Development and validation of a claims-based approach to proxy ECOG performance status across ten tumor groups

Abstract

To develop a claims-based prediction model of poor performance status (PS) in commercially insured and Medicare supplemental beneficiaries with cancer. Retrospective analysis was conducted of electronic medical records (EMR) from community oncology practices linked to MarketScan claims. Multivariable logistic regression predicted PS scores from the EMR using claims-based diagnostic and procedure codes. The study included 8442patients diagnosed with cancer from 2007 to 2015. Overall, 8.1% of patients had poor EMR-based PS. Bootstrapping results from the final model showed sensitivity and specificity of approximately 75% with a predicted probability cutpoint=0.078, c-statistic=0.821 and pseudo-R2 =0.25. Patients with poor PS can be identified in claims data. This prediction model enables future studies evaluating cancer treatments and outcomes to account for PS.