ArticleJournal for immunotherapy of cancer2026
Data-informed optimization of CAR T-cell therapy long-term follow-up.
Article in Journal for immunotherapy of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
21 authors.
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Abstract
Following administration of chimeric antigen receptor (CAR) T-cell therapy, extensive long-term follow-up (LTFU) requirements and complex data collection processes have posed significant challenges for patients and providers. To reassess whether a 15-year LTFU period remains scientifically justified, we convened a multistakeholder working group that included representatives from patient advocacy groups, academia, industry, and government. This analysis incorporates newly aggregated primary data on composite percentages of adverse events (AEs) reported by year for five Food and Drug Administration-approved CAR T-cell therapies. Combined with previously published research, the findings indicate that AEs are infrequently reported after 3 years post-infusion, and secondary T-cell malignancy-the AE of primary concern based on the mechanism of action of CAR T-cell therapy-has predominantly been reported within the first 2 years. Based on current cumulative safety data, a 5-year follow-up period may be scientifically sufficient in both clinical trial and commercial settings. Additionally, we propose a streamlined process that leverages technological advancements to automate the transfer of focused safety data from electronic health records into a third-party database. To facilitate implementation, we recommend feasibility testing of this updated data collection approach using an established platform. We also outline regulatory policy considerations to most effectively enable adoption of these recommendations.
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