Discussion of combining biomarkers to optimize patient treatment recommendations

Kang, Janes and Huang propose an interesting boosting method to combine biomarkers for treatment selection. The method requires modeling the treatment effects using markers. We discuss an alternative method, outcome weighted learning. This method sidesteps the need for modeling the outcomes, and thu...

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Bibliographic Details
Published in:Biometrics 2014-09, Vol.70 (3), p.713-716
Main Authors: Zhao, Ying‐Qi, Kosorok, Michael R
Format: Article
Language:English
Subjects:
Biomarkers
Biomarkers, Tumor - blood
Biometrics
biometry
Biometry - methods
Boosting
Breast Neoplasms - blood
Breast Neoplasms - therapy
Data Interpretation, Statistical
DISCUSSION PAPER
Educational outcomes
Female
Health outcomes
Humans
Logistic regression
Logistics
Machine learning
Male
Medical treatment
Outcome Assessment (Health Care) - methods
Outcome weighted learning
patients
Personalized medicine
Sample size
Simulations
Support vector machine
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Summary:Kang, Janes and Huang propose an interesting boosting method to combine biomarkers for treatment selection. The method requires modeling the treatment effects using markers. We discuss an alternative method, outcome weighted learning. This method sidesteps the need for modeling the outcomes, and thus can be more robust to model misspecification.
ISSN:0006-341X
1541-0420
DOI:10.1111/biom.12189