Prognostic implications of splenomegaly in BCMA-directed CAR T-Cell therapy for relapsed myeloma.

Abstract

Background: B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T-cell therapy has shown significant promise for patients with relapsed or refractory multiple myeloma (RRMM). Despite its efficacy, treatment is frequently complicated by adverse events such as cytokine release syndrome and hematologic toxicities, including severe thrombocytopenia. Identifying reliable prognostic markers is essential to improve patient risk stratification, optimizing treatment strategies, and managing complications effectively. While various prognostic markers have been explored, spleen size has not been extensively studied in this context.

Objective: This study aims to evaluate spleen size as a prognostic marker in RRMM patients receiving CAR T-cell therapy. Specifically, we examine its association with thrombocytopenia, metabolic tumor volume, soluble BCMA (sBCMA) levels, progression-free survival (PFS), and overall survival (OS). Additionally, we compare spleen size to other established prognostic markers, including sBCMA, EASIX, and CAR-HEMATOTOX scores, to determine its predictive value.

Study design: Data from RRMM patients (N=73) treated with either Idecabtagene vicleucel or Ciltacabtagen autoleucel were analyzed. The association of spleen size, assessed via computed tomography imaging, with clinical outcomes was analyzed.

Results: Splenomegaly (spleen size > 340 cm³) was found to be significantly associated with severe and prolonged thrombocytopenia, higher metabolic tumor volumes, and elevated sBCMA levels. In our cohort, splenomegaly emerged as an independent prognostic factor for both PFS and OS, showing stronger associations than other markers such as sBCMA, EASIX, and CAR-HEMATOTOX scores.

Conclusions: Spleen size may serve as a promising prognostic marker in CAR T-cell therapy for RRMM patients, providing a simple and readily accessible tool for enhancing risk stratification. This finding could inform monitoring strategies and optimize healthcare resource management for these patients.