Investigating heterogeneity in an individual patient data meta-analysis of time to event outcomes

2005 ◽  
Vol 24 (9) ◽  
pp. 1307-1319 ◽  
Author(s):  
Catrin Tudur Smith ◽  
Paula R. Williamson ◽  
Anthony G. Marson
Keyword(s):  
Individual Patient Data ◽  
Meta Analysis ◽  
Patient Data ◽  
Time To Event

scholarly journals Mortality in trials on transcatheter aortic valve implantation versus surgical aortic valve replacement: a pooled meta-analysis of Kaplan–Meier-derived individual patient data

2020 ◽  
Vol 58 (2) ◽  
pp. 221-229 ◽  
Author(s):  
Fabio Barili ◽  
Nicholas Freemantle ◽  
Alberto Pilozzi Casado ◽  
Mauro Rinaldi ◽  
Thierry Folliguet ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Patient Data ◽  
Time Varying ◽  
Time To Event ◽  
Surgical Aortic Valve Replacement ◽  
Transcatheter Aortic Valve ◽  
Kaplan Meier ◽  
Valve Implantation

Abstract OBJECTIVES This meta-analysis of Kaplan–Meier-estimated individual patient data was designed to evaluate the effects of transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR) on the long-term all-cause mortality rate, to examine the potential time-varying effect and to model their hazard ratios (HRs) over time. Moreover, we sought to compare traditional meta-analytic tools and estimated individual patient data meta-analyses. METHODS Trials comparing TAVI versus SAVR were identified through Medline, Embase, Cochrane databases and specialist websites. The primary outcome was death from any cause at follow-up. Enhanced secondary analyses of survival curves were performed estimating individual patient time-to-event data from published Kaplan–Meier curves. Treatments were compared with the random effect Cox model in a landmark framework and fully parametric models. RESULTS We identified 6 eligible trials that included 6367 participants, randomly assigned to undergo TAVI (3252) or SAVR (3115). According to the landmark analysis, the incidence of death in the first year after implantation was significantly lower in the TAVI group [risk-profile stratified HR 0.85, 95% confidence interval (CI) 0.73–0.99; P = 0.04], whereas there was a reversal of the HR after 40 months (risk-profile stratified HR 1.31, 95% CI 1.01–1.68; P = 0.04) favouring SAVR over TAVI. This time-varying trend of HRs was also confirmed by a fully parametric time-to-event model. Traditional meta-analytic tools were shown to be biased because they did not intercept heterogeneity and the time-varying effect. CONCLUSIONS The mortality rates in trials of TAVI versus SAVR are affected by treatments with a time-varying effect. TAVI is related to better survival in the first months after implantation whereas, after 40 months, it is a risk factor for all-cause mortality.

Meta-analysis when only the median survival times are known: A comparison with individual patient data results

2005 ◽  
Vol 21 (1) ◽  
pp. 119-125 ◽  
Author(s):  
Stefan Michiels ◽  
Pascal Piedbois ◽  
Sarah Burdett ◽  
Nathalie Syz ◽  
Lesley Stewart ◽  
...  
Keyword(s):  
Median Survival ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Survival Rates ◽  
Patient Data ◽  
Survival Times ◽  
Time To Event ◽  
Sufficient Detail ◽  
Meta Analyses ◽  
Surrogate Measures

Background:The hazard ratio (HR) is the most appropriate measure for time to event outcomes such as survival. In systematic reviews, HRs can be calculated either from the raw trial data obtained as part of an individual patient data (IPD) meta-analysis or from the appropriate trial-level summary statistics. However, the information required for the latter are seldom reported in sufficient detail to allow reviewers to calculate HRs. In contrast, the median survival and survival rates at specific time points are frequently presented. We aimed to evaluate retrospectively the performance of meta-analyses using median survival times and survival rates by comparing them with meta-analyses using IPD to calculate HRs.Methods:IPD from thirteen published meta-analyses (MAs) in cancers with high mortality rates were used. Median survival and survival rates were calculated from the IPD rather than taken from publications so that the same trials, patients, and extended follow-up are used in each analysis.Results and Conclusions:We show that using median survival times or survival rates at a particular point in time are not reasonable surrogate measures for meta-analyses of survival outcomes and that, wherever possible, HRs should be calculated. Individual trial publications reporting on time to event outcomes, therefore, should provide more detailed statistical information, preferably logHRs and their variances, or their estimators.

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