Risk Assessment in Large B-Cell Lymphoma Using Metabolic Tumor Volume: Real-World Data from a Multicenter Cohort of Patients Undergoing CAR T-Cell Therapy

医学 肿瘤科 内科学 队列 淋巴瘤 风险评估 危险分层 队列研究 生物标志物 前瞻性队列研究 接收机工作特性 预测模型 回顾性队列研究 曲线下面积 正电子发射断层摄影术 年轻人 生存分析 放射科 试验预测值
作者
Conrad‐Amadeus Voltin,Sarah Flossdorf,Lars Kurch,Michael Winkelmann,Andrea Farolfi,Laura Beckmann,Beatrice Casadei,Ken Herrmann,Nadine Kutsch,Peter Borchmann,Matthias Brendel,Viktoria Blumenberg,Stefano Fanti,Pier Luigi Zinzani,Kambiz Rahbar,Gabriel T. Sheikh,Osama Sabri,Alexander Drzezga,Markus Dietlein,H. Christian Reinhardt
出处
期刊:Journal of nuclear medicine [Society of Nuclear Medicine and Molecular Imaging]
卷期号:67 (6): jnumed.125.271976-jnumed.125.271976
标识
DOI:10.2967/jnumed.125.271976
摘要

Chimeric antigen receptor (CAR) T-cell therapy has proven highly effective in relapsed and refractory large B-cell lymphoma (LBCL). However, it remains unclear how to identify potential nonresponders before infusion. PET-derived metabolic tumor volume (MTV) has emerged as a promising biomarker in this context. The International Prognostic Index (IPI) remains commonly used to guide initial therapy and is an important element of patient stratification at later treatment time points. This study assessed whether quantification of 18F-FDG–avid lymphoma burden or MTV-based risk scores can predict outcomes more accurately than the IPI. Methods: The analysis set included 111 patients with LBCL from 5 German university hospitals and 1 Italian center who underwent PET imaging before CAR T-cell therapy. Metabolic tumor burden was measured semiautomatically using a fixed SUV threshold of 4.0 for lesion delineation. We evaluated its performance in the prediction of progression-free survival (PFS) through receiver-operating-characteristic curves, Harrell C-index, and additional criteria. Based on these analyses, MTV was compared with the IPI, considering 4 risk scores that incorporate 18F-FDG–avid tumor load. Results: We calculated an area under the curve and a Harrell C-index of 0.68 (95% CI, 0.58–0.78) and 0.59 (95% CI, 0.52–0.66), respectively, for MTV. Metabolic tumor burden was a more accurate predictor of PFS in our cohort than the IPI. The established score’s area under the curve and Harrell C-index were 0.61 (95% CI, 0.49–0.72) and 0.54 (95% CI, 0.47–0.61), respectively. A risk model combining MTV and extranodal involvement demonstrated the highest performance among those considered but was not superior to PET-derived tumor volume alone. Conclusion: Our data show that MTV outperforms the widely used IPI in predicting PFS of LBCL patients planned for tisagenlecleucel or axicabtagene ciloleucel. Compared with metabolic tumor burden alone, scores which combine the PET biomarker with other factors did not further improve risk assessment. Thus, effective reduction of MTV through individualized bridging strategies may play a particularly important role in this specific context.
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