Development, Validation, and Dissemination of a Breast Cancer Recurrence Detection and Timing Informatics Algorithm.

ABSTRACT:

Background

This study developed, validated, and disseminated a generalizable informatics algorithm for detecting breast cancer recurrence and timing using a gold standard measure of recurrence coupled with data derived from a readily available common data model that pools health insurance claims and electronic health records data.

Methods

The algorithm has two parts: to detect the presence of recurrence and to estimate the timing of recurrence. The primary data source was the Cancer Research Network Virtual Data Warehouse (VDW). Sixteen potential indicators of recurrence were considered for model development. The final recurrence detection and timing models were determined, respectively, by maximizing the area under the ROC curve (AUROC) and minimizing average absolute error

SUBMITTER: Ritzwoller DP 

PROVIDER: S-EPMC5972574 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature