One of the prognostic factors most highly associated with ovarian cancer survival is response to initial chemotherapy. Current prediction models of chemo-response built with comprehensive molecular datasets, like The Cancer Genome Atlas (TCGA), could be improved by including clinical and outcomes data designed to study response to treatment. The objective of this study was to create a prediction model of ovarian cancer chemo-response using clinical-pathological features, and to compare its performance with a similar TCGA clinical model.
Ovarian cancer, serous epithelial ovarian cancer, chemotherapy, chemotherapy response, prediction model, clinical predictors, TCGA
The authors report no conflict of interest.
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