster-randomized trial investigated whether providing oncologists the results of GA and GA-guided recommendations improved patient and caregiver satisfaction as well as number and quality of conversations about aging-related concerns compared to those who received usual care. 8 The study recruited 541 patients aged ≥70 years with an advanced solid malignancy or lymphoma who had one or more GA-identified impairment, and 414 associated caregivers. The study recruited a population of vulnerable older adults with cancer as 90% of patients were found to have three or more impairments in GA domains. Compared to the usual care arm, patients and caregivers in the intervention arm were more satisfied with communication about aging-related concerns and they had more aging-related conversations. Quality of life (QoL) was not different between arms.

The GAP70+ cluster-randomized study employed a similar study design and eligibility criteria, except that patients were also planning to start a new cancer treatment regimen with a high risk of toxicity ( N = 718). 6 The study found that the proportion of grade 3-5 toxicities was lower in the intervention arm compared to usual care [51% versus 71%; relative risk (RR): 0.74, P = 0.0001]. Non-hematologic adverse events (AEs) were also lower, with no difference in survival between arms. Notably, upfront dose reduction was more common in the intervention arm versus the usual-care arm (49% versus 35%, adjusted RR: 1.38, P = 0.015) and subsequent dose modifications due to toxicity were lower in the intervention arm (43% versus 58%, P = 0.18). Patients in the intervention arm also experienced significantly fewer falls (RR: 0.58, P = 0.0035) and reduction in polypharmacy ( P = 0.015). Together, both the COACH and GAP70+ studies demonstrate that providing oncologists with GA and GA-guided recommendations can lead to a decrease in serious toxicities and improvements in patient and caregiver communication and satisfaction without a negative impact on overall survival.

The GAIN study ( N = 605) utilized a different model than COACH and GAP70+. 8 In the intervention arm, a multidisciplinary team implemented GA-guided interventions, whereas in the usual-care arm, treating oncologists received the GA results for use at their discretion. The study recruited patients aged ≥65 years with a solid tumor who were starting a new chemotherapy regimen. Like GAP70+, the study showed a 10.1% reduction in the incidence of grade 3-5 hematologic and non-hematologic toxicities favoring the intervention arm (50.5% versus 60.6%, P = 0.02). Completion of advanced directives was also higher in the intervention arm (28.4% versus 13.3%; P < 0.001), with no differences in survival between arms. The study confirmed that use of a multidisciplinary team model to deliver GAM reduced the rate of serious toxicities and increased the completion of advanced directives.

The INTEGERATE study, a randomized parallel group trial, examined the effect of GAM integrated into oncology care versus usual care on QoL in patients aged >70 years receiving systemic cancer treatments ( n = 154). 9 Results showed that patients in the intervention arm reported significantly higher QoL scores compared to those in the usual-care arm, with the most significant difference observed at week 18 ( P = 0.039). Moreover, there were fewer unplanned hospitalizations in the intervention group by week 24 ( P = 0.0066). Exploratory analyses revealed that patients receiving GAM experienced significantly fewer toxicities ( P = 0.0013), leading to a lower rate of early treatment discontinuation ( P = 0.010). Similar to the GAIN study, the INTEGERATE trial utilized a multidisciplinary approach and demonstrated that integrating GAM not only improved QoL but also reduced health care utilization in older adults with cancer.

The Canadian 5C randomized multicenter trial aimed to determine whether GAM could enhance QoL compared to standard care among patients aged ≥70 years with solid malignancies or myeloma/lymphoma undergoing adjuvant or palliative systemic cancer treatments ( N = 340). 10 , 11 However, despite the provision of GAM for 6 months, there was no observed improvement in global QoL. Additionally, the study found no significant differences in OS, treatment-related AEs, alterations in treatment plans, or rates of unplanned hospitalization. It is worth noting that in this study, GA was conducted on the first day of treatment for most patients, potentially minimizing the impact of GA on treatment adjustments.

The randomized phase III GERICO trial investigated the effect of GAM in adults ≥70 years of age with colorectal cancer receiving either adjuvant or first-line palliative systemic cancer treatments ( N = 142). 12 Notably, a higher proportion of patients in the GAM arm successfully completed their planned treatments compared to those in the control arm (45% versus 28%, P = 0.0366). Furthermore, individuals in the intervention group experienced lower rates of dose reduction (28% versus 45%, P = 0.037) and were more likely to receive all chemotherapy cycles at the intended dosage (65% versus 42%, P = 0.007). Additionally, they exhibited significant improvements in QoL ( P = 0.048) and mobility ( P = 0.008). However, the trial observed no discernible differences in AEs or QoL between the two groups.

Dumontier et al. conducted a randomized controlled trial to evaluate the impact of integrating geriatric consultation within the oncology clinic compared to standard care among adults aged ≥75 years diagnosed with hematologic malignancies ( N = 160). 13 The study found that 80% of participants randomized to receive geriatric consultation completed at least one visit with a geriatrician. There was no significant improvement in 1-year survival rates compared to standard care ( P = 0.65). Additionally, there was no difference in the incidence of emergency department visits, hospital admissions, or days spent in the hospital. Nevertheless, the intervention did lead to a notable more than threefold increase in the likelihood of engaging in end-of-life goals-of-care discussions [odds ratio (OR) = 3.12, 95% confidence interval (CI) 1.03-9.41].

Nipp et al. conducted a randomized study focusing on a 12-week transdisciplinary intervention designed to address both geriatric and palliative care needs among adults aged ≥65 years diagnosed with incurable gastrointestinal or lung cancer. 14 Almost 90% of patients completed both the baseline and week 12 surveys, indicating a high level of engagement and acceptance of the intervention. In comparison to those receiving usual care, patients in the intervention group experienced a smaller decrease in QoL [effect size (ES) = 0.21], a reduction in the number of moderate to severe symptoms (ES = 0.58), and an improvement in communication confidence (ES = 0.38). This pilot study underscores the feasibility and acceptability of transdisciplinary interventions, with small to medium effects on QoL, symptom management, and communication.

Summary and recommendations

Collectively, while models of care differed, several large, randomized trials have demonstrated the positive impact of GAM on multiple meaningful endpoints. These trials demonstrated improvements in QoL, treatment tolerability, physical function or independence, and communication. Although GAM does not influence survival, these outcomes are patient centered and valued by older adults. Additionally, three recently published systematic reviews have further reinforced the benefits of GAM, particularly in reducing treatment-related toxicity and the need for dose reductions. 15 , 16 , 17 Note that these trials were conducted primarily in high-income countries, and many took place in settings with ample resources.

Taken together, the ESMO/SIOG Cancer in the Elderly Working Group proposes the following recommendations: 1. GAM should be implemented in patients aged ≥70 years (and ≥65 years when possible) being considered for cancer-directed treatments, especially systemic treatments. 2. GAM should be carried out as early as possible before treatment initiation, and when possible, before finalization of the treatment plan. 3. In settings where GAM cannot be carried out for all patients, use validated screening tools to identify those who are likely to benefit from subsequent GAM. 18 4. Models of GAM delivery needs to be tailored to the availability of local resources, settings (e.g. academic cancer centers versus community oncology practices), and staff (e.g. geriatricians or geriatric oncologists, and other allied health care professionals). 5. Utilize the Cancer and Aging Research Group (CARG) or Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) tools to estimate chemotherapy toxicity in older patients with cancer.

Models to deliver GAM in clinical practice

Understanding local resources and expertise available can guide the appropriate models to deliver GAM ( Table 4 ). The traditional gold standard model of care involves a comprehensive multidisciplinary clinic where patients undergo GA and receive oncologic treatment planning from either a geriatrician or geriatric oncologist with the primary oncologist at a single time point and setting (unless the geriatric oncologist serves as the primary oncologist). 19 During this visit, patients also have access to supportive or holistic care services, such as dietitians, pharmacists, physical/occupational therapists, and social workers, minimizing the need for additional clinic visits. This model creates an opportunity for ongoing follow-up throughout the treatment course to address any changes or challenges that arise. While providing comprehensive care, its implementation is limited to a few select centers with ample resources and specialized personnel. Consequently, several alternative models have emerged to deliver GAM. 20 Table 4 Models of care for geriatric assessment and management based on local resources Settings Proposed approaches for geriatric assessment and management Models of care High resource (geriatric oncologist or geriatrician and oncologist are available) • Comprehensive multidisciplinary clinic where patients undergo geriatric assessment and management • Chemotherapy toxicity tools • Traditional gold standard morel • Shared-care model Intermediate resource (geriatrician and oncologist are available) • Validated screening tools (e.g. Geriatric-8, Vulnerable Elders Survery-13, Senior Adult Supplement Screening Questionnaire) or abbreviated geriatric assessment • Geriatric assessment and management based on pre-defined intervention plan or evaluation in a comprehensive multidisciplinary clinic if positive screening • Chemotherapy toxicity tools by the geriatricians or oncology teams • Shared-care model • Two-step consultative model Low resource (oncologist is available) • Validated screening tools • Selected validated geriatric assessment tool that may or may not be based on screening tools • Pre-defined geriatric intervention plan (i.e. carried out in the community setting) • Chemotherapy toxicity tools

In the shared-care model, patients are co-managed by a geriatrician and an oncologist, with separate visits to each specialist in different clinics, possibly at different times. The geriatrician conducts the GA, while the oncologist carried out the oncologic assessment. An interdisciplinary team then collaborates to develop a comprehensive care plan, including referrals to additional support services. The geriatrician and support services may provide longitudinal care alongside the oncologist. While more feasible, particularly in moderate resource settings, this model places a higher burden on patients and caregivers due to multiple visits. A variation of this model is having a geriatrician embedded in the oncology clinic without access to support services.

For centers with intermediate resources, a two-step consultative model may be more practical. An oncologist uses a geriatric screening tool [e.g. Geriatric 8, Vulnerable Elders Survey-13, Senior Adult Supplement Screening Questionnaire (SAOP3)] to identify patients at higher risk who would benefit from a GA conducted by a geriatrician or geriatric oncologist. 21 , 22 , 23 These patients are then referred to the geriatric-specialized team for evaluation, after which a summary of recommendations is shared with the oncologist to inform the treatment plan. In this model, the oncology team carries the onus to initiate the geriatric screening tool and refer patients to the geriatrician or geriatric oncologist where a traditional or shared-care model can be implemented.

In settings with even more limited resources, geriatric screening tools may be utilized solely to facilitate selected management decisions (e.g. cancer-directed treatment versus specific non-oncologic intervention). In any of the aforementioned models, innovative strategies such as telehealth or video-assisted GA should be considered.

Future directions and conclusions

GAM is crucial in delivering patient-centered and personalized care to older adults with cancer. The working group proposes several future directions to advance this field: (i) studying GAM (by itself or with other interventions) or comparing models of GAM in specific cancer types; (ii) investigating the effects of longitudinal GAM on outcomes; (iii) exploring the role of GAM during treatment (e.g. maintenance phase) and after completion of curative-intent treatments; (iv) incorporating biological markers of aging with GA to predict outcomes and guide subsequent management; (v) developing and validating predictive models and risk stratification algorithms, such as machine learning, to better identify older adults with cancer at risk and streamline referrals and subsequent management; (vi) leveraging technologies (e.g. telemedicine, wearables, mobile applications) to monitor and deliver supportive care interventions as well as facilitate self-management; (vii) using dissemination and implementation science methods to understand barriers and facilitate the integration of GAM into clinical practice; (viii) studying the impact of system change (e.g. implementing age-friendly health care) on outcomes; and (ix) integrating novel or combined endpoints in clinical trials of GAM, such as both objective outcomes (e.g. toxicities) and patient-reported outcomes (e.g. functional status, QoL). Advancing collaborative research in these areas will lead to improvement of outcomes that matter to this growing and diverse population.

References

1 Sung H. Ferlay J. Siegel R.L. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries CA Cancer J Clin 71 3 2021 209 249 33538338 10.3322/caac.21660

2 Pilleron S. Gnangnon F. Noronha V. Soto-Perez-de-Celis E. Cancer incidence estimates in adults aged 60 years and older living in low-and-middle-income countries for the years 2020 and 2040 Ecancermedicalscience 17 2023 1594 37799947 10.3332/ecancer.2023.1594 PMC10550290

3 Garner W.B. Smith B.D. Ludmir E.B. Predicting future cancer incidence by age, race, ethnicity, and sex J Geriatr Oncol 14 1 2023 101393 10.1016/j.jgo.2022.10.008 36692964

4 Medeiros B.C. Satram-Hoang S. Hurst D. Hoang K.Q. Momin F. Reyes C. Big data analysis of treatment patterns and outcomes among elderly acute myeloid leukemia patients in the United States Ann Hematol 94 7 2015 1127 1138 25791241 10.1007/s00277-015-2351-x PMC4432101

5 Medeiros B.C. Satram-Hoang S. Momin F. Parisi M. Increase in chemotherapy use and associated survival benefit among medicare-aged patients with acute myeloid leukemia (AML) Blood 132 suppl 1 2018 3591

6 Mohile S.G. Mohamed M.R. Xu H. Evaluation of geriatric assessment and management on the toxic effects of cancer treatment (GAP70+): a cluster-randomised study Lancet 398 10314 2021 1894 1904 34741815 10.1016/S0140-6736(21)01789-X PMC8647163

7 Mohile S.G. Dale W. Somerfield M.R. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology J Clin Oncol 36 22 2018 2326 2347 29782209 10.1200/JCO.2018.78.8687 PMC6063790

8 Mohile S.G. Epstein R.M. Hurria A. Communication with older patients with cancer using geriatric assessment: a cluster-randomized clinical trial from the National Cancer Institute Community Oncology Research Program JAMA Oncol 6 2 2020 196 204 31697365 10.1001/jamaoncol.2019.4728 PMC6865234

9 Soo W.K. King M.T. Pope A. Parente P. Dārziņš P. Davis I.D. Integrated geriatric assessment and treatment effectiveness (INTEGERATE) in older people with cancer starting systemic anticancer treatment in Australia: a multicentre, open-label, randomised controlled trial Lancet Healthy Longev 3 9 2022 e617 e627 36102776 10.1016/S2666-7568(22)00169-6

10 Puts M.T.E. Hsu T. Mariano C. Clinical and cost-effectiveness of a comprehensive geriatric assessment and management for Canadian elders with cancer-the 5C study: a study protocol for a randomised controlled phase III trial BMJ Open 9 5 2019 e024485 10.1136/bmjopen-2018-024485 PMC6530407 31079079

11 Puts M. Alqurini N. Strohschein F. Impact of geriatric assessment and management on quality of life, unplanned hospitalizations, toxicity, and survival for older adults with cancer: the randomized 5C Trial J Clin Oncol 41 4 2023 847 858 36473126 10.1200/JCO.22.01007 PMC9902020

12 Lund C.M. Vistisen K.K. Olsen A.P. The effect of geriatric intervention in frail older patients receiving chemotherapy for colorectal cancer: a randomised trial (GERICO) Br J Cancer 124 12 2021 1949 1958 33828260 10.1038/s41416-021-01367-0 PMC8185087

13 DuMontier C. Uno H. Hshieh T. Randomized controlled trial of geriatric consultation versus standard care in older adults with hematologic malignancies Haematologica 107 5 2022 1172 1180 34551505 10.3324/haematol.2021.278802 PMC9052912

14 Nipp R.D. Temel B. Fuh C.X. Pilot randomized trial of a transdisciplinary geriatric and palliative care intervention for older adults with cancer J Natl Compr Cancer Netw 18 5 2020 591 598 10.6004/jnccn.2019.7386 PMC7851750 32380460

15 Anwar M.R. Yeretzian S.T. Ayala A.P. Effectiveness of geriatric assessment and management in older cancer patients: a systematic review and meta-analysis J Natl Cancer Inst 115 12 2023 1483 1496 37738290 10.1093/jnci/djad200

16 Chuang M.H. Chen J.Y. Tsai W.W. Impact of comprehensive geriatric assessment on the risk of adverse events in the older patients receiving anti-cancer therapy: a systematic review and meta-analysis Age Ageing 51 7 2022 afac145 10.1093/ageing/afac145 35776674

17 Disalvo D. Moth E. Soo W.K. The effect of comprehensive geriatric assessment on care received, treatment completion, toxicity, cancer-related and geriatric assessment outcomes, and quality of life for older adults receiving systemic anti-cancer treatment:a systematic review J Geriatr Oncol 14 8 2023 101585 10.1016/j.jgo.2023.101585 37573197

18 Decoster L. Van Puyvelde K. Mohile S. Screening tools for multidimensional health problems warranting a geriatric assessment in older cancer patients: an update on SIOG recommendations Ann Oncol 26 2 2015 288 300 24936581 10.1093/annonc/mdu210

19 Magnuson A. Dale W. Mohile S. Models of care in geriatric oncology Curr Geriatr Rep 3 3 2014 182 189 25587518 10.1007/s13670-014-0095-4 PMC4289627

20 Chapman A.E. Elias R. Plotkin E. Lowenstein L.M. Swartz K. Models of care in geriatric oncology J Clin Oncol 39 19 2021 2195 2204 34043453 10.1200/JCO.21.00118 PMC10476747

21 Bellera C.A. Rainfray M. Mathoulin-Pélissier S. Screening older cancer patients: first evaluation of the G-8 geriatric screening tool Ann Oncol 23 8 2012 2166 2172 22250183 10.1093/annonc/mdr587

22 van Walree I.C. Vondeling A.M. Vink G.R. Development of a self-reported version of the G8 screening tool J Geriatr Oncol 10 6 2019 926 930 31477512 10.1016/j.jgo.2019.08.011

23 Owusu C. Koroukian S.M. Schluchter M. Bakaki P. Berger N.A. Screening older cancer patients for a comprehensive geriatric assessment: a comparison of three instruments J Geriatr Oncol 2 2 2011 121 129 21927633 10.1016/j.jgo.2010.12.002 PMC3173499

24 Li D. Sun C.L. Kim H. Geriatric assessment-driven intervention (GAIN) on chemotherapy-related toxic effects in older adults with cancer: a randomized clinical trial JAMA Oncol 7 11 2021 e214158 10.1001/jamaoncol.2021.4158 PMC8485211 34591080

25 Paillaud E. Brugel L. Bertolus C. Effectiveness of geriatric assessment-driven interventions on survival and functional and nutritional status in older patients with head and neck cancer: a randomized controlled trial (EGeSOR) Cancers (Basel) 14 13 2022 3290 35805060 10.3390/cancers14133290 PMC9265581

26 Orum M. Eriksen S.V. Gregersen M. The impact of a tailored follow-up intervention on comprehensive geriatric assessment in older patients with cancer - a randomised controlled trial J Geriatr Oncol 12 1 2021 41 48 32747208 10.1016/j.jgo.2020.07.011

27 Nipp R.D. Qian C.L. Knight H.P. Effects of a perioperative geriatric intervention for older adults with cancer: a randomized clinical trial J Geriatr Oncol 13 4 2022 410 415 35074322 10.1016/j.jgo.2022.01.001 PMC9058195

28 Nadaraja S. Matzen L.E. Jorgensen T.L. The impact of comprehensive geriatric assessment for optimal treatment of older patients with cancer: a randomized parallel-group clinical trial J Geriatr Oncol 11 3 2020 488 495 31279749 10.1016/j.jgo.2019.06.019

29 Jeppesen S.S. Matzen L.E. Brink C. Impact of comprehensive geriatric assessment on quality of life, overall survival, and unplanned admission in patients with non-small cell lung cancer treated with stereotactic body radiotherapy J Geriatr Oncol 9 6 2018 575 582 29871849 10.1016/j.jgo.2018.05.009

30 Hempenius L. Slaets J.P. van Asselt D. Long term outcomes of a geriatric liaison intervention in frail elderly cancer patients PLoS One 11 2 2016 e0143364 10.1371/journal.pone.0143364 PMC4762573 26901417

31 Hempenius L. Slaets J.P. van Asselt D. de Bock T.H. Wiggers T. van Leeuwen B.L. Outcomes of a geriatric liaison intervention to prevent the development of postoperative delirium in frail elderly cancer patients: report on a multicentre, randomized, controlled trial PLoS One 8 6 2013 e64834 10.1371/journal.pone.0064834 PMC3686791 23840308

32 Sahakyan Y. Li Q. Alibhai S.M.H. Cost-utility analysis of geriatric assessment and management in older adults with cancer: economic evaluation within 5C trial J Clin Oncol 42 1 2024 59 69 37871266 10.1200/JCO.23.00930 PMC10730076

Acknowledgements

This is a position paper initiated by the ESMO/SIOG Cancer in the Elderly Working Group. We thank ESMO and SIOG leadership for their support in this manuscript. Dr Loh is supported by the National Cancer Institute of the National Institutes of Health (R00CA237744), National Institute of Aging of the National Institutes of Health (R03AG073985) and Conquer Cancer Foundation American Society of Clinical Oncology-Walther Cancer Foundation Career Development Award. Dr. Krok-Schoen is supported by the National Institute on Aging of the National Institutes of Health (R21AG078258-01A1). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding

This work was supported by the 10.13039/501100007075 European Society for Medical Oncology (no grant number).

Disclosure

KPL reports receipt of a fee as an invited speaker from Pfizer; receipt of a fee for providing consultancy from Pfizer, Seagen. GL reports receipt of a fee for participation in an expert panel from Nutricia AS; receipt of a fee as an invited speaker from Servier. SPA reports receipt of a fee for participation in Advisory Board from AstraZeneca, QED Therapeutics, Seagen; receipt of a fee as an invited speaker from Bristol Meyers Squibb, Exelixis, Tempus; no financial interest for serving as a local principal investigator in research conducted by Beigene, Caris Life Sciences, Faron, Genentech, Novartis, Tvardi. NRN reports receipt of a fee for participation in advisory board from Hexal, Janssen-Cilag, Pfizer; receipt of travel support from AbbVie, Jazz, Novartis; receipt of licensing fee, royalties from De Gruyter, Urban & Fischer; non-remunerated advisory role in My Cancer Navigator. TA reports receipt of a fee for participation in advisory board from Delcath; receipt of a fee as an invited speaker from BMS, Neracare, Novartis, Pierre Fabre; receipt of a fee for writing engagement from CeCaVa; receipt of funding for research to institution from MNI—Naturwissenschaftliches und Medizinisches Institut, Neracare, Novartis, Pascoe, Sanofi, Skyline-Dx; receipt of research grant to institution from iFIT, Novartis; financial interest to institution as a coordinating principal investigator from Unicancer; financial interest to institution as a local principal investigator from Agenus Inc, AstraZeneca, BMS, Biontech, HUYA Bioscience, Immunocore, IO Biotech, MSD, Pfizer, Philogen, Regeneron, Roche, University Hospital Essen; relations with INFARMED-PT for providing clinical expertise in medical oncology. EM reports receipt of a fee as an invited speaker from AstraZeneca; receipt of a fee for providing an expert testimony from MSD, Novartis. LB reports receipt of a fee for participation in advisory board from Amgen, AstraZeneca, Boehringer-Ingelheim, Daiichi Sankyo, Eisai, Exact Sciences, Gilead, Menarini, Pfizer, Pierre Fabre, Sanofi, Seattle Genetics; receipt of a fee as an invited speaker from Lilly, Novartis, Roche; receipt of a research grant to institution from Celgene, Genomic Health, Novartis. EB reports receipt of a fee for participation in advisory board from Menarini, Pfizer, Sandoz; receipt of a fee as a invited speaker from Daiichi, Eli Lilly, Incyte, Pfizer, Seagen, Takeda; receipt of a fee for participation in IDMC from Daiichi; receipt of a financial interest to institution as a coordinating principal investigator from Pfizer; receipt of a financial interest to institution as a local principal investigator from AstraZeneca, Daiichi. CB reports receipt of a fee to institution for participation in advisory board from BMS; receipt of a fee as an invited speaker from AstraZeneca; receipt of a fee to institution for providing an expert testimony from MSD; receipt of a research grant to institution from BMS; non-financial interest as a coordinating principal investigator from iTeos, Janssen, Pyramid Bioscience, Seattle Genetics, Taiho; non-financial interest as a local principal investigator from Amgen, AstraZeneca, Bicycle Therapeutics, MSD, Roche Genentech, Tango. NMLB reports receipt of a fee for participation in advisory board from Abbott, Astellas, Pfizer, Sanofi; receipt of a fee as an invited speaker from AbbVie, AstraZeneca, Gilead, Lilly, Novartis, Pfizer, Roche, Sanofi, Servier; receipt of a travel support from Exact Sciences, Lilly, Novartis, Pfizer. MF reports receipt of a fee for participation in advisory board from Sando; receipt of a fee as an invited speaker from MSD; receipt of funding to institution for research from IPSEN. RK reports receipt of a fee to institution for participation in advisory board from Amgen, AstraZeneca, Bayer, BMS, Ferring, Ipsen, Johnson and Johnson, MSD, Pfizer; receipt of a fee to institution as an invited speaker from Amgen, Astellas, AstraZeneca, BMS, Ipsen, Johnson and Johnson, Merck, MSD, Novartis, Sanofi; receipt of research grant to institution from Eisai, Johnson and Johnson, Sanofi. DP reports receipt of a fee to institution for participation in advisory board from BMS, Ipsen, Merck Serono, Servier; receipt of a fee to institution as an invited speaker from Amgen, BMS, Ipsen, Merck Serono, Servier; non-financial interest from receipt of a research grant to institution from MSD. CS reports receipt of a fee for participation in advisory board from AstraZeneca, GSK, Ipsen, Janssen, MSD, Sanofi; receipt of a fee as an invited speaker from BMS, Eisai. All other authors have declared no conflicts of interest.