Computational approaches to support comparative analysis of multiparametric tests: Modelling versus Training.

ABSTRACT: Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX® (Genomic Health.), Prosigna™ (NanoString Technologies, Inc.), MammaPrint® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly com

SUBMITTER: Bartlett JMS 

PROVIDER: S-EPMC7470374 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature