The choice of cancer treatment based on covariate information.

This paper is concerned with methods for choosing optimal treatment for particular patients; the central idea is that information contained in covariates may be useful for this kind of decision making. For each patient estimated conditional survivor functions for each mode of treatment may be compared and the optimal treatment may be defined as the one providing higher predicted survival. Regression survival models form the basis for a pertinent statistical decision rule, and a procedure for retrospective validation of such a rule is given. The usefulness of the proposed approach is illustrated with an application to the treatment of patients with cancer of cervix uteri. The results of data analysis suggest that the choice of optimal treatment based on covariate information is of considerable promise for practical use.