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Progression-free survival as a surrogate endpoint in advanced breast cancer

Published online by Cambridge University Press:  01 October 2008

Rebecca A. Miksad
Affiliation:
Harvard Medical School
Vera Zietemann
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Raffaella Gothe
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Ruth Schwarzer
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Annette Conrads-Frank
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Petra Schnell-Inderst
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Björn Stollenwerk
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Uwe Siebert
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology and Harvard Medical School

Abstract

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.

Type
GENERAL ESSAYS
Copyright
Copyright © Cambridge University Press 2008

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