Patient-specific meta-analysis for risk assessment using multivariate proportional hazards regression

Abstract

We propose a method for assessing an individual patient's risk of a future clinical event using clinical trial or cohort data and Cox proportional hazards regression, combining the information from several studies using meta-analysis techniques. The method combines patient-specific estimates of the log cumulative hazard across studies, weighting by the relative precision of the estimates, using either fixed- or random-effects meta-analysis calculations. Risk assessment can be done for any future patient using a few key summary statistics determined once and for all from each study. Generalizations of the method to logistic regression and linear models are immediate. We evaluate the methods using simulation studies and illustrate their application using real data.

Keywords:

• Cox proportional hazards regression
• meta-analysis
• patient-specific meta-analysis
• risk assessment

Acknowledgements

We are grateful to Jack Cuzick and Chris Wale of Queen Mary, London, UK, and Mitch Dowsett of the Royal Marsden Hospital, London, UK, all from the TransATAC Trialists’ Group, for design considerations and for providing key summary statistics for TransATAC for the example patient-specific meta-analysis calculation. Thanks to Steve Shak, Drew Watson and Carl Yoshizawa of Genomic Health, Inc. for their help and advice.