The role of covariates in estimating treatment effects and risk in long-term clinical trials

This paper reviews previously published work showing that the impact of including covariates in models used to estimate the magnitude of treatment effects in long-term clinical trials is different from what would be predicted from results for the normal linear model. Typically, models with and without covariates cannot simultaneously be valid. A case is made for the use of data from clinical trials to model the future risk and potential benefits of treatment in individual subjects. The methods and results are illustrated using data from the West of Scotland Coronary Prevention Study.