Instrumental variable estimation in semi-parametric additive hazards models.

Instrumental variable methods allow unbiased estimation in the presence of unmeasured confounders when an appropriate instrumental variable is available. Two-stage least-squares and residual inclusion methods have recently been adapted to additive hazard models for censored survival data. The semi-parametric additive hazard model which can include time-independent and time-dependent covariate effects is particularly suited for the two-stage residual inclusion method, since it allows direct estimation of time-independent covariate effects without restricting the effect of the residual on the hazard. In this article, we prove asymptotic normality of two-stage residual inclusion estimators of regression coefficients in a semi-parametric additive hazard model with time-independent and time-dependent covariate effects. We consider the cases of continuous and binary exposure. Estimation of the conditional survival function given observed covariates is discussed and a resampling scheme is proposed to obtain simultaneous confidence bands. The new methods are compared to existing ones in a simulation study and are applied to a real data set. The proposed methods perform favorably especially in cases with exposure-dependent censoring.

Performance of different clinical trial designs to evaluate treatments during an epidemic.

In the 2013-2016 west Africa outbreak of Ebola Virus Disease (EVD), most of the planned clinical trials failed to reach a conclusion within the time frame of the epidemic. The performance of clinical trial designs for the evaluation of one or more experimental treatments in the specific context of an ongoing epidemic with changing case fatality rates (CFR) and unpredictable case numbers is unclear. We conduct a comprehensive evaluation of commonly used two- and multi-arm clinical trial designs based on real data, which was recorded during the 2013-16 EVD epidemic in west Africa. The primary endpoint is death within 14 days of hospitalization. The impact of the recruitment start times relative to the time course of the epidemic on the operating characteristics of the clinical trials is analysed. Designs with frequent interim analyses with the possibility of early stopping are shown to outperform designs with only a single analysis not only in terms of average time to conclusion and average sample size, but also in terms of the probability of reaching any conclusion at all. Historic control designs almost always result in substantially inflated false positive rates, when the case fatality rate changes over time. Response-adaptive randomization may be a compromise between the goal of scientific validity and the ethical goal of minimizing the number of patients allocated to ineffective treatments.