Progression-free survival as a surrogate endpoint for overall survival in glioblastoma: a literature-based meta-analysis from 91 trials
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CitationHan, Kelong, Melanie Ren, Wolfgang Wick, Lauren Abrey, Asha Das, Jin Jin, and David A. Reardon. 2013. “Progression-free survival as a surrogate endpoint for overall survival in glioblastoma: a literature-based meta-analysis from 91 trials.” Neuro-Oncology 16 (5): 696-706. doi:10.1093/neuonc/not236. http://dx.doi.org/10.1093/neuonc/not236.
AbstractBackground: The aim of this study was to determine correlations between progression-free survival (PFS) and the objective response rate (ORR) with overall survival (OS) in glioblastoma and to evaluate their potential use as surrogates for OS. Method Published glioblastoma trials reporting OS and ORR and/or PFS with sufficient detail were included in correlative analyses using weighted linear regression. Results: Of 274 published unique glioblastoma trials, 91 were included. PFS and OS hazard ratios were strongly correlated; R2 = 0.92 (95% confidence interval [CI], 0.71–0.99). Linear regression determined that a 10% PFS risk reduction would yield an 8.1% ± 0.8% OS risk reduction. R2 between median PFS and median OS was 0.70 (95% CI, 0.59–0.79), with a higher value in trials using Response Assessment in Neuro-Oncology (RANO; R2 = 0.96, n = 8) versus Macdonald criteria (R2 = 0.70; n = 83). No significant differences were demonstrated between temozolomide- and bevacizumab-containing regimens (P = .10) or between trials using RANO and Macdonald criteria (P = .49). The regression line slope between median PFS and OS was significantly higher in newly diagnosed versus recurrent disease (0.58 vs 0.35, P = .04). R2 for 6-month PFS with 1-year OS and median OS were 0.60 (95% CI, 0.37–0.77) and 0.64 (95% CI, 0.42–0.77), respectively. Objective response rate and OS were poorly correlated (R2 = 0.22). Conclusion: In glioblastoma, PFS and OS are strongly correlated, indicating that PFS may be an appropriate surrogate for OS. Compared with OS, PFS offers earlier assessment and higher statistical power at the time of analysis.
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