Multiple myeloma care, treatment patterns, and treatment durations in academic and community care settings.

Introduction

The treatment landscape for multiple myeloma (MM) has significantly advanced over the past decade [ 1 ]. Treatment options available to patients now include immunomodulatory drugs, proteasome inhibitors (PIs), chemotherapy, monoclonal antibodies, stem cell transplantation (SCT), chimeric antigen receptor (CAR) T-cell therapy, bispecific antibody therapies and other novel agents [ 2 , 3 ]. Complementary and synergistic mechanisms of action of these agents led to the development of various combination therapies, from doublet to quadruplet regimens, that provide durable disease control and improve survival [ 1 ]. Unfortunately, most patients experience multiple relapses, develop disease refractory to treatment, and require sequential lines of therapy (LOT) [ 2 , 4 ].

Patients with MM often experience complex treatment journeys [ 5 ]. Clinical teams must consider a host of factors to individualize treatment, including age, patient fitness, comorbidities, disease characteristics, accessibility to resources, and prior treatment in the relapsed and refractory (RR) setting [ 6 , 7 ]. Recent advances of novel combinations into early LOT (e.g., increased use of triplet regimens) has altered the RRMM treatment landscape and the need for retreatment with a previously used drug class [ 8 , 9 ]. Although most patients in the US receive care at community cancer centers [ 8 , 10 ], some may need to shift to academic centers, receiving care in a “mixed” setting, for specialized treatments, such as SCT or CAR-T, and access to clinical trials [ 6 , 11–16 ]. Moreover, observational studies have reported improved survival for patients receiving treatment in academic versus community centers and in higher versus lower volume centers [ 14 , 15 , 17–19 ]. The different outcomes by care setting may be due in part to variability across a number of factors, including experience of centers in treating MM, patient characteristics including socioeconomic status, and access to novel treatments and specialized care [ 14 ]. Patients who shift between settings have not been well described and their outcomes have yet to be evaluated.

Given the complexity of MM management and differential outcomes by treatment center, it is important to better understand a patient’s treatment journey, including shifts in care, to identify unmet needs and gaps in care. Real-world data sources, such as claims data, generally lack indicators of the setting (i.e., academic or community) in which treatment took place, thus limiting comparisons between care settings. Electronic medical record databases have only recently added these indicators.

This observational study in patients with MM linked data from a US insurance claims database to a database of healthcare provider affiliations to evaluate outcomes across patient cohorts defined by the care setting of treatment (academic only, community [non-academic] only, or both [mixed]), as well as treatment patterns, healthcare resource utilization (HCRU), and cost of care (e.g., treatment, office visits, hospitalization) in each setting (academic and community).

Methods

Study design

This observational, retrospective cohort study utilized PharMetrics® Plus claims data linked to OneKey™ healthcare professional (HCP) profile data to identify patients with MM with administrative claims from academic and community settings. PharMetrics® Plus contains adjudicated claims and provides information on the inpatient/outpatient diagnoses, procedures, prescription records, pharmacy/medical benefit (co-payment, deductible), inpatient stay (admission type and source, discharge status) and provider details [ 20 ]. OneKey™ is a US health-care provider reference database and identifies providers with affiliations to academic settings, community settings, or dual affiliations [ 21 ]. When available, patients in this study had data supplemented from the Experian ConsumerView℠ database, which collects data from a variety of public and proprietary sources, including self-reported information, public records, and purchase transaction information. IQVIA used a proprietary algorithm and a deterministic matching method with a trusted third party to create a patient key to link disparate data sets, and a de-identification process that ensured compliance with Health Insurance Portability and Accountability Act (HIPAA) regulations.

The study included database claims between 1 April 2017, and 30 June 2022, and consisted of three periods: pre-index, index, and post-index follow-up. The pre-index period was a 6-month minimum washout period to establish the first line of therapy (LOT). The index period lasted from 1 October 2017, to 31 December 2021, and the index date was the date of earliest observed MM treatment. The index period was selected to utilize the most recent 5 years of PharMetrics® Plus data, as well as to allow for at least 6 months of pre- and post-index follow-up. This period used OneKey™ data (provider/facility affiliation [academic or community] associated with the national provider identifier [NPI] from each PharMetrics® Plus medical claim) to determine the initial care setting. An academic setting was defined as a healthcare organization associated with a teaching hospital or medical, dental, and/or nursing school, while non-academic healthcare organizations defined the community setting; some providers had dual affiliations. The post-index period followed the index date and was variable for each patient but required the 6-month minimum. All MM claims were assigned to a care setting throughout the entire index/post-index period using OneKey™ data.

Study population

Selection criteria identified patients with newly-diagnosed MM who received a first LOT (LOT1) during the index period. Patients must have been adults with ≥ 1 claim for an MM treatment during the indexing period in the PharMetrics® Plus database, with ≥6 months of continuous enrollment pre- and post-index date. Patients had a diagnosis of MM (International Classification of Disease Version 9 [ICD-9] code 203.0×, ICD-10 code C90.0×) before the index date and any time on or after the index date until the end of follow-up. Patients must have had no MM treatments during the pre-index period, except for steroids. Patients must have been ≥18 years old on the index date. OneKey™ database linkage required any MM diagnosis or treatment administrative claim (medical or pharmacy) with national provider identifier (NPI) ±15 days from the index date. Patients were excluded if there were data quality issues, such as missing age and/or gender.

Study outputs

A primary objective of this study was to describe baseline demographics, clinical, and socioeconomic characteristics of patients with MM by the care setting of treatment. Patients were aggregated to one of three cohorts based on the provider affiliation for treatment claims: all MM treatments in an academic setting, academic only cohort; all MM treatments in a community setting, community only cohort; and treatment in both academic and community settings or from physicians with dual affiliations, mixed cohort. Baseline characteristics were collected during pre-index (National Cancer Institute [NCI] comorbidity index score) and on the index date (age, sex, geographical region, payer type). Clinical trial participation was assessed post-index. Data from Experian could have been collected at any time during the study period. A primary objective for the mixed cohort was evaluating shifts in care (defined as a patient moving from one care setting to another) during the post-index period. Assessment of outcomes during the post-index period by care setting of treatment was also a primary objective and included duration of treatment overall and by LOT (time from initiation of the LOT to the end of the LOT), and time to next treatment (TTNT) defined as the time from each LOT start date to the next LOT start date. First LOT and LOT advancements were determined as described in Supplementary Table S1.

The study also included analyses of MM care (e.g., treatment, office visits, hospitalization) by setting. Each claim was associated with a care setting based on the provider affiliation: academic, community, or physician with dual affiliation. Patients were not stratified into cohorts based on setting of MM treatment. A primary objective of these analyses was to evaluate treatment patterns by care setting, including number of LOT and treatment regimens (e.g., triplet, quadruplet), drug classes utilized, and retreatment (defined as treatment with the same drug used in a previous LOT). Drug classes included monoclonal antibodies (mAbs, anti-CD38 [cluster of differentiation 38] or anti-SLAMF7 [signaling lymphocytic activation molecule family member 7]), immunomodulatory drugs, PIs, selective inhibitor of nuclear export (SINE), and chemotherapy. Use of steroids was captured during a LOT but was not used to determine the index date, advances in LOT, or assessment of retreatment because of their frequent use across regimens and therapy lines, and potential use for indications beyond MM. Secondary objectives were to assess MM-related HCRU and costs based on claims by care setting. MM-related HCRU claims were assessed for MM-related visits, including inpatient hospital (e.g., SCT), emergency department (ED), urgent care, outpatient, and physician/non-physician office visits, as well as prescription claims. Costs were estimated from claims for MM-related visits and prescriptions and reported as cost per visit or per prescription. Costs were adjusted and reported in 2022 US dollars using the medical care services component of the Consumer Price Index (CPI). Costs represent the contracted amount for covered medical services or supplies that the health plan agreed to pay to service providers for services rendered, including prescription costs as well as out-of-pocket expenses such as co-payment and co-insurance for which patients were held responsible.

Data analysis

Standardized mean differences (SMD) and confidence intervals (CIs) were used to assess differences in categorical and continuous measures between care setting. An SMD ≥ 0.10 was considered a meaningful observed difference between care setting of the patient cohorts. Medians and associated 95% CIs for duration of treatment and TTNT were estimated using the Kaplan-Meier method. Patients without an event were censored on the date of loss of visibility in the data or the end of the study period, whichever occurred first. Statistical analyses were performed using SAS v9.4, SAS Institute, Cary, NC.

Results

Patients

Overall

A total of 35,282 patients had ≥ 1 administrative claim recording an MM diagnosis and ≥1 month of continuous enrollment for both pharmacy and medical benefits during the study period. Of these patients, 3778 met the eligibility criteria and had a link to the OneKey™ database (Supplementary Figure S1). Overall, the median age was 61 years (IQR 55–66), with 28.1% 65+ years old; 58.4% male, and 87.1% commercial/self-insured ( Table 1 ); comorbidities were common and included hematologic complications (64.2%), anemia (61.9%), and hypertension (57.9%) ( Table 2 ). Table 1. Patient demographics and clinical characteristics overall and across cohorts defined by care setting of treatment. Overall N = 3778 Academic only cohort N = 530 Community only cohort N = 1647 Mixed cohort N = 1601 SMD (community – academic) SMD (mixed-academic) SMD (mixed- community) Age, years Mean (SD) NR 59.6 (9.7) 63.2 (10.5) 59.3 (9.2) 0.35 −0.03 −0.39 Median 61 60 62 60 – – – Aged 65+ years, n (%) 1061 (28) 110 (21) 597 (36) 354 (22) 0.35 0.03 −0.31 Male, n (%) 2205 (58) 313 (59) 952 (58) 940 (59) −0.03 −0.01 0.02 Geographic region, n (%) Northeast 663 (18) 147 (28) 192 (12) 324 (20) −0.41 −0.18 0.24 Midwest 1025 (27) 143 (27) 456 (28) 426 (27) 0.02 −0.01 −0.02 South 1637 (43) 200 (38) 765 (46) 672 (42) 0.18 0.09 −0.09 West 453 (12) 40 (8) 234 (14) 179 (1) 0.22 0.12 −0.09 Payer type, n (%)* Commercial/self-insured 3291 (87) 505 (95) 1328 (81) 1458 (91) −0.46 −0.17 0.30 Medicare (commercially managed) † 487 (13) 25 (5) 319 (19) 143 (9) 0.46 0.17 −0.30 Experian-linked data Not linked, n (%) 1345 (36) 212 (40) 554 (34) 579 (36) −0.13 −0.08 0.05 Race/Ethnicity, n (%) ‡ Caucasian 1887 (50) 249 (47) 821 (50) 807 (50) 0.06 0.07 0.01 African American 277 (7) 39 (7) 132 (8) 106 (7) 0.02 −0.03 −0.05 Hispanic 171 (5) 15 (3) 81 (5) 75 (5) 0.11 0.10 −0.01 Asian 54 (1) 8 (2) 28 (2) 18 (1) 0.02 −0.03 −0.05 Other 54 (1) 7 (1) 31 (2) 16 (1) 0.04 −0.03 −0.07 Household Income, n (%) ‡ <$25,000 264 (7) 28 (5) 129 (8) 107 (7) 0.10 0.06 −0.04 $25,000–$49,999 369 (10) 42 (8) 198 (12) 129 (8) 0.14 0.00 −0.13 $50,000–$74,999 560 (15) 83 (16) 256 (16) 221 (14) 0.00 −0.05 −0.05 $75,000–$99,999 455 (12) 58 (11) 189 (11) 208 (13) 0.02 0.06 0.05 $100,000–$124,999 223 (6) 25 (5) 100 (6) 98 (6) 0.06 0.06 0.00 $125,000–$149,999 196 (5) 35 (7) 82 (5) 79 (5) −0.07 −0.07 0.00 $150,000+ 366 (10) 47 (9) 139 (8) 180 (11) −0.02 0.08 0.09 Education, n (%) ‡ Less than high school diploma 191 (5) 23 (4) 96 (6) 72 (4) 0.07 0.01 −0.06 High school 807 (21) 105 (20) 379 (23) 323 (20) 0.08 0.01 −0.07 Some college 574 (15) 77 (15) 268 (16) 229 (14) 0.05 −0.01 −0.05 Completed college 538 (14) 77 (15) 222 (13) 239 (15) −0.03 0.01 0.04 Graduate school 322 (9) 36 (7) 127 (8) 159 (10) 0.04 0.11 0.08 Unknown 1 (<1) 0 (0) 1 (<1) 0 (0) 0.03 0.00 −0.03 Time from the first observed diagnosis to first MM LOT, days Mean (SD) NR 149.24 (281.12) 168.18 (296.95) 129.83 (252.06) 0.07 −0.07 −0.14 Median NR 29.5 33.0 28.0 – – – NCI Comorbidity Index Score Mean (SD) NR 1.08 (1.60) 1.21 (1.69) 0.94 (1.47) 0.08 −0.09 −0.18 Median 0.0 0.0 0.0 0.0 – – – NCI categories, n (%) 0 2185 (58) 304 (57) 886 (54) 995 (62) −0.07 0.10 0.17 1 to < 2 889 (24) 135 (25) 412 (25) 342 (21) −0.01 −0.10 −0.09 2 to < 3 234 (6) 25 (5) 112 (7) 97 (6) 0.09 0.06 −0.03 ≥3 470 (12) 66 (12) 237 (14) 167 (10) 0.06 −0.06 −0.12 Patients who participated in a clinical trial, n (%) 314 (8) 45 (8) 100 (6) 169 (11) −0.09 0.07 0.16 *No patients were covered by Medicaid. † Commercially managed Medicare refers to Medicare Part C. ‡ Experian-linked data. LOT: line of therapy; MM: multiple myeloma; NCI: National Cancer Institute; NR: not reported; SD: standard deviation; SMD: standard mean difference. Table 2. Comorbidities overall and across cohorts defined by care setting of treatment. Overall N = 3778 Academic only cohort N = 530 Community only cohort N = 1647 Mixed cohort N = 1601 SMD (community – academic) SMD (mixed – academic) SMD (mixed- community) Comorbidities, n (%) Immunosuppressive disorders 3764 (>99) 528 (>99) 1638 (99) 1598 (>99) −0.02 0.04 0.06 Hematologic complications 2426 (64) 323 (61) 1097 (67) 1006 (63) 0.12 0.04 −0.08 Anemia 2338 (62) 304 (57) 1053 (64) 981 (61) 0.13 0.08 −0.06 Hypertension 2188 (58) 276 (52) 1031 (63) 881 (55) 0.21 0.06 −0.15 Infections (overall) 1204 (32) 154 (29) 514 (31) 536 (33) 0.05 0.10 0.05 Diabetes 782 (21) 92 (17) 396 (24) 294 (18) 0.17 0.03 −0.14 Liver/gallbladder/pancreatic disease 525 (14) 84 (16) 218 (13) 223 (14) −0.07 −0.05 0.02 Chronic kidney disease 551 (15) 84 (16) 271 (16) 196 (12) 0.02 −0.10 −0.12 Renal failure/dialyses 307 (8) 47 (9) 157 (10) 103 (6) 0.02 −0.09 −0.11 Cardiovascular complications 654 (17) 84 (16) 308 (19) 262 (16) 0.08 0.01 −0.06 Thrombocytopenia 441 (12) 66 (12) 202 (12) 173 (11) −0.01 −0.05 −0.05 Ischemic heart disease 498 (13) 57 (11) 236 (14) 205 (13) 0.11 0.06 −0.04 Upper respiratory tract infection 421 (11) 53 (10) 172 (10) 196 (12) 0.01 0.07 0.06 Depression 402 (11) 52 (10) 180 (11) 170 (11) 0.04 0.03 −0.01 Pneumonia 309 (8) 49 (9) 137 (8) 123 (8) −0.03 −0.06 −0.02 Neutropenia 215 (6) 45 (8) 84 (5) 86 (5) −0.14 −0.12 0.01 Leukopenia 215 (6) 45 (8) 84 (5) 86 (5) −0.14 −0.12 0.01 Congestive heart failure 306 (8) 42 (8) 162 (10) 102 (6) 0.07 −0.06 −0.13 Stroke 235 (6) 40 (8) 122 (7) 73 (5) −0.01 −0.13 −0.12 Venous thromboembolism 198 (5) 35 (7) 95 (6) 68 (4) −0.03 −0.10 −0.07 Urinary tract infection 289 (8) 28 (5) 124 (8) 137 (9) 0.09 0.13 0.04 Skin and soft tissue infection 199 (5) 24 (5) 94 (6) 81 (5) 0.05 0.02 −0.03 Peripheral vascular disease 179 (5) 22 (4) 98 (6) 59 (4) 0.08 −0.02 −0.11 Reported are comorbidities in ≥ 5% of patients in any cohort. SMD: standard mean difference.

Patient cohorts by care setting of MM treatment

Of the 3778 patients, 530 (14.0%) received all MM treatment from the academic setting (academic only cohort), 1647 (43.6%) from the community setting (community only cohort), and 1601 (42%) from both settings (mixed cohort) based on the care setting of treatment claims (Supplementary Figure S2). The mean follow-up was 650 days (standard deviation [SD] ±400 days) in the academic only cohort, 657 days (SD ±397 days) in the community only cohort, and 742 days (SD ± 405) in the mixed cohort. The community cohort had the highest proportion of patients in the 65+ age group (36% versus 21% for academic [SMD 0.35] and versus 22% for mixed [SMD 0.31]), which corresponded to a higher proportion of patients with Medicare (19% versus 5% for academic [SMD 0.46] and versus 9% for mixed [SMD 0.30]) ( Table 1 ). Most patients across cohorts were male (59% in academic, 58% in community, and 59% in mixed) and commercially insured (95%, 81%, and 91%, respectively). The mean NCI comorbidity index score was 1.08 (SD ± 1.60) in the academic cohort, 1.21 (SD ± 1.69) in the community cohort, and 0.94 (SD ± 1.47) in the mixed cohort; patients in the community cohort had a higher prevalence of most comorbidities, with meaningful differences observed versus academic and mixed cohorts for rates of hypertension (63% community, 52% academic, and 55% mixed) and diabetes (24%, 17%, and 18%, respectively) ( Table 2 ). The academic cohort had a higher proportion of patients located in the Northeast geographic region (28% versus 12% for community [SMD 0.41] and versus 20% for mixed [SMD 0.18]). The community cohort had a lower proportion of patients who participated in a clinical trial (6% versus 8% for academic [SMD 0.09] and versus 11% for mixed [SMD 0.16]).

As evaluated using Experian linked data (212 [40%] patients in academic only, 554 [34%] in community only, and 579 [36%] in mixed were not linked to Experian), a higher proportion of patients in the community only versus academic only cohorts were Hispanic (81/1647 [5%] versus 15/530 [3%] patients; SMD 0.11) and had an annual income <$25,000 (129/1647 [8%] versus 28/530 [5%]; SMD 0.10). The community only cohort had a higher proportion that did not complete college (743/1647 [45%]) versus academic only (205/530 [39%]; SMD 0.13) and versus mixed (624/1601 [39%]; SMD 0.12).

Mixed cohort: shifts in care

For patients receiving MM treatment in both academic and community care settings (mixed cohort), the overall mean duration of treatment in an academic setting was 4.6 months (SD ± 6.9), and the mean duration of treatment in a community setting was 10.6 months (SD ± 11.8). Most of the 1,601 patients in the mixed cohort initially received MM treatment in a community setting ( n = 940; 58.7%), and 867 of the 940 patients (92.2%) spent a median of 4.3 months in this setting before shifting to an academic treatment setting. After a median of 0.5 months in the academic setting, 682 of the 867 patients (78.7%) then shifted back to a community setting ( Figure 1 ). Stem cell transplant (SCT) was observed in almost half of patients (423 of 867, 48.8%) after shifting from a community setting to an academic setting, a marked increase from the 11 (1.3%) patients who received SCT prior to the shift. Figure 1. Shifts in care in the mixed care cohort. This figure shows the treatment journey of patients in the mixed cohort, starting with the care setting where they received LOT1, followed by the median time to their first care shift and setting, and then median time to their second shift and setting. LOT: line of therapy; mo: months.

Of the 1601 patients in the mixed cohort, 385 (24.0%) were initially treated in an academic setting, most of whom (306/385, 79.5%) spent a median of 2.6 months in this setting before shifting to a community setting. Then 252 of 306 (82.4%) shifted back to an academic setting after a median of 3.6 months ( Figure 1 ). SCT was observed in 26 of the 306 patients (8.5%) before the shift from academic to community setting and in 17 (5.6%) patients after the shift to the community setting.

Treatment patterns by care setting

For all 3778 patients, there were over 1.75 million claims during a median post-index follow-up of 595 days (range 180–1733). Patients generally received most of their MM treatments in the community setting: 3387 (89.7%) patients had treatment claims in community, 2148 (56.9%) in the academic setting, and 1492 (39.5%) had treatment claims from physicians with dual affiliations.

MM-related claims indicated that most patients received only LOT1 during the post-index follow-up period. In the overall study population, 1965 patients (52.0%) had received only LOT1, 992 (26.3%) received LOT2, and 821 (21.7%) received ≥ 3 LOT. Overall, 48.3% of patients received at least part of their LOT1 in the academic setting, 84.9% in the community setting, and 32.6% from physicians with dual affiliations. These data indicate shifts between academic and community settings which occurred within a LOT for some patients. From LOT2 to LOT5+, the proportions of patients with treatment claims in academic (20.0% at LOT2 and 1.8% at LOT5+) and community settings (38.7% at LOT2 and 3.0% at LOT5+) were generally similar, although the number of patients decreased by LOT due to the duration or loss of follow-up, or death (data will be made available upon request).

Among 3778 patients, 810 (21.4%) had an inpatient SCT claim in the academic setting, 277 (7.3%) in the community setting, and 12 (0.3%) from physicians with dual affiliations. SCT was part of LOT1 for 606 (16.0%), 190 (5.0%), and 7 patients (0.2%), respectively.

Triplet therapy was the most common regimen in both the academic and the community settings, with 37.0% and 40.3% of patients, respectively, having claims for triplet combinations in these care settings. Triplet therapy was relatively common across all LOTs. The combination of bortezomib, lenalidomide, and dexamethasone (VRd) was the most common regimen prescribed in academic and community settings overall (24.3% and 28.0%, respectively) (Supplementary Figure S3) and for LOT1 (19.5% and 25.4%). Quadruplet therapy was also frequently used, particularly in LOT1 (34.1% in academic and 26.2% in community settings). Doublet and monotherapy were used less frequently, with increased use among patients in later LOT. Doublet therapy was more prevalent in the community setting than in the academic setting. In later LOT, doublet therapy was more prevalent than quadruplet in the community setting (data will be made available upon request).

Of the 2148 patients who had any claim in an academic setting, most patients received a PI (56.3%) and a steroid (52.5%) during follow-up, while 22.3% received an immunomodulatory drug and 25.1% an anti-CD38 agent ( Figure 2 ). For the 3387 patients with claims in the community setting, 85.0% received a steroid, 75.1% an immunomodulatory drug, 67.1% a PI, and 27.1% an anti-CD38 agent. Anti-SLAMF7 mAbs were used infrequently in both academic (1.5%) and community (1.6%) settings. Among the 1492 patients with claims from physicians with dual affiliations, 75.1% were prescribed an immunomodulatory drug, 64.8% a steroid, 17.6% a PI, and 5.1% an anti-CD38 agent ( Figure 2 ). Figure 2. Percentage of patients with claims by MM therapeutic classes from the academic setting, community setting, and physicians with dual affiliations (A), and retreatment with same drug by drug class (B). In panel B, Ns are patients with at least 1 retreatment claim among those who received 2+ LOTs. CD: cluster of differentiation; LOT: line of therapy; MM: multiple myeloma; PI: proteasome inhibitor; SLAMF7: signaling lymphocytic activation molecule family member 7.

By LOT, PIs (50.0–59.4%) and steroids (45.6–68.3%) were commonly prescribed across LOT1 to LOT5 in the academic settings, and prescriptions of anti-CD38 agents increased from LOT1 (10.3%) to later LOT (34.7–44.4% from LOT2 through LOT5). In claims from the community setting, steroids (68.0–79.7%), immunomodulatory drugs (54.0–66.8%), and PIs (45.5–65.3%) were commonly prescribed across LOT1 to LOT4, and there was also increased use of anti-CD38 agents from LOT1 (10.4%) to later LOT (25.0–38.4% from LOT2 through LOT5) (data will be made available upon request).

Retreatment

Overall, claims data indicated that 1594 patients (57.9%) had retreatment with the same drug among 2751 patients with ≥ 2 LOT—387/756 (51.2%) at the academic setting, 944/1463 (64.5%) at the community setting, and 263/532 (49.4%) from physicians with dual affiliations. Among patients with retreatment claims in the academic setting ( N = 387), the most common drugs used for retreatment were PIs (72.4%), anti-CD38 mAbs (30.2%), and immunomodulatory drugs (19.1%), whereas immunomodulatory drugs (62.4%) and PIs (50.1%) were favored in the community setting ( N = 944) ( Figure 2 and Supplementary Table S2).

Patient cohorts by care setting of MM treatment: lines of therapy and treatment durations

The mean time from earliest reported MM diagnosis to the start of the first MM LOT (index date) was 149.2 days (SD ± 281.1; median 29.5 days) in the academic cohort, 168.2 days (SD ± 297.0; median 33.0 days) in the community cohort, and 129.8 days (SD ± 252.1; median 28.0 days) in the mixed cohort ( Table 1 ). Most patients in the academic (58.3%) and community (56.7%) cohorts had only received LOT1 during the study period, while the mixed cohort had the highest proportion with 5+ LOT (6.7%) ( Figure 3 ). The mean total number of LOT was 1.7 (SD ± 1.0) in the academic and community cohorts, and 2.1 (SD ± 1.4) in the mixed cohort. SCT was received by 178 (33.6%) patients in the academic cohort and 252 (15.3%) in the community cohort, with the highest proportion in the mixed cohort (972 [60.7%]). Figure 3. Care setting cohorts, lines of therapy and duration of therapy: (A) total number of therapy lines and (B) Kaplan–Meier-estimated treatment duration by line of therapy. CI: confidence interval; LOT: line of therapy; No.: number.

For the 1601 patients in the mixed cohort, a total of 121,279 MM-related treatment claims were identified during the post-index period. Almost half (49.1%) of claims were from the community setting, 41.9% were from the academic setting, and 9.0% were from physicians with dual affiliations. The proportion of claims was consistently higher in the community setting across LOT and increased with LOT advancement (Supplementary Figure S4). Of the 972 mixed-cohort patients who received SCT, 65.3% received their SCT procedure in an academic setting, while 53.0% and 71.2% received induction and maintenance, respectively, in the community setting.

The median duration of treatment from the start of LOT1 to the end of follow-up was similar between the academic and community cohorts (19.0 months [95% CI 16.3–21.3] for academic and 20.7 months [95% CI 18.8–21.9] for community), and longest in the mixed cohort (30.9 months [95% CI 29.3–32.5]). The median duration of LOT1 was 7.0 months (95% CI 6.1–7.8) in the academic cohort, 7.6 months (95% CI 7.0–8.3) in the community cohort, and 7.7 months (95% CI 7.0–8.4) in the mixed cohort. Generally, median duration of LOT decreased with LOT advancement across all cohorts ( Figure 3 and Supplementary Figure S5); median duration of LOT2 was 4.6 months for the academic cohort, 5.6 months for the community cohort, and 5.4 months for the mixed cohort. For 221, 714, and 878 patients who received LOT2 in the academic, community, and mixed cohorts, respectively, median LOT1 TTNT (time from start of the first to start of the second LOT) was 6.0, 6.6, and 6.8 months. Consistent with duration of LOT, median TTNT generally decreased with each LOT advancement across all cohorts ( Figure 4 and Supplementary Figure S6). Figure 4. Care setting cohorts, time to next line of therapy: (a) Kaplan–Meier-estimated time to next line of therapy in patients who received at least 2 lines, and (b) Kaplan–Meier-estimated time from first to second line of therapy. CI: confidence interval; LOT: line of therapy.

MM-related HCRU by care setting

Generally, there were more MM-related claims in the community setting than in the academic setting (Supplementary Table S3). SCT claims were more common in the academic setting, while there was a high rate of outpatient prescription claims from the community setting. For the overall cohort, inpatient hospital claims were submitted for 1611 patients (42.6%) from the academic setting and 1003 patients (26.6%) from the community setting and 15 patients (0.4%) from physicians with dual affiliations. Claims for SCT inpatient hospital visits were submitted for 810 patients (21.4%) from the academic setting, for 277 patients (7.3%) from the community setting, and for 12 patients (0.3%) from physicians with dual affiliations. In the academic setting, inpatient visits were more common in LOT1 (1215/3778; 32.2% of patients) compared with later LOT (21.0–23.2% for LOT2 through LOT5), driven by first-line SCT claims (606/3778; 16.0%). Claims for outpatient visits were submitted for 83.8% of patients from the academic setting and 96.5% of patients from the community setting. Claims for physician office visits were less frequent from the academic setting (57.8% of patients) than from the community setting (92.4%).

Overall, the rate of patients with claims for MM-related prescriptions (including pharmacy prescriptions and in-office drug administration) written in the academic setting was lower (63.9% of patients) than those written in the community setting (92.1%) ( Figure 5 ); 664 patients (17.6%) had MM-related claims for pharmacy prescriptions from the academic setting, whereas 3158 patients (83.6%) had claims from the community setting. The rate of patients with claims for MM-related in-office drug administration was similar for academic (60.9%) and community settings (63.2%). Figure 5. Percentage of patients with MM-related HCRU (a) and costs per claim (b) from academic and community settings ( N = 3778). *SCT inpatient visit claims comprise a subset of overall inpatient visit claims and are defined as inpatient hospitalization with an SCT procedure observed during the stay. † Physician office visit claims comprise a subset of outpatient visit claims. ‡ In-office drug administration claims comprise a subset of prescription claims and are defined as unique health-care common procedure coding system (HCPCS) claims. § Pharmacy prescription claims comprise a subset of prescription claims and are defined as unique national drug codes (NDC) claims. ED: emergency department; HCRU: health-care resource utilization; MM: multiple myeloma; SCT: stem cell transplantation; USD: United States dollar.

MM-related costs by care setting

Mean costs per visit were higher in the academic setting than in the community setting across most categories, although costs of prescriptions originating from the community setting were higher ( Figure 5 and Supplementary Table S4). Costs in both academic and community settings were largely driven by inpatient hospital visits, particularly for SCT, followed by prescription costs. The mean MM-related inpatient costs per visit were $83,324 and $48,422 for academic and community settings, respectively. In the community setting, costs for SCT inpatients visits were substantial (mean, $124,309) but lower than those estimated for the academic setting (mean, $138,962). The mean MM-related ED costs were higher in the academic setting ($1915) than in the community setting ($1123), and mean MM-related outpatient visit costs at the academic setting ($307) were more than two times higher than in the community setting ($136). By LOT, mean costs remained higher in the academic setting across each LOT for inpatient visits, SCT, and ED costs (Supplementary Figure S7). Outpatient costs and non-physician office visit costs were higher in the academic setting from LOT1–LOT4, but community outpatient costs increased markedly at LOT5. Prescription costs were highest in the community setting from LOT1–LOT4 but became higher in the academic setting at LOT5.

Discussion

Patients with MM require a comprehensive therapeutic strategy, as most patients experience multiple relapses and require sequential LOT [ 4 , 22 ]. At the cohort level, this observational, retrospective study described patient populations in the academic and community care settings with overlapping but also distinct characteristics, which could help establish patient profiles and inform therapeutic decisions, patient support programs, and policy. Claim-level analyses revealed that patients received the majority of MM-related care, including prescriptions, from the community setting, while the academic setting appeared to be an important resource for SCT. Claims data indicated the potential for fractured care, with patients likely shifting between academic and community settings, sometimes within a LOT. Access to SCT appeared to be a primary reason for shifts in care, as further demonstrated in the mixed cohort, where care shifts were generally from community (for induction therapy) to academic for SCT and then back to a community setting (for maintenance therapy).

Patients in the community cohort were older, had less education and lower income, and had higher rates of most comorbidities. These are generally consistent with other reports in patients with MM and other cancer types [ 14 , 23 , 24 ]. Demographic and socioeconomic differences between the two settings may be explained in part by patients’ ability and willingness to travel to receive SCT and novel agents at an academic setting. Patients with lower income and those with Medicare have been shown to have a lower likelihood of receiving SCT [ 25 ]; the community cohort was comprised of patients with lower income and higher rates of Medicare, and the rate of SCT was less than half that of the academic cohort (15.3% versus 33.6%). Consistent with previous analyses of cancer trials, there was a low rate of clinical trial participation overall, but the rate was lowest in the community cohort [ 12 ]. Given that clinical trials are generally conducted in academic settings, patients who are treated in community settings, particularly those not in close proximity to academic centers, may have limited access to trials. Reasons for non-enrollment in clinical trials include travel distance, financial concerns, and insurance denial, which may disproportionately affect patients treated in community settings [ 12 ]. As patients who participate in MM clinical trials have shown better outcomes [ 26 , 27 ], there is a need to improve access to patient support programs (e.g., financial and transportation assistance, and care coordination) and increase clinical trial access (such as broadening eligibility requirements, expanding insurance coverage, and involving community physicians), as this will help to address disparities that exist in clinical trials and ensure appropriate representation of the broader MM population.

The analysis reported here captured a relatively high proportion of patients early in their treatment journey, with 52.0% having received only LOT1 at the time of the post-index data cutoff. Similar MM treatment trends were observed in the academic and community settings. The use of quadruplet and triplet regimens was common, particularly in the first few LOT. In the past, the predominant frontline MM treatments mainly comprised doublet and triplet therapies [ 8 ]. However, by 2019, the majority of frontline regimens transitioned to triplet and quadruplet therapies, with increased upfront use of lenalidomide and daratumumab [ 28 , 29 ].

The claims data showed that retreatment with the same drug was relatively common in both academic and community settings. Retreatment with an immunomodulatory drug in the community setting was more than double that in the academic setting. With the introduction of triplet and quadruplet regimens into early therapy lines, which was common in both settings in this study, retreatment may become more frequent [ 30 ]. The use of effective multidrug regimens, such as those that include daratumumab and lenalidomide, in early lines limits availability of subsequent therapies with distinct mechanisms of action that patients have not been previously exposed or have become refractory to [ 30–33 ]. Use of anti-CD38 agents was relatively low in LOT1 in the current analysis, likely due to its relatively recent approval in frontline regimens [ 34 ], with higher rates of claims observed in LOT2 and beyond. Previous studies in RRMM demonstrated that the retreatment with immunomodulatory drugs, anti-CD38 agents, and PIs resulted in suboptimal outcomes [ 30 , 33 , 35 , 36 ], highlighting the continued need for agents with novel mechanisms of action to limit retreatment.

Despite the advanced age and higher rate of comorbidities in patients treated in community versus academic setting cohorts, these patients had a similar median duration of treatment overall and in each LOT, and TTNT for each LOT. Patients in the mixed cohort spent most of their time in a community setting, and most initiated treatment in the community setting, briefly shifted to an academic setting, and then returned to a community setting. The brief shift to an academic setting was likely to receive a SCT, as rates of SCT increased from 1.3% to 48.8% for patients who initially started their care in community setting and shifted to academic care. Patients in this mixed cohort received a higher mean number of LOT versus the academic and community cohorts. Although the mixed cohort had the highest rate of SCT, which has been associated with improved outcomes in MM, treatment durations and TTNT were similar to the academic and community cohorts, potentially due to treatment advances improving outcomes in transplant-ineligible patients [ 37 ]. While patients treated in academic centers have generally had improved OS versus community-treated patients [ 8 , 14 , 17 , 38 ], no significant difference in TTNT has been reported between the settings [ 8 ]. In all cohorts, there was a decline in duration of LOT and TTNT as therapy lines advanced, consistent with previous reports [ 39 ]. The reduction in treatment durations as LOT advanced may be related to prevalence of triplet and quadruplet regimens in early LOTs.

Use of SCT was low among the academic and community cohorts (15.3% community, 33.6% academic), considering its role as a standard frontline treatment in eligible patients. However, this is in line with real-world studies which have shown that less than half of eligible patients receive SCT [ 40–43 ]. Studies have shown that White race, younger age, higher income, more education, and treatment at an academic facility are associated with higher probability of receiving a SCT [ 40 , 44 ]. This is aligned with the characteristics observed in the academic cohort of this study, where the rate of SCT was more than double that of the community cohort. This further highlights a need for improved care access in the community setting.

There was a lower rate of overall prescription claims from the academic setting than from the community setting. Prescriptions for PIs and steroids were predominant in the academic setting, while prescriptions for immunomodulatory drugs were relatively infrequent. In the community setting, patients were frequently prescribed steroids and immunomodulatory drugs. This likely reflects the prevalence of care and treatment in the community setting, even within a LOT. The cohort analysis showed that it was relatively common for patients with SCT to receive induction and maintenance therapy in the community setting. Further, the older age and higher comorbidity burden of patients in the community only cohort compared to those in the academic only cohort could potentially contribute to the increased proportion of MM-related prescription claims in the community versus academic care settings.

Differences in MM-related costs between academic and community care settings, particularly the cost for inpatient hospital visits and prescriptions, are likely related to differences in HCRU. Claims for inpatient hospital visits, especially for SCT, were higher in the academic setting than in the community setting, while the number of pharmacy prescriptions were lower in the academic setting. Among all categories, inpatient visits had the highest MM-related cost in both academic and community settings, and these costs were highest in the academic setting, possibly driven by more expensive procedures such as SCTs. Other studies suggest differences in cost could be driven by greater use of supportive care (e.g., prophylactic antivirals) at academic centers [ 45 ] and more comprehensive testing to characterize and monitor the disease [ 46 ]. Outpatient and non-physician office visit costs were consistently higher in the academic setting through LOT4, but these costs became higher in the community setting at LOT5; similarly, prescription costs were consistently higher in the community setting through LOT4 but became higher in the academic setting at LOT5. These increases in cost at LOT5 may be related to costs associated with more advanced disease, including intensive care services [ 47 ].

RRMM treatment has advanced with the development and approval of B-cell maturation antigen (BCMA)- and G-protein – coupled receptor class C group 5 member D (GPRC5D)-targeting therapies, and these agents are becoming available to patients in earlier LOTs [ 48 , 49 ]. CAR-T therapies targeting BCMA are highly active and have recently been approved for second-line treatment [ 50 ]. However, it is important to recognize that CAR-T treatment has complex logistics and high costs and currently is only available at specialized centers, which will likely require shifts in care [ 51 , 52 ]. BCMA-targeting bispecific antibodies are approved for later LOTs in RRMM and are being assessed in earlier LOTs [ 53 ]. In this study, there were a limited number of patients who received novel therapies, such as bispecific treatments, since the study period was before their approval [ 54 , 55 ]. The BCMA-targeting antibody-drug conjugate belantamab mafodotin is being evaluated in combination regimens for early LOTs and has shown progression-free survival (PFS) benefits in phase 3 RRMM studies [ 56 , 57 ]. Future studies should assess accessibility to these and other novel treatments and their impact on patient outcomes and costs in different care settings, especially in the community setting. Some novel therapies, such as CAR-T and bispecifics, require inpatient hospitalization.

This retrospective study has limitations related to the nature of observational research using administrative claims data, as the claims are used for the management, billing, and/or reimbursement of patient care and not for research purposes. Database history is not exhaustive, therefore there is potential for missing data and misidentification of the first LOT. As a result, total LOT and treatment duration might be underestimated. In addition, participation in clinical trials may have been underreported in administrative claims, and the follow-up time captured most patients in their LOT1, with limited data for later LOTs. PharMetrics® Plus comprises only commercially insured patients in the US (as well as commercial Medicare and Medicaid patients); thus, while these data are generalizable to similar commercially insured patients, they may not be generalizable to patients who are uninsured or who are covered only by traditional fee-for-service Medicare. Further, PharMetrics® Plus underrepresents people greater than 65 years of age as most plans come from large employers and only commercially managed Medicare, and limited data were available for certain patient characteristics in the Experian database. Lastly, patients with longer follow-up have more opportunity to switch to a different treatment setting than patients with shorter follow-up; notably, the mixed setting had the longest follow-up among the cohorts.

Strengths of this study include the large sample size that allowed for linkage to OneKey™ and resulted in cohorts of appropriate size to conduct the analyses. In addition, the linkage of claims data to the OneKey™ database made it possible to define care setting cohorts, which are usually not available in data sources. Defining the care setting cohorts allowed for assessment of shifts in care, which have not been well-described previously. The databases used in this study covered the majority of US hospitals and doctors, indicating that the data are representative of the US MM patient population with commercial health insurance.

Future research is warranted to further characterize the effect of care setting on patients with MM. While our study assessed proxies of treatment outcomes (treatment duration and TTNT), progression-free survival and overall survival by setting should be considered, along with the effect of prognostic factors on these outcomes. Future analyses should also include adjustments for patient demographics and clinical characteristics.

Conclusion

This study identified important differences among patients with MM based on treatment setting, including advanced age, higher comorbidity burden, lower income, and less education for patients treated in a community setting than for those treated in an academic setting. These findings highlight a need for enhanced patient support at community centers, where the majority of care occurs. More research is needed to further characterize the relationship of prognostic factors (e.g., Eastern Cooperative Oncology Group performance status, cancer stage, cytogenetic risk) and care setting with treatment outcomes and overall survival. Specialized care, such as SCT, is more accessible in the academic setting, and likely contributes to shifts in care. The relatively high use of quadruplet and triplet regimens in the frontline setting likely contributes to the use of retreatment with the same drug or drug classes in early LOTs for RRMM regardless of care setting. Additionally, the observed low rate of clinical trial participation, particularly from patients in the community setting, indicates a need for strategies to increase clinical trial enrollment; increased patient representation will allow better evaluation of treatment in a more generalizable MM population. These findings highlight the complexity and challenges of MM care and the need for therapies with novel mechanisms of action in early LOTs of RRMM that are accessible to both academic and community clinicians, without adding significant financial burden to patients and health-care systems.

Supplementary Material

Supplemental Material

Article highlights

Although treatment options for multiple myeloma (MM) have increased, differences may exist based on the care setting where patients receive their treatments. This retrospective cohort study utilized linked PharMetrics® Plus and OneKey™ databases to evaluate MM patient characteristics and treatment durations in cohorts defined by the care setting of treatment (academic only, community only, or mixed) and shifts in care (mixed setting). In addition, MM treatment patterns, health-care resource utilization, and costs of care (e.g., treatment, office visits, hospitalization) were evaluated by care setting (academic or community) utilizing administrative claims data. Patients treated only in a community setting were older, had more comorbidities, lower income and less education, and less clinical trial participation than those treated only in an academic setting. Most patients in the mixed cohort initiated their first LOT in the community setting, and after a brief shift to an academic setting, returned to community care. There was a large increase in the rate of SCT upon this shift from community to academic care, suggesting that SCT was a key reason for the observed shift in care. Based on claims data, patients received most of their MM care, including treatments, in the community setting versus the academic setting. Triplet therapies were the most common regimens in both the academic and community settings and were used frequently across all lines of therapy. Most patients were prescribed a proteasome inhibitor (PI), steroid, anti-CD38 agent and/or an immunomodulatory drug in the academic setting, whereas most patients were prescribed a steroid, an immunomodulatory drug, PI and/or anti-CD38 agent in the community setting. Retreatment was common in both community and academic settings; PIs and anti-CD38 agents were the most common drug classes for retreatment in the academic setting, while immunomodulatory drugs and PIs were favored in the community setting. Patients in the academic only, community only, and mixed cohorts remained in each line of therapy (LOT) for similar periods of time and had similar times to next LOT. Costs for inpatient visits were higher in the academic setting than in the community setting, likely driven by greater use of SCT, whereas costs for prescriptions were higher in the community setting. Given the advanced age and higher rates of comorbidities in patients treated in community settings, there is a need for enhanced patient support in the community and improved clinical trial access to ensure representation of these patients. In addition, the findings suggest the need for new therapies with novel mechanisms of action that are accessible to patients treated in both academic and community care settings.

Declaration of interest

Natalie Boytsov is an employee of and holds financial equities in GSK; Catherine B. McGuiness is an employee of IQVIA; Zifan Zhou is an employee of IQVIA; Tianyao Huo is an employee of IQVIA; Kathleen Montgomery is an employee of and holds financial equities in GSK; Nirali Kotowsky is a former employee of and held financial equities in GSK; Chi-Chang Chen is an employee of IQVIA. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Writing disclosure

Editorial support (in the form of writing assistance, including preparation of the draft manuscript under the direction and guidance of the authors, collating and incorporating authors’ comments for each draft, assembling tables and figures, grammatical editing and referencing) was provided by Priyanka Vaz, PhD, and Alexus Rivas-John, PharmD, at Fishawack Indicia Ltd, part of Avalere Health, and was funded by GSK.

Author contributions

All authors contributed to the conception or design of this research, analysis and interpretation of the data, drafting of the manuscript, or revising it critically for important intellectual content. All authors provided final approval of the version to be published and agree to be accountable for all aspects of the work.

Data availability statement

The data reported in this manuscript are from the IQVIA PharMetrics® Plus database. The patient-level dataset cannot be shared publicly; however, the manuscript reports all relevant data that supports the research objectives and conclusions.

Ethical disclosure

This study complied with all applicable laws regarding patient privacy. No direct patient contact or primary collection of individual human patient data occurred. Study results are presented as aggregate analyses that omit patient identification. Informed consent and ethics committee or institutional review board (IRB) approval were not required. IQVIA provided consent to utilize the PharMetrics® Plus database.

For further information on data access, please contact IQVIA.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14796694.2025.2504318

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