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PET/CT Biomarkers Enable Risk Stratification of Patients with Relapsed/Refractory Diffuse Large B-cell Lymphoma Enrolled in the LOTIS-2 Clinical Trial

医学 肿瘤科 内科学 生物标志物 弥漫性大B细胞淋巴瘤 比例危险模型 逻辑回归 临床试验 耐火材料(行星科学) 淋巴瘤 生物化学 天体生物学 物理 化学
作者
Juan Pablo Alderuccio,Isildinha M. Reis,Mehdi Hamadani,Muthiah Nachiappan,Salman Leslom,Brad S. Kahl,Weiyun Z. Ai,John Radford,Melhem Solh,Kirit M. Ardeshna,Brian T. Hess,Matthew A. Lunning,Pier Luigi Zinzani,Anastasios Stathis,Carmelo Carlo‐Stella,Izidore S. Lossos,Paolo F. Caimi,Sunwoo Han,Fei Yang,Russ Kuker,Craig H. Moskowitz
出处
期刊:Clinical Cancer Research [American Association for Cancer Research]
卷期号:30 (1): 139-149 被引量:2
标识
DOI:10.1158/1078-0432.ccr-23-1561
摘要

Abstract Purpose: Significant progress has occurred in developing quantitative PET/CT biomarkers in diffuse large B-cell lymphoma (DLBCL). Total metabolic tumor volume (MTV) is the most extensively studied, enabling assessment of FDG-avid tumor burden associated with outcomes. However, prior studies evaluated the outcome of cytotoxic chemotherapy or chimeric antigen receptor T-cell therapy without data on recently approved FDA agents. Therefore, we aimed to assess the prognosis of PET/CT biomarkers in patients treated with loncastuximab tesirine. Experimental Design: We centrally reviewed screening PET/CT scans of patients with relapsed/refractory DLBCL enrolled in the LOTIS-2 (NCT03589469) study. MTV was obtained by computing individual volumes using the SUV ≥4.0 threshold. Other PET/CT metrics, clinical factors, and the International Metabolic Prognostic Index (IMPI) were evaluated. Logistic regression was used to assess the association between biomarkers and treatment response. Cox regression was used to determine the effect of biomarkers on time-to-event outcomes. We estimated biomarker prediction as continuous and binary variables defined by cutoff points. Results: Across 138 patients included in this study, MTV with a cutoff point of 96 mL was the biomarker associated with the highest predictive performance in univariable and multivariable models to predict failure to achieve complete metabolic response (OR, 5.42; P = 0.002), progression-free survival (HR, 2.68; P = 0.002), and overall survival (HR, 3.09; P < 0.0001). IMPI demonstrated an appropriate performance, however, not better than MTV alone. Conclusions: Pretreatment MTV demonstrated robust risk stratification, with those patients demonstrating high MTV achieving lower responses and survival to loncastuximab tesirine in relapsed/refractory DLBCL.

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