Network meta‐analysis of parametric survival curves
- 1 July 2010
- journal article
- Published by Wiley in Research Synthesis Methods
- Vol. 1 (3-4), 258-271
- https://doi.org/10.1002/jrsm.25
Abstract
To inform health‐care decision‐making, treatments are often compared by synthesizing results from a number of randomized controlled trials. The meta‐analysis may not only be focused on a particular pairwise comparison, but can also include multiple treatment comparisons by means of network meta‐analysis. For time‐to‐event outcomes such as survival, pooling is typically based on the hazard ratio (HR). The proportional hazards assumption that underlies current approaches of evidence synthesis is not only often implausible, but can also have a huge impact on decisions based on differences in expected outcomes, such as cost‐effectiveness analysis. The application of a constant HR implies the assumption that the treatment only has an effect on one characteristic of the survival distribution, while commonly used survival distributions, like the Weibull distribution, have both a shape and a scale parameter. Instead of using constant HRs, this paper proposes meta‐analysis of treatment effects based on the shape and scale parameters of parametric survival curves. The model for meta‐analysis is extended for network meta‐analysis and illustrated with an example. Copyright © 2011 John Wiley & Sons, Ltd.Keywords
This publication has 22 references indexed in Scilit:
- Evaluating novel agent effects in multiple‐treatments meta‐regressionStatistics in Medicine, 2010
- Estimation and Adjustment of Bias in Randomized Evidence by Using Mixed Treatment Comparison Meta-AnalysisJournal of the Royal Statistical Society Series A: Statistics in Society, 2010
- Efficacy of Melphalan and Prednisone Plus Thalidomide in Patients Older Than 75 Years With Newly Diagnosed Multiple Myeloma: IFM 01/01 TrialJournal of Clinical Oncology, 2009
- Oral melphalan, prednisone, and thalidomide in elderly patients with multiple myeloma: updated results of a randomized controlled trialBlood, 2008
- Meta‐analysis of summary survival curve dataStatistics in Medicine, 2008
- Assessing Evidence Inconsistency in Mixed Treatment ComparisonsJournal of the American Statistical Association, 2006
- Simultaneous comparison of multiple treatments: combining direct and indirect evidenceBMJ, 2005
- Combination of direct and indirect evidence in mixed treatment comparisonsStatistics in Medicine, 2004
- Bayesian Measures of Model Complexity and FitJournal of the Royal Statistical Society Series B: Statistical Methodology, 2002
- Flexible parametric proportional‐hazards and proportional‐odds models for censored survival data, with application to prognostic modelling and estimation of treatment effectsStatistics in Medicine, 2002