Keegan, Theresa H.M.

Abstract In this secondary analysis of Hispanic adolescents and young adults (AYA) with acute lymphoblastic leukemia (ALL) treated on Cancer and Leukemia Group B (CALGB) 10403, we evaluated outcomes and geographic enrollment patterns relative to US population data. We used demographic, clinical, and survival data on AYAs enrolled on CALGB 10403 (N = 295, 2007-2012). Surveillance, Epidemiology, and End Results registries provided overall survival (OS) for US AYA ALL by ethnicity/race. North American Association of Cancer Registries provided AYA ALL incidence overall and proportion among Hispanics by US state. Of AYAs enrolled on CALGB 10403, 263 (89%) reported ethnicity/race: 45 (17%) Hispanic, 172 (65%) non-Hispanic White (NHW), 25 (10%) non-Hispanic Black (NHB), and 21 (8%) other. Compared with NHWs, Hispanic and NHB patients had lower household income, and Hispanic patients were more likely to harbor high-risk CRLF2 aberrations. Relative to US estimates, where Hispanic patients represented 46% of newly diagnosed AYA ALL patients and experienced inferior OS compared with NHW (P < .001), Hispanic AYAs on CALGB 10403 did as well as NHW patients (3 year OS, 75% vs 74%; P = NS). Hispanic patients also had higher rates of protocol completion (P = .05). Enrollments on CALGB 10403 differed relative to the distribution of Hispanic AYA ALL in the United States: enrollment was highest in the Midwest; t and only 15% of enrollees were from states with a high proportion of Hispanic AYA ALL patients. In summary, Hispanic patients treated on CALGB 10403 did as well as NHWs and better than population estimates. Geographical misalignment between trial sites and disease epidemiology may partially explain the lower-than-expected enrollment of Hispanic AYA ALL patients.

Abstract Introduction According to population-based Surveillance, Epidemiology and End Results (SEER) cancer registry data, approximately 40% of adolescents and young adults (AYA) with acute lymphoblastic leukemia (ALL) in the United States (U.S.) are Hispanic and 7% are Black and both Hispanic and Black patients have significantly inferior outcomes relative to non-Hispanic Whites (NHW). CALGB 10403, a prospective Phase II clinical trial conducted by the U.S. Intergroup, demonstrated the feasibility of delivering a pediatric-inspired ALL regimen to newly diagnosed AYA ALL patients and found this approach to be superior to historical adult regimens (Stock et al. Blood 2019). In the current analysis, we evaluate enrollment patterns of Hispanic and Black AYAs on CALGB 10403 and compare survival relative to SEER estimates. Methods Demographics on AYAs (18-40 yrs) enrolled on CALGB 10403 (N=295 from 2007-2012) were supplemented with patient-reported education and socioeconomic status (SES) information. Data from the North American Association of Cancer Registries (NAACCR; 2013-2017) were used to evaluate U.S. country-wide ALL incidence (20-49 yrs) overall and among Hispanics, reported per U.S. state. SEER registries (2008-2012) provided racial/ethnic distribution and overall survival (OS) of AYA ALL (15-39 yrs). The distribution of OS was estimated using the Kaplan-Meier method and compared across racial/ethnic groups using log-rank tests. Results Relative to the U.S. AYA ALL population, CALGB 10403 included proportionally fewer Hispanics (41.7% vs. 16.3%, P < 0.001); the distribution of blacks was similar (6.4% vs. 8.5%, P = 0.174). Demographics and ALL characteristics among CALGB 10403 enrollees demonstrated no significant differences in age, sex, cytogenetics, or BMI by race/ethnicity; however, Black AYAs were more likely to have T-ALL, and Hispanic patients were more likely to have Ph-like B-ALL and rearrangements in CRLF2. Hispanic and Black patients reported lower household yearly income, and Black patients had less educational attainment. In order to explore reasons for disproportionately low Hispanic enrollment on CALGB 10403, we calculated the proportion of Hispanic AYAs with ALL relative to the AYA ALL incidence across U.S. states using NAACCR data and compared this with the geographical distribution of CALGB 10403 enrollments. The incidence of AYA ALL across U.S. states is represented in Fig 1A and the proportion of Hispanic AYA ALL patients in Fig 1B. The states with highest proportion of Hispanic patients included CA, TX, and NM, followed by AZ, CO, FL, and NJ. Although CALGB 10403 enrolled patients in 31 U.S. states, the trial did not open in TX or FL. The enrollments numbers were highest across the Mid-Western U.S., with only 47/295 (15.9%) of enrollments coming from the seven states with a high proportion of Hispanic AYA ALL patients (Fig 1C). The 3-yr event-free survival (EFS) and OS for the total CALGB 10403 cohort were 59.1% (53.1%, 65.75%) and 73.5% (68.1%, 79.4%), respectively. Per protocol completion of therapy was highest in Hispanics (75%), relative to Black (64%) and NHW patients (56%), P=0.049. Overall survival among CALGB 10403 participants differed significantly across race/ethnicity (Fig 2), with superior OS experienced by Hispanic patients and inferior OS by Black patients (P= 0.021). These clinical trial results differ from SEER estimates, where both Hispanic and Black patients experience worse OS relative to NHW (Fig 2). Conclusions This in-depth analysis of racial/ethnic enrollments and outcomes on CALGB 10403 uncovered findings that may translate across clinical trials beyond AYA ALL. Importantly, our data suggest that closer matching of trial site selection to geographical racial/ethnic disease incidence may improve minority enrollments on multi-center clinical trials. Relative to NHW, Hispanic patients had superior survival despite having higher rates of Ph-like ALL, indicating that clinical trial participation may mitigate racial/ethnic survival disparities seen in population-based data. Finally, we saw no improvement in trial outcomes among Black AYAs; a deeper understanding of the biological leukemia underpinnings and barriers to successful outcomes would aid future efforts at improving survival across racial/ethnic groups. Figure 1 Figure 1. Disclosures Muffly: Pfizer, Amgen, Jazz, Medexus, Pfizer: Consultancy; Astellas, Jasper, Adaptive, Baxalta: Research Funding; Adaptive: Honoraria, Other: fees for non-CME/CE services: , Research Funding. Advani: Abbvie: Research Funding; Macrogenics: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Glycomimetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Immunogen: Research Funding; Pfizer: Honoraria, Research Funding; OBI: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Luger: Syros: Honoraria; Agios: Honoraria; Daiichi Sankyo: Honoraria; Jazz Pharmaceuticals: Honoraria; Brystol Myers Squibb: Honoraria; Acceleron: Honoraria; Astellas: Honoraria; Pfizer: Honoraria; Onconova: Research Funding; Celgene: Research Funding; Biosight: Research Funding; Hoffman LaRoche: Research Funding; Kura: Research Funding. Tallman: NYU Grand Rounds: Honoraria; Syros: Membership on an entity's Board of Directors or advisory committees; Kura: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Biosight: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Orsenix: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Rafael Pharmaceuticals: Research Funding; Glycomimetics: Research Funding; Biosight: Research Funding; Orsenix: Research Funding; Abbvie: Research Funding; Mayo Clinic: Honoraria; UC DAVIS: Honoraria; Northwell Grand Rounds: Honoraria; NYU Grand Rounds: Honoraria; Danbury Hospital Tumor Board: Honoraria; Acute Leukemia Forum: Honoraria; Miami Leukemia Symposium: Honoraria; New Orleans Cancer Symposium: Honoraria; ASH: Honoraria; NCCN: Honoraria. Litzow: Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Pluristem: Research Funding; Actinium: Research Funding; Amgen: Research Funding; AbbVie: Research Funding; Astellas: Research Funding; Biosight: Other: Data monitoring committee. Foster: Macrogenics: Research Funding; Rafael Pharmaceuticals: Research Funding; Macrogenics: Consultancy; Daiichi Sankyo: Consultancy; Agios: Consultancy; Bellicum Pharmaceuticals: Research Funding. Larson: Gilead: Research Funding; Epizyme: Consultancy; Astellas: Consultancy, Research Funding; Rafael Pharmaceuticals: Research Funding; CVS/Caremark: Consultancy; Takeda: Research Funding; Novartis: Research Funding; Cellectis: Research Funding.

BACKGROUND The Patient‐Reported Outcomes Measurement Information System (PROMIS) was a National Institutes of Health‐funded initiative to develop measures of symptoms and function. Responsiveness is the degree to which a measure can detect underlying changes over time. The objective of the current study was to document the responsiveness of 8 PROMIS measures in a large, population‐based cancer cohort. METHODS The Measuring Your Health study recruited 2968 patients who were diagnosed with 1 of 7 cancers between 2010 and 2012 through 4 Surveillance, Epidemiology, and End Results registries. Participants completed a baseline survey (6‐13 months after diagnosis) and a 6‐month follow‐up survey. Changes in 8 PROMIS scores were compared with global ratings of transition, changes in performance status, and clinical events. RESULTS Measures were responsive to 6‐month declines and improvements in performance status with small to large effect sizes (ES) (Cohen d = 0.34‐0.71; P < .01). Mean changes and effect sizes were larger for participants who reported declines compared with those who reported improvements. Small‐to‐medium ES were observed in patients who reported being “a little” worse (d = 0.31‐0.56), and medium‐to‐large ES were observed in those who reported being “a lot” worse (d = 0.53‐0.72). Hospitalized participants reported significant score increases, resulting in worsening of pain (d = 0.51), fatigue (d = 0.35), and depression (d = 0.57; all P < .01). Cancer recurrence and progression were associated with smaller increases in pain, fatigue, and sleep disturbance (d = 0.22‐0.27). CONCLUSIONS The current results indicated that all 8 PROMIS measures were sensitive to patient‐perceived worsening and improvement and to major clinical events. These findings will be able to inform the design and interpretation of future research studies and clinical initiatives administering PROMIS measures. Cancer 2017;123:327–335. © 2016 American Cancer Society .

Key Points Patients living in low SES neighborhoods had worse survival after DLBCL. Disparity was most striking in younger (non-Medicare) patients and after the introduction of rituximab.