Large B-Cell Lymphoma after CD19 CAR-T Failure: Updated Real-World Outcomes, Prognostic Factors, and Prediction...

Outcomes after CD19-directed chimeric antigen receptor T-cell (CAR-T) therapy failure in relapsed or refractory large B-cell lymphoma (LBCL) remain poor, and prognostic tools to guide subsequent management are limited. We evaluated real-world outcomes after CAR-T failure and developed clinical prediction models (CPMs) for survival after subsequent anti-cancer therapy. We conducted a single-center retrospective cohort study of adult patients with LBCL treated with CD19-directed CAR-T therapy at Oregon Health & Science University between 2016 and 2024. Patients experiencing relapse or progression after CAR-T therapy were included. Overall survival from relapse/progression (OS1) and from initiation of subsequent anti-cancer therapy (OS2) were evaluated. Cox proportional hazards models were used to develop CPMs for 1-yr OS among patients receiving subsequent therapy. Among 187 patients treated with CD19-directed CAR-T therapy, 100 (53%) experienced treatment failure. Sixty-eight patients received subsequent anti-cancer therapy and were included in prognostic analyses. Median OS1 was 5.07 mo (95% CI, 3.71 to 8.58). Patients receiving subsequent therapy had significantly improved OS compared with those who did not receive further treatment (median OS1, 9.94 versus 0.74 mo; P < .001). Among treated patients, median OS2 was 8.34 mo (95% CI, 6.73 to 20.1), with no significant differences across treatment strategy groups or treatment eras. The best-performing CPM incorporated time from CAR-T infusion to subsequent therapy, lactate dehydrogenase level, and Eastern Cooperative Oncology Group performance status, demonstrating good discrimination (c-statistic, 0.771) and calibration after internal validation. Outcomes after CAR-T failure in LBCL remain poor despite the availability of multiple salvage treatment strategies. Time to relapse after CAR-T therapy was the strongest prognostic factor. The proposed CPMs may provide a practical framework for risk stratification and support clinical decision-making and clinical trial selection pending external validation.