Downsizing Multigenic Predictors of the Response to Preoperative Chemotherapy in Breast Cancer

We present a method for designing efficient multigenic predictors with few probes and its application to the prediction of the response to preoperative chemotherapy in breast cancer. In this study, each DNA probe was regarded as an elementary predictor of the response to the chemotherapy and the probes which were selected performed a faithful sampling of the training dataset. In a first stage of the study, the prediction delivered by a multigenic predictor was that of the majority of the elementary predictions of its probes. For the data set at hand, the best majority decision predictor (MD predictor) had 30 probes. It significantly outperformed the best predictor previously published, which was designed on probes that had been selected by p-value of a t-test. In a second stage, the majority decision was replaced by a support vector machine (SVM) with linear kernel. With the same set of probes, the performances of the SVM predictor were slightly better for both training and testing set...

• Type: Journal
• Year: 2008
• Where: KES
• Authors: René Natowicz, Roberto Incitti, Roman Rouzier, Arben Çela, Antônio de Pádua Braga, Euler G. Horta, Thiago S. Rodrigues, Marcelo Azevedo Costa
• Keywords: Efficient Multigenic Predictors, Information Technology, KES 2008, MD Predictor, Multigenic Predictor