PhD Defence of Kelly Van Lancker

28-05-2021 from 17:30 to 19:30
digital: bongo
Kelly Van Lancker
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PhD Defence of Kelly Van Lancker on Optimizing treatment effect estimation in randomized trials by leveraging baseline covariates and early read-outs.


While the randomized controlled trial (RCT) is the gold standard for causal inference, its application in medical practice is inefficient. This is because many published analyses of RCTs ignore information in patient characteristics (e.g., age, BMI,gender, …).

The aim of this thesis it to develop approaches for inclusion of additional information in estimating treatment effects in randomized trials. We hereby first focus on improving interim analyses of clinical trials. We develop a framework that allows earlier interim decision making by incorporating patient characteristics measured before and during the trial. This time gain results in a lower expected number of recruited patients in case of stopping for futility, such that fewer patients receive the futile regimen. We moreover shed light on the estimation of the effect of dose switching, where we can no longer solely rely on randomization. Valid estimation of the causal effect of interest therefore requires appropriate adjustment for confounding. Finally, the desire to adjust for baseline variables in the first two parts of the thesis creates the need to use the collected data to guide the selection of variables and a statistical model. The research therefore involves an illustration of how related methods can also be used to obtain valid inference after variable selection for time-to-event-data.

Due to the COVID-19 outbreak the public defence will be held online through Bongo. You can attend by accessing the following link: