UK Medical Research Council
Development and practical application of landmarking in studies of time-varying exposures and survival
4 years (April 2015-March 2019)
The aim of this work is to develop of statistical methods which enable us to gain understanding of the effects of time-varying exposures on survival, for example to make predictions of individual features on survival, to gain insight into biological mechanisms or to inform treatment decisions. I am interested especially in methods that enable us to make best use of data such as electronic health records, which contain patient-level variables recorded longitudinally.
My research focuses on (1) making dynamic predictions of survival to a future time horizon based on an individual’s measurements up to a given time; (2) estimating the causal effects on survival of patterns in time-varying exposures, including continuous and binary exposures and intermediate events, taking into account time-varying confounding. These investigations have to date required quite different complex statistical methods. A unified approach does not exist but is essential to enable applications from a wide range of researchers. In this project I am developing statistical methods based on an approach called ‘landmarking’ to provide a unified and intuitive approach. A key advantage of landmarking is that it is based on the familiar method of Cox regression modelling. However, landmarking has so far been limited to dynamic prediction and by lack of extensions to accommodate practical constraints.
The methods developed are being partly motivated by and also applied to data from the US and UK Cystic Fibrosis Patient Registries.