|Title||On Estimation of Optimal Treatment Regimes For Maximizing -Year Survival Probability.|
|Publication Type||Journal Article|
|Year of Publication||2017|
|Authors||Jiang, Runchao, Wenbin Lu, Rui Song, and Marie Davidian|
|Journal||J R Stat Soc Series B Stat Methodol|
|Date Published||2017 Sep|
A treatment regime is a deterministic function that dictates personalized treatment based on patients' individual prognostic information. There is increasing interest in finding optimal treatment regimes, which determine treatment at one or more treatment decision points so as to maximize expected long-term clinical outcome, where larger outcomes are preferred. For chronic diseases such as cancer or HIV infection, survival time is often the outcome of interest, and the goal is to select treatment to maximize survival probability. We propose two nonparametric estimators for the survival function of patients following a given treatment regime involving one or more decisions, i.e., the so-called value. Based on data from a clinical or observational study, we estimate an optimal regime by maximizing these estimators for the value over a prespecified class of regimes. Because the value function is very jagged, we introduce kernel smoothing within the estimator to improve performance. Asymptotic properties of the proposed estimators of value functions are established under suitable regularity conditions, and simulations studies evaluate the finite-sample performance of the proposed regime estimators. The methods are illustrated by application to data from an AIDS clinical trial.
|Alternate Journal||J R Stat Soc Series B Stat Methodol|
|Original Publication||On estimation of optimal treatment regimes for maximizing t-year survival probability.|
|PubMed Central ID||PMC5624740|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 CA140632 / CA / NCI NIH HHS / United States
On Estimation of Optimal Treatment Regimes For Maximizing -Year Survival Probability.