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.