ABSTRACT
Background Yttrium-90 ibritumomab tiuxetan [(90)Y-IT;Zevalin] is a radio-immunoconjugate (RIC) which targets CD20. This study evaluates the utilization and cost-effectiveness of (90)Y-IT in the first line treatment for patients with previously untreated low-grade FL (UFL) and marginal zone lymphoma (UMZL) treated at our institution with (90)Y-IT. Methods We utilized the Advanced Text Explorer (ATE) and the Lymphoma SPORE databases to identify two groups of patients with UFL, WHO grade 1-2, and UMZL who received treatment with either (90)Y-IT or bendamustine plus rituximab (BR) at Mayo Clinic Cancer Center between January 2003 and December 2019. We excluded all patients who had >25% bone marrow involvement with lymphoma for the BR group as this was a requirement for (90)Y-IT treatment. Inverse propensity weighting was utilized to balance the groups for baseline patients and disease characteristics. We use progression-free survival (PFS) as a denominator for the cost effectiveness/utilization evaluation. We identified meaningful and retrospectively measurable outcomes to compare between the groups. we extracted the following data;number of clinic visits in the first year after therapy, emergency room visits, number of hospital admissions, number of hospitalization days, numbers of days on the floor and ICU, number of infections, number of neutropenic fever hospitalizations, number of C-difficile events, number of blood products transfusions, overall use of growth factors due to therapy induced neutropenia, average number of times a growth factor was used, and the number of therapeutic use days. We defined days of therapeutic use as the number of days a treatment was administered on. We also calculated the average cost of the induction treatment when utilizing either (90)Y-IT or BR. The therapeutic cost included only the cost of the medications/therapies and their administration. Results Our cohort consists of a total of 143 patients - 64% (92/143) received BR and 36% (51/143) received (90)Y-IT (see Table-1 for clinical characteristics).The median follow-up from the time of therapeutic administration for the (90)Y-IT group was 5.3 years (95% CI;4.2, 6.2) with one death and 4.7 years (95% CI;3.9, 4.9) for the BR group with 6 deaths. The ORR was 100% in (90)Y-IT group with 94% achieving complete response (CR) while ORR in the BR group was 98% with 95% achieving CR. Rituximab maintenance was utilized in 33% of BR patients compared to only 6% in patients who received (90)Y-IT, p=0.002. After utilizing inverse propensity weighting (Figure-1), 5 years PFS was 76% for the (90)Y-IT group and 75% for the BR group, p=0.63 (Figure-2). We evaluated the average treatment effect of (90)Y-IT compared to BR on utilization outcomes, Table-2. (90)Y-IT required an average of 4.5 clinic visits less within the first year after treatment compared to BR group, p<0.001. (90)Y-IT patients had an average of 10 days less of therapeutic use days compared to the BR group, p<0.001. Patienta had similar admission rates to the hospital in both groups. However, when patients were admitted to the hospital in the first year after treatment, those who received (90)Y-IT spent an average of 1.5 days less in the hospital compared to the BR group, p=0.046. The overall use of growth factors was 40% less in the (90)Y-IT group as compared to the BR group, p<0.001. The therapeutic cost of induction of (90)Y-IT was 54% less than that of 6 cycles of BR. Transformation to a high grade of lymphoma was seen in 4 patients in the BR group and 2 patients in the (90)Y-IT group. There was only one case of myelodysplastic syndrome in the BR group and none in the (90)Y-IT group. Conclusion Radio-immunoconjugate therapy with (90)Y-IT is a very convenient and cost-effective treatment for low-grade UFL and UMZL. This is especially important amidst the COVID-19 pandemic as it requires less contact with the health system with decreased number of therapeutic days, clinic visits, use of growth factors and number of hospitalization days. The cost of the therapeutic agents and heir administration was also significantly lower for the (90)Y-IT which could help reducing the burden on the health system. (Figure Presented).
ABSTRACT
Introduction: Non-Hodgkin lymphoma (NHL) constitutes ~40% of hematologic malignancies and, in 2020, resulted in 19,940 deaths in the USA. The most common NHL subtypes are diffuse large B-cell lymphoma (DLBCL), including primary mediastinal large B-cell lymphoma (PMBCL), and follicular lymphoma (FL). Although a majority of patients respond to standard-of-care therapy, many patients with NHL eventually relapse, highlighting the need for additional treatments. Real-world data regarding the safety and efficacy of emerging therapies in the relapsed/refractory (R/R) population, and the association between treatment patterns and patient outcomes, are limited. These data could provide unique insights to clinical and health-related quality of life (HRQoL) outcomes in patients with DLBCL, FL, or PMBCL treated with emerging therapies, especially novel options such as chimeric antigen receptor (CAR) T cell therapies. Methods: The Connect ® Lymphoma Disease Registry (NCT04982471) is a US-based, multicenter, prospective observational cohort study of patients with R/R NHL (DLBCL, FL, and PMBCL). Approximately 2100 patients ≥ 18 years of age from ~200 community oncology (~80%) or academic (~20%) sites will be enrolled over a ~3-year period. Patients with histologically confirmed NHL subtypes will be enrolled into 1 of 4 cohorts: first R/R DLBCL, second R/R DLBCL, first R/R FL, or first R/R PMBCL (Figure). Patients will be required to have begun second- (first R/R) or third- (second R/R) line systemic treatment within 60 days prior to enrollment. Patients receiving treatment for any active malignancy other than DLBCL, FL, or PMBCL at the time of enrollment, or who are diagnosed with any other malignancy in the 6 months prior to enrollment, will be excluded. All treatment and management decisions will be determined by the practicing clinicians. Patients may undergo hematopoietic stem cell transplantation, CAR T cell therapy, or other treatments at other sites while participating in this study. Patients will be followed from enrollment for up to 5 years or until death, withdrawal of consent, loss to follow-up, or study termination, whichever occurs first. Data collection will occur at enrollment (baseline) and then every ~3 months. The main objectives of the Connect ® Registry are to describe patient characteristics, practice patterns, and factors associated with treatment choice, sequencing, and effectiveness in NHL subtypes. Secondary objectives include describing treatment regimen safety, patient-reported outcomes (PROs) including HRQoL, and healthcare resource utilization outcomes. Exploratory objectives include tumor and blood biomarker evaluation and understanding the availability of social support and its impact on long-term treatment decision-making. Case report forms will be used to collect clinical and treatment data, including baseline demographics, clinical characteristics, treatment details and response, and socioeconomic factors. Outcome measures for efficacy will be progression-free survival, event-free survival, objective response rate, time to next treatment, and overall survival. The availability of social support will be assessed via a specific questionnaire administered at baseline. General (EQ-5D-5L) and disease-specific (FACT-Lym) questionnaires will also be administered. Patients may also optionally agree to release tumor biopsies and blood samples for biomarker analysis. Clinicians will be required to report serious adverse events (AEs), secondary primary malignancies, and confirmed COVID-19 infections within 24 hours. Non-serious AEs of interest include grade 1-3 cytokine release syndrome, grade 1-3 neurotoxicity, grade 3 colitis, grade 3 arrhythmia, grade 3 hemorrhage. Other AEs of interest to be collected include grade 3 hypogammaglobulinemia, prolonged grade 3 cytopenia, and grade 3 infections. Data collected in the Connect ® Registry will increase understanding of the association between emerging therapies and patient outcomes for R/R DLBCL, FL, and PMBCL. Study support: Bristol Myers Squibb [Formula presented] Disclosures: Flowers: Amgen: Research Funding;Janssen: Research Funding;Biopharma: Consultancy;Ziopharm: Research Funding;Burroughs Wellcome Fund: Research Funding;Nektar: Research Funding;Karyopharm: Consultancy;Iovance: Research Funding;Allogene: Research Funding;AbbVie: Consultancy, Research Funding;Cellectis: Research Funding;Pfizer: Research Funding;Sanofi: Research Funding;BeiGene: Consultancy;Kite: Research Funding;EMD: Research Funding;Genentech/Roche: Consultancy, Research Funding;Morphosys: Research Funding;Adaptimmune: Research Funding;Novartis: Research Funding;Epizyme, Inc.: Consultancy;Spectrum: Consultancy;Pharmacyclics/Janssen: Consultancy;Acerta: Research Funding;4D: Research Funding;Denovo: Consultancy;Celgene: Consultancy, Research Funding;Guardant: Research Funding;Genmab: Consultancy;Gilead: Consultancy, Research Funding;Bayer: Consultancy, Research Funding;SeaGen: Consultancy;Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding;Takeda: Research Funding;National Cancer Institute: Research Funding;TG Therapeutics: Research Funding;Eastern Cooperative Oncology Group: Research Funding;Xencor: Research Funding;Pharmacyclics: Research Funding. Andorsky: Celgene/Bristol Myers Squibb: Research Funding;AbbVie: Consultancy;Celgene/Bristol Myers Squibb: Consultancy;AstraZeneca: Other: served on steering committees;Epizyme: Research Funding;AbbVie: Research Funding. Burke: SeaGen: Consultancy, Speakers Bureau;X4 Pharmaceuticals: Consultancy;Bristol Myers Squibb: Consultancy;Verastem: Consultancy;AstraZeneca: Consultancy;MorphoSys: Consultancy;Adaptive Biotechnologies: Consultancy;Roche/Genentech: Consultancy;Epizyme: Consultancy;Kura: Consultancy;AbbVie: Consultancy;Beigene: Consultancy, Speakers Bureau;Kymera: Consultancy. Cerhan: Genentech: Research Funding;NanoString: Research Funding;Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding;Regeneron Genetics Center: Other: Research Collaboration. Grinblatt: Astellas Pharma, Inc.: Consultancy;Bristol Myers Squibb: Consultancy;Astra Zeneca: Consultancy;AbbVie: Consultancy. Toomey: Bristol Myers Squibb: Consultancy. Zelenetz: Gilead: Honoraria, Research Funding;Verastem: Honoraria;Novartis: Honoraria;MEI Pharma: Honoraria, Research Funding;SecuraBio: Honoraria;Abbvie: Honoraria, Research Funding;MorphoSys: Honoraria;Pharmacyclics: Honoraria;AstraZeneca: Honoraria;LFR: Other;Genentech/Roche: Honoraria, Research Funding;NCCN: Other;MethylGene: Research Funding;Beigene: Honoraria, Other, Research Funding;BMS/Celgene/JUNO: Honoraria, Other;Amgen: Honoraria;Gilead: Honoraria;Janssen: Honoraria. Sullivan: Bristol Myers Squibb: Current Employment, Current holder of individual stocks in a privately-held company. Flick: Bristol Myers Squibb: Current Employment. Kiselev: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Kaplan: Bristol Myers Squibb: Current Employment. Ahn: Bristol Myers Squibb: Current Employment.
ABSTRACT
Objective: To determine the association between chronic statin use and mortality in patients hospitalized with coronavirus disease 2019 (COVID-19). Patients and Methods: We identified a retrospective cohort of patients requiring admission at the Mayo Clinic using our enterprise-wide COVID-19 registry from March 1, 2020, through September 30, 2020. Available information included age, sex, use of statins, medical comorbidities, and 30-day mortality. We estimated the association of statins with 30-day mortality using odds ratios and 95% CIs from logistic regression modeling. Results: Patients (N=1295) between the ages of 30 and 80 years tested positive for COVID-19 and required admission during the study period, of whom 500 (38.6%) were taking statins at admission. Patients taking statins were older and more likely to have diabetes mellitus or congestive heart failure. Within 30 days of diagnosis, 59 (4.6%) died. In multivariable analysis, statin users did not have statistically different odds of death within 30 days with an odds ratio of 1.14 (95% CI, 0.64 to 2.03;P=.67) compared to nonusers. Conclusion: Patients with COVID-19 taking statins had similar 30-day mortality to those not taking statins after adjusting for relevant covariates. Although this is partly influenced by a higher prevalence of risk factors for more severe COVID-19 presentation not entirely adjusted for by the Charlson comorbidity index, these data would not support statins as a likely therapeutic intervention for COVID-19 in the hospital setting.