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Multivariate meta-analysis model for the difference in restricted mean survival times.

ABSTRACT: In randomized controlled trials (RCTs) with time-to-event outcomes, the difference in restricted mean survival times (RMSTD) offers an absolute measure of the treatment effect on the time scale. Computation of the RMSTD relies on the choice of a time horizon, $\tau$. In a meta-analysis, varying follow-up durations may lead to the exclusion of RCTs with follow-up shorter than $\tau$. We introduce an individual patient data multivariate meta-analysis model for RMSTD estimated at multiple time horizons. We derived the within-trial covariance for the RMSTD enabling the synthesis of all data by borrowing strength from multiple time points. In a simulation study covering 60 scenarios, we compared the statistical performance of the proposed method to that of two univariate meta-analysis models, based on available data at each time point and based on predictions from flexible parametric models. Our multivariate model yields smaller mean squared error over univariate methods at all time points. We illustrate the method with a meta-analysis of five RCTs comparing transcatheter aortic valve replacement (TAVR) with surgical replacement in patients with aortic stenosis. Over 12, 24, and 36 months of follow-up, those treated by TAVR live 0.28 [95% confidence interval (CI) 0.01 to 0.56], 0.46 (95% CI $-$0.08 to 1.01), and 0.79 (95% CI $-$0.43 to 2.02) months longer on average compared to those treated by surgery, respectively.

SUBMITTER: Weir IR

PROVIDER: S-EPMC7846118 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Multivariate meta-analysis model for the difference in restricted mean survival times.

Weir Isabelle R IR Tian Lu L Trinquart Ludovic L

Biostatistics (Oxford, England) 20210101 1

In randomized controlled trials (RCTs) with time-to-event outcomes, the difference in restricted mean survival times (RMSTD) offers an absolute measure of the treatment effect on the time scale. Computation of the RMSTD relies on the choice of a time horizon, $\tau$. In a meta-analysis, varying follow-up durations may lead to the exclusion of RCTs with follow-up shorter than $\tau$. We introduce an individual patient data multivariate meta-analysis model for RMSTD estimated at multiple time hori ...[more]

PMID: 31175828

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Project description:Background/aims Non-inferiority trials with time-to-event outcomes are becoming increasingly common. Designing non-inferiority trials is challenging, in particular, they require very large sample sizes. We hypothesized that the difference in restricted mean survival time, an alternative to the hazard ratio, could lead to smaller required sample sizes. Methods We show how to convert a margin for the hazard ratio into a margin for the difference in restricted mean survival time and how to calculate the required sample size under a Weibull survival distribution. We systematically selected non-inferiority trials published between 2013 and 2016 in seven major journals. Based on the protocol and article of each trial, we determined the clinically relevant time horizon of interest. We reconstructed individual patient data for the primary outcome and fit a Weibull distribution to the comparator arm. We converted the margin for the hazard ratio into the margin for the difference in restricted mean survival time. We tested for non-inferiority using the difference in restricted mean survival time and hazard ratio. We determined the required sample size based on both measures, using the type I error risk and power from the original trial design. Results We included 35 trials. We found evidence of non-proportional hazards in five (14%) trials. The hazard ratio and the difference in restricted mean survival time were consistent regarding non-inferiority testing, except in one trial where the difference in restricted mean survival time led to evidence of non-inferiority while the hazard ratio did not. The median hazard ratio margin was 1.43 (Q1-Q3, 1.29-1.75). The median of the corresponding margins for the difference in restricted mean survival time was -21?days (Q1-Q3, -36 to -8) for a median time horizon of 2.0?years (Q1-Q3, 1-3?years). The required sample size according to the difference in restricted mean survival time was smaller in 71% of trials, with a median relative decrease of 8.5% (Q1-Q3, 0.4%-38.0%). Across all 35 trials, about 25,000 participants would have been spared from enrollment using the difference in restricted mean survival time compared to hazard ratio for trial design. Conclusion The margins for the hazard ratio may seem large but translate to relatively small differences in restricted mean survival time. The difference in restricted mean survival time offers meaningful interpretation and can result in considerable reductions in sample size. Restricted mean survival time-based measures should be considered more widely in the design and analysis of non-inferiority trials with time-to-event outcomes.

Project description:OBJECTIVES:To use restricted mean survival time, which summarizes treatment effects in terms of event-free time over a fixed time period, to evaluate the benefit of pravastatin therapy for primary prevention of cardiovascular disease in older adults. DESIGN:Secondary analysis of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial-Lipid-Lowering Trial (ALLHAT-LLT). SETTING:Ambulatory setting. PARTICIPANTS:Individuals aged 65 and older (mean aged 71, 49% female) free of cardiovascular disease (N=2,867). INTERVENTION:Pravastatin 40 mg/d (n=1,467) versus usual care (n=1,400). MEASUREMENTS:We estimated the difference in RMST for total and coronary heart disease (CHD)-free survival between the pravastatin and usual care groups over the 6-year trial period and used parametric survival models to estimate RMST differences projected over 10 years. RESULTS:Over 6 years, individuals treated with pravastatin lived (RMST 2,008.1 days), on average, 33.7 fewer days than those receiving usual care (RMST 2,041.8 days) (difference -33.7 days, 95% confidence interval (CI)=-67.0 to -0.5 days, p=.047). Pravastatin-treated individuals lived RMST 2,088.1 days), on average, 18.7 more days free of CHD over 6 years than those receiving usual care (RMST 2,069.4 days), but this difference was not statistically significant (difference 18.7 days, 95% CI=-10.4-47.8 days, p=.21). The 10-year projection showed that pravastatin-treated individuals would live 108.1 fewer days (95% CI=-204.5 to -14.1, p=.03) than those receiving usual care, although treated individuals would gain 77.9 days (95% CI=3.8-159.6, p=.046) of CHD-free survival. CONCLUSION:RMST provides an intuitive and explicit way to express the effect of pravastatin therapy on CHD-free and overall survival in older adults free of cardiovascular disease. This measure allows a more personalized interpretation than hazard ratios of the benefits and risks of a medical intervention for decision-making.

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Multivariate meta-analysis model for the difference in restricted mean survival times.

Publications

Multivariate meta-analysis model for the difference in restricted mean survival times.

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