Enhancing Breast Cancer Recurrence Algorithms Through Selective Use of Medical Record Data.

ABSTRACT:

Background

The utility of data-based algorithms in research has been questioned because of errors in identification of cancer recurrences. We adapted previously published breast cancer recurrence algorithms, selectively using medical record (MR) data to improve classification.

Methods

We evaluated second breast cancer event (SBCE) and recurrence-specific algorithms previously published by Chubak and colleagues in 1535 women from the Life After Cancer Epidemiology (LACE) and 225 women from the Women's Health Initiative cohorts and compared classification statistics to published values. We also sought to improve classification with minimal MR examination. We selected pairs of algorithms-one with high sensitivity/high positive predictive value (PPV) and another with high specif

SUBMITTER: Kroenke CH 

PROVIDER: S-EPMC5943828 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature