Journal
INTERNATIONAL JOURNAL OF TECHNOLOGY ASSESSMENT IN HEALTH CARE
Volume 24, Issue 4, Pages 371-383Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0266462308080495
Keywords
Progression-free survival; Surrogate endpoint; Meta-analytic validation; Advanced breast cancer; Overall survival
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Funding
- NCI NIH HHS [K23 CA139005, R25 CA 92203, R25 CA092203] Funding Source: Medline
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Objectives: Progression-free survival (PFS) has not been validated as a surrogate endpoint for overall survival (OS) for anthracycline (A) and taxane-based (T) chemotherapy in advanced breast cancer (ABC). Using trial-level, meta-analytic approaches, we evaluated PFS as a surrogate endpoint. Methods: A literature review identified randomized, controlled A and T trials for ABC. Progression-based endpoints were classified by prospective definitions. Treatment effects were derived as hazard ratios for PFS (HRPFS) and OS (HROS). Kappa statistic assessed overall agreement. A fixed-effects regression model was used to predict HROS from observed HRPFS, Cross-validation was performed. Sensitivity and subgroup analyses were performed for PFS definition, year of last patient recruitment, line of treatment, and constant rate assumption. Results: Sixteen A and fifteen T trials met inclusion criteria, producing seventeen A (n 4,323) and seventeen T (n = 5,893) trial-arm pairs. Agreement (kappa statistic) between the direction of HROS and HRPFS was 0.71 for A (p = .0029) and 0.75 for T (p = .0028). While HRPFS was a statistically significant predictor of HROS for both A (p = .0019) and T (p = .012), the explained variances were 0.49 (A) and 0.35 (T). In cross-validation, 97 percent of the 95 percent prediction intervals crossed the equivalence line, and the direction of predicted HROS agreed with observed HROS in 82 percent (A) and 76 percent (T). Results were robust in sensitivity and subgroup analyses. Conclusions: This meta-analysis suggests that the trial-level treatment effect on PFS is significantly associated with the trial-level treatment effect on OS. However, prediction of OS based on PFS is surrounded with uncertainty.
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