  Gene/pathway-based methods are drawing significant attention due to their
usefulness in detecting rare and common variants that affect disease
susceptibility. The biological mechanism of drug responses indicates that a
gene-based analysis has even greater potential in pharmacogenetics. Motivated
by a study from the Vitamin Intervention for Stroke Prevention (VISP) trial, we
develop a gene-trait similarity regression for survival analysis to assess the
effect of a gene or pathway on time-to-event outcomes. The similarity
regression has a general framework that covers a range of survival models, such
as the proportional hazards model and the proportional odds model. The
inference procedure developed under the proportional hazards model is robust
against model misspecification. We derive the equivalence between the
similarity survival regression and a random effects model, which further
unifies the current variance component-based methods. We demonstrate the
effectiveness of the proposed method through simulation studies. In addition,
we apply the method to the VISP trial data to identify the genes that exhibit
an association with the risk of a recurrent stroke. The TCN2 gene was found to
be associated with the recurrent stroke risk in the low-dose arm. This gene may
impact recurrent stroke risk in response to cofactor therapy.
