Detecting deviations from the efficacy and safety results of single‐arm trials using real‐world data: The case of a CAR‐T cell therapy in B‐cell lymphoma

• Published in: Pharmacoepidemiology and drug safety Vol. 30; no. 4; pp. 514 - 519
• Main Authors: Jakobsen, Lasse Hjort, Callréus, Torbjörn, Sessa, Maurizio, Jerkeman, Mats, Andersen, Morten, El‐Galaly, Tarec Christoffer
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Inc 01-04-2021; Wiley Subscription Services, Inc
• Subjects: Adverse events; Aphasia; B-cell lymphoma; Basic Medicine; Cancer and Oncology; Cancer och onkologi; CAR-T cell therapy; Cell therapy; Cell- and Tissue-Based Therapy; Chimeric antigen receptors; Clinical Medicine; Clinical trials; Humans; Immunologi inom det medicinska området; Immunology in the medical area; Immunotherapy, Adoptive; Klinisk medicin; Lymphocytes; Lymphocytes T; Lymphoma; Lymphoma, Large B-Cell, Diffuse; Medical and Health Sciences; Medicin och hälsovetenskap; Medicinska och farmaceutiska grundvetenskaper; monitoring; Randomized Controlled Trials as Topic; Receptors, Chimeric Antigen; Safety; single-arm trial; single-arm trial; monitoring; CAR-T cell therapy
• ISSN: 1053-8569; 1099-1557
• DOI: 10.1002/pds.5195

Purpose
Personalized therapies are leading to an increasing number of marketing authorizations based on single‐arm trials, which increases the demand for better post‐authorization monitoring strategies. The aim of the present study was to estimate the power over time as data accrue in population‐based registries for detecting deviations from the expected efficacy/safety of chimeric antigen receptor T cell (CAR‐T) therapy approved for relapsed/refractory large B‐cell lymphoma (RR‐LBCL).
Methods
The number of real‐world RR‐LBCL patients was projected over time in a general population of 5, 15, and 25 million citizens using lymphoma registry data. For each scenario, we computed the power over time for detecting significant deviations in efficacy (1‐year overall survival [1yOS]) when comparing to historical controls (SCHOLAR‐1 study; 1yOS, 28%) and RR‐LBCL patients treated with CAR‐T cell therapy in a single‐arm trial (ZUMA‐1; 1yOS, 59%) as well as deviations in selected adverse events (grade ≥3 aphasia) from the ZUMA‐1 trial. We assumed a 10% absolute deviation in 1yOS (efficacy) and a relative increase of 50% in grade ≥3 aphasia (safety).
Results
Assuming a general population of 5, 15, and 25 million, the accrual time needed to achieve 80% power for detecting a significant increase over the 1yOS reported in SCHOLAR‐1 was 9, 4, and 3 years, respectively, while 80% power for detecting a significant decrease in 1yOS compared to ZUMA‐1 required 10.5, 4.5, and 3 years of data accrual, respectively. However, corresponding estimates for aphasia were >20, 8, and 5 years, respectively.
Conclusions
Projections of the statistical power for detecting important deviations in efficacy/safety from that reported in pivotal clinical trials(s) provide critical information about the expected performance of post‐authorization monitoring programs.