Citations

Abstract The prognostic relevance of diagnosis to treatment interval (DTI) in patients with newly diagnosed mantle cell lymphoma (MCL) is unknown. Hence, we sought to evaluate the impact of DTI on outcomes in MCL using 3 large datasets (1) the University of Iowa/Mayo Clinic Specialized Program of Research Excellence Molecular Epidemiology Resource, (2) patients enrolled in the ALL Age Asthma Cohort/CALGB 50403, and (3) a multisitecohort of patients with MCL. Patients were a priori divided into 2 groups, 0 to 14 days (short DTI) and 15 to 60 days (long DTI). The patients in whom observation was deemed appropriate were excluded. One thousand ninety-seven patients newly diagnosed with MCL and available DTI were included in the study. The majority (73%) had long DTI (n=797). Patients with short DTI had worse eastern cooperative oncology group performance status (ECOG PS ≥2), higher lactate dehydrogenase, bone marrow involvement, more frequent B symptoms, higher MCL International Prognostic Index (MIPI ≥6.2), and were less likely to receive intensive induction therapy than long DTI group. The median progression-free survival (2.5 years vs 4.8 years, p<0.0001) and overall survival (7.8 years vs. 11.8 years, p<0.0001) were significantly inferior in the short DTI group than the long DTI cohort and remained significant for progression-free survival and overall survival in multivariable analysis. We show that the DTI is an important prognostic factor in patients newly diagnosed with MCL and is strongly associated with adverse clinical factors and poor outcomes. DTI should be reported in all the patients newly diagnosed with MCL who are enrolling in clinical trials and steps must be taken to ensure selection bias is avoided.

Abstract Cancer clinical trial eligibility criteria may create patient populations studied in trials that do not reflect the patient populations treated in the real-world setting. Follicular lymphoma (FL) is an indolent lymphoma with heterogeneous presentations across a broad range of individuals, resulting in many acceptable management strategies. We evaluated how first-line clinical trial eligibility criteria impacted the demographic makeup and outcomes of patients with FL for whom systemic therapy might be considered. We compared the characteristics of 196 patients with FL from a single institution to eligibility criteria from 10 first-line FL trials on clinicaltrials.gov. Next, we tabulated eligibility criteria from 24 first-line FL protocols and evaluated their impact on 1198 patients with FL with stages II to IV disease from the prospective Molecular Epidemiology Resource (MER) and Lymphoma Epidemiology of Outcomes (LEO) cohort studies. We found that 39.8% and 52.7% of patients with FL might be excluded from clinical trials based on eligibility criteria derived from clinicaltrials.gov and protocol documents, respectively. Patients excluded because of renal function, prior malignancy, and self-reported serious health conditions tended to be older. Expanding stage requirement from III-IV to II-IV, and platelet requirement from ≥150 000 to ≥75 000 increased population size by 21% and 8%, respectively, in MER and by 16% and 13%, respectively, in LEO, without impacting patient demographics or outcomes. These data suggest that management of older individuals with FL may not be fully informed by recent clinical trials. Moreover, liberalizing stage and platelet criteria might expand the eligible population and allow for quicker trial accrual without impacting outcomes.

7573 Background: While most patients (pts) with follicular lymphoma (FL) usually have favorable outcomes, those with refractory disease after first-line anti-CD20 based immunochemotherapy (IC), or progression within 24 months of diagnosis (POD24) have higher risk of premature death. There are no standard approaches for treating this vulnerable group and studies testing novel agents are ongoing in this setting. We sought to investigate clinical practice treatment choices and efficacy for pts with POD24 that align with eligibility criteria for the randomized SWOG1608 which compares IC with novel agents in this population. Methods: This was a multicenter observational cohort study from the LEO Consortium. Eligible pts had grade 1-3a FL diagnosed between 1/1/2002 and 2/1/2019, and initiated therapy after POD24 to first-line bendamustine or CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone) based IC. Observation, radiotherapy, or rituximab monotherapy were permitted prior to IC and pts with transformation prior to the subsequent therapy after IC were excluded as per S1608. Outcomes of interest were overall and complete response rate (ORR/CR), progression-free survival (PFS), and overall survival (OS). Results: We identified 196 eligible pts with early progression to IC (39% antiCD20 Benda; 61% antiCD20 CHOP) who received subsequent therapy. Median age at post IC treatment was 57 years, 78% grade 1-2 FL. Treatments for pts with POD24 included CHOP- or Benda-based in 31%, salvage/hematopoietic stem cell transplant (HSCT) in 27%, novel therapies in 10% (including phosphatidylinositol 3-kinase inhibitors), antiCD20 monotherapy in 9%, and lenalidomide-based treatment in 8% (table); 21% of pts were treated on clinical trials. Across all treatments, ORR (CR) was 63% (37%) (95% CI: 55-70). At a median follow up of 6.2 years, 2 year PFS was 22% (95% CI: 17%-29%) and 5 year OS was 71% (95% CI: 65-79). Outcomes by regimen are shown in the table. Conclusions: Pts with FL experiencing POD24 following first-line IC are treated heterogeneously, with many pts still receiving IC as subsequent therapy. Despite modest CR rates and low 2-year PFS, 5-year OS appear to be improving compared to historical outcomes. This supports the ongoing need to investigate novel treatments in this population. [Table: see text]

Abstract Background: Differences in outcomes between clinical trial and real-world populations in follicular lymphoma (FL) may be partially explained by differences in characteristics between clinical trial and real-world patients. We hypothesized that certain eligibility criteria may be responsible for populations with distinct demographic/clinical characteristics. In this study, we compiled a list of eligibility criteria from front-line FL trials and evaluated their impact on the potentially eligible FL patients derived from two national cohort studies. We also evaluated whether criteria were duplicative and whether liberalizing criteria might enlarge the pool of eligible patients. Methods: Eligibility criteria were abstracted from 21 first-line clinical trials in FL in the FLASH database. We identified FL patients in two prospective cohort studies: Molecular Epidemiology Resource (MER) and Lymphoma Epidemiology of Outcomes (LEO). Descriptive statistics were used to characterize patients included and excluded by various eligibility criteria. Chi-square tests and two-sample t-tests were used to compare categorical and continuous variables, respectively. To study the relative impact of individual criteria, we used a step-wise approach to quantify the number of additional patients excluded with each individual criterion after applying other criteria. Results: Eligibility criteria included in at least one-third of studies included stage (present in all 21 trials), renal function (18), HIV/AIDS status (17), performance status (16), history of other malignancies (16), hepatic function (16), and cardiac function (15), other serious health conditions (13), pregnancy status (10), neuro/psych function (10), age (10), metabolic disease status (9), CNS involvement (9), birth control (8), pulmonary function (8), WBC count (8), HBV status (8), platelet count (7), measurable disease (7), HCV status (7), active infection status (7), and CD20 status (7). We included 738 patients with newly diagnosed FL undergoing first-line therapy from MER and 703 patients from LEO. In MER, the median age was 60 years; 87% were White vs 2% non-White, 80% were non-Hispanic vs 2% Hispanic, and 68% were stage III/IV. In LEO, the median age was 60 years; 88% were White vs 11% non-White, 87% were non-Hispanic vs 11% Hispanic, and 67% were stage III/IV. Exclusion criteria impacting more than 10% of patients included stage (31 in LEO vs 29% in MER), self-reported serious health conditions (17 vs 31%), prior cancer diagnosis (14 vs 11%), performance status (10%), and platelet count (10%). Patients excluded due to the following criteria tended to be older: renal function (median 70 vs 60 years in MER), prior malignancy (67 vs 58 years), and self-reported serious health conditions (66 vs 58 years). This pattern was consistent in LEO (Table). No eligibility criteria significantly impacted race/ethnicity. Given the potential for multiple eligibility criteria to exclude the same patients, we used a step-wise approach to evaluate the impact of individual criteria on patients remaining after exclusion by the larger group of criteria, and whether liberalizing criteria impacted patient numbers and/or demographics. We found that only self-reported serious health conditions significantly impacted numbers (excluding 43% of patients), whereas hematologic parameters and performance status excluded only 5 and 1% of patients, respectively, with no impact on age or race/ethnicity. We also found that liberalizing stage requirement from III-IV to II-IV could increase enrollment by 14% in MER (12% in LEO), and liberalizing platelet requirement from ≥150,000 to ≥100,000 could increase enrollment by 11% (15% in LEO). Moreover, liberalizing eligibility criteria had no impact on age or race/ethnicity of the patient pool or on EFS (Figure). Conclusions: We found that excluding patients with prior malignancies, poor renal function, and self-reported serious health conditions appears to inadvertently exclude older patients. Other serious health conditions appeared to exclude a significant number of patients but did not impact patient demographics. Liberalizing certain criteria, including stage and platelet requirement, could potentially increase trial accrual, but would not likely correct the older patient deficit. These findings may serve in developing consensus eligibility criteria for future first-line FL trials. Figure 1 Figure 1. Disclosures Flowers: Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; National Cancer Institute: Research Funding; Allogene: Research Funding; Biopharma: Consultancy; Cellectis: Research Funding; EMD: Research Funding; Genentech/Roche: Consultancy, Research Funding; Epizyme, Inc.: Consultancy; Genmab: Consultancy; Iovance: Research Funding; Guardant: Research Funding; Burroughs Wellcome Fund: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; Spectrum: Consultancy; Gilead: Consultancy, Research Funding; Amgen: Research Funding; Xencor: Research Funding; Nektar: Research Funding; SeaGen: Consultancy; Ziopharm: Research Funding; TG Therapeutics: Research Funding; 4D: Research Funding; Acerta: Research Funding; Denovo: Consultancy; Novartis: Research Funding; Pfizer: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Morphosys: Research Funding; Adaptimmune: Research Funding; Pharmacyclics/Janssen: Consultancy; Karyopharm: Consultancy; BeiGene: Consultancy; AbbVie: Consultancy, Research Funding; Kite: Research Funding; Janssen: Research Funding; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Pharmacyclics: Research Funding. Link: MEI: Consultancy; Novartis, Jannsen: Research Funding; Genentech/Roche: Consultancy, Research Funding. Friedberg: Acerta: Other: DSMC ; Bayer: Other: DSMC ; Novartis: Other: DSMC . Cohen: Genentech, Takeda, BMS/Celgene, BioInvent, LAM, Astra Zeneca, Novartis, Loxo/Lilly: Research Funding; Janssen, Adaptive, Aptitude Health, BeiGene, Cellectar, Adicet, Loxo/Lilly, AStra ZenecaKite/Gilead: Consultancy. Kahl: AbbVie, Acerta, ADCT, AstraZeneca, BeiGene, Genentech: Research Funding; AbbVie, Adaptive, ADCT, AstraZeneca, Bayer, BeiGene, Bristol-Myers Squibb, Celgene, Genentech, Incyte, Janssen, Karyopharm, Kite, MEI, Pharmacyclics, Roche, TG Therapeutics, and Teva: Consultancy. Lossos: Lymphoma Research Foundation: Membership on an entity's Board of Directors or advisory committees; Stanford University: Patents & Royalties; Seattle Genetics: Consultancy; NCI: Research Funding; Verastem: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; NIH grants: Research Funding; University of Miami: Current Employment. Nastoupil: Bayer: Honoraria; Gilead/Kite: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; ADC Therapeutics: Honoraria; IGM Biosciences: Research Funding; Takeda: Honoraria, Other: DSMC, Research Funding; Janssen: Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; TG Therapeutics: Honoraria, Research Funding; Epizyme: Honoraria, Research Funding; Denovo Pharma: Other: DSMC; Caribou Biosciences: Research Funding; Bristol Myers Squibb/Celgene: Honoraria, Research Funding; MorphoSys: Honoraria. Maurer: Nanostring: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; BMS: Research Funding. Cerhan: NanoString: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding. Martin: ADCT: Consultancy.