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Robust Method for Estimating Optimal Treatment Regimes

Biometrics, 2012-12, Vol.68 (4), p.1010-1018 [Peer Reviewed Journal]

2012 The International Biometric Society ;2012, The International Biometric Society ;2012, The International Biometric Society. ;ISSN: 0006-341X ;EISSN: 1541-0420 ;DOI: 10.1111/j.1541-0420.2012.01763.x ;PMID: 22550953 ;CODEN: BIOMA5

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Title:
Robust Method for Estimating Optimal Treatment Regimes
Author: Zhang, Baqun ; Tsiatis, Anastasios A. ; Laber, Eric B. ; Davidian, Marie
Subjects: BIOMETRIC METHODOLOGY ; Biometrics ; biometry ; breast neoplasms ; Breast Neoplasms - epidemiology ; Breast Neoplasms - therapy ; Clinical trials ; Clinical Trials as Topic - methods ; Computer Simulation ; Datasets ; Decision Support Systems, Clinical ; Doubly robust estimator ; Estimation methods ; Estimators ; Female ; Health outcomes ; Humans ; Inverse probability weighting ; Medical treatment ; Models, Statistical ; Observational studies ; Outcome Assessment (Health Care) - methods ; Outcome regression ; Patient care planning ; patients ; Personalized medicine ; Population estimates ; Population mean ; Potential outcomes ; Prevalence ; probability ; Propensity score ; Regression Analysis ; Treatment Outcome
Is Part Of: Biometrics, 2012-12, Vol.68 (4), p.1010-1018
Description: A treatment regime is a rule that assigns a treatment, among a set of possible treatments, to a patient as a function of his/her observed characteristics, hence “personalizing” treatment to the patient. The goal is to identify the optimal treatment regime that, if followed by the entire population of patients, would lead to the best outcome on average. Given data from a clinical trial or observational study, for a single treatment decision, the optimal regime can be found by assuming a regression model for the expected outcome conditional on treatment and covariates, where, for a given set of covariates, the optimal treatment is the one that yields the most favorable expected outcome. However, treatment assignment via such a regime is suspect if the regression model is incorrectly specified. Recognizing that, even if misspecified, such a regression model defines a class of regimes, we instead consider finding the optimal regime within such a class by finding the regime that optimizes an estimator of overall population mean outcome. To take into account possible confounding in an observational study and to increase precision, we use a doubly robust augmented inverse probability weighted estimator for this purpose. Simulations and application to data from a breast cancer clinical trial demonstrate the performance of the method.
Publisher: Malden, USA: Blackwell Publishing Inc
Language: English;French
Identifier: ISSN: 0006-341X
EISSN: 1541-0420
DOI: 10.1111/j.1541-0420.2012.01763.x
PMID: 22550953
CODEN: BIOMA5
Source: MEDLINE
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Robust Method for Estimating Optimal Treatment Regimes

2012 The International Biometric Society ;2012, The International Biometric Society ;2012, The International Biometric Society. ;ISSN: 0006-341X ;EISSN: 1541-0420 ;DOI: 10.1111/j.1541-0420.2012.01763.x ;PMID: 22550953 ;CODEN: BIOMA5

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