Efficacy and safety of add-on anti-CD20 monoclonal antibody to Bruton tyrosine kinase inhibitor treatment for chronic lymphocytic leukemia: a meta-analysis

Thi Thuy Nguyen, Nguyen Thanh Nhu, Van Khoi Tran, Nguyen Kieu Viet-Nhi, Xuan Dung Ho, Ming Kai Jhan, Ya Ping Chen, Chiou Feng Lin

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Abstract

The efficacy of Bruton tyrosine kinase inhibitors (BTKi) remains suboptimal in chronic lymphocytic leukemia (CLL) treatment. A systematic review and meta-analysis were conducted to compare the outcomes of combining anti-CD20 monoclonal antibodies (mAb) with BTKi therapy versus BTKi monotherapy for patients with CLL. We searched for relevant studies in the Pubmed, Medline, Embase, and Cochrane databases until December 2022. We estimated the effective results using a hazard ratio (HR) for survival outcomes and relative risk (RR) for response outcomes and safety. Four randomized controlled trials (including 1056 patients) were found until November 2022 and fulfilled the inclusion criteria. Progression-free survival was significantly improved with the addition of anti-CD20 mAb to BTKi over BTKi (HR 0.70, 95% confidence interval (CI) 0.51–0.97), whereas pooled analysis of overall survival did not favor combination therapy compared to BTKi monotherapy (HR 0.72, 95% CI 0.50–1.04). Combination therapy was related to a statistically better complete response (RR, 2.03; 95% CI 1.01 to 4.06) and an undetectable minimal residual disease rate (RR, 6.43; 95% CI 3.54 to 11.67). The risk of grade ≥ 3 adverse events was comparable between the two groups (RR, 1.08; (95% CI 0.80 to 1.45). Overall, adding anti-CD20 mAb to BTKi revealed superior efficacy than BTKi alone in untreated or previously treated CLL patients without affecting the safety of single-agent BTKi. Conducting further randomized studies to confirm our results and determine the optimal therapy for managing patients with CLL is essential.

Original languageEnglish
Article number9775
JournalScientific reports
Volume13
Issue number1
DOIs
Publication statusPublished - 2023 Dec

All Science Journal Classification (ASJC) codes

  • General

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