BMC Cancer (Apr 2024)

Progression-free survival as a surrogate endpoint for overall survival in patients with relapsed or refractory multiple myeloma

  • Meletios Dimopoulos,
  • Pieter Sonneveld,
  • Salomon Manier,
  • Annette Lam,
  • Tito Roccia,
  • Jordan M. Schecter,
  • Patricia Cost,
  • Lida Pacaud,
  • Abbey Poirier,
  • Gabriel Tremblay,
  • Tommy Lan,
  • Satish Valluri,
  • Shaji Kumar

DOI
https://doi.org/10.1186/s12885-024-12263-0
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 7

Abstract

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Abstract Objectives The goal of the research was to assess the quantitative relationship between median progression-free survival (PFS) and median overall survival (OS) specifically among patients with relapsed/refractory multiple myeloma (RRMM) based on published randomized controlled trials (RCTs). Methods Two bibliographic databases (PubMed and Embase, 1970–2017) were systematically searched for RCTs in RRMM that reported OS and PFS, followed by an updated search of studies published between 2010 and 2022 in 3 databases (Embase, MEDLINE, and EBM Reviews, 2010–2022). The association between median PFS and median OS was assessed using the nonparametric Spearman rank and parametric Pearson correlation coefficients. Subsequently, the quantitative relationship between PFS and OS was assessed using weighted least-squares regression adjusted for covariates including age, sex, and publication year. Study arms were weighted by the number of patients in each arm. Results A total of 31 RCTs (56 treatment arms, 10,450 patients with RRMM) were included in the analysis. The average median PFS and median OS were 7.1 months (SD 5.5) and 28.1 months (SD 11.8), respectively. The Spearman and Pearson correlation coefficients between median PFS and median OS were 0.80 (P < 0.0001) and 0.79 (P < 0.0001), respectively. In individual treatment arms of RRMM trials, each 1-month increase in median PFS was associated with a 1.72-month (95% CI 1.26–2.17) increase in median OS. Conclusion Analysis of the relationship between PFS and OS incorporating more recent studies in RRMM further substantiates the use of PFS to predict OS in RRMM.

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