Development and validation of a claims-based approach to proxy ECOG performance status across ten tumor groups
Abstract
Aim: To develop a claims-based prediction model of poor performance status (PS) in commercially insured and Medicare supplemental beneficiaries with cancer. Patients & methods: 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. Results: The study included 8442 patients 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. Conclusion: 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.
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© 2018 Future Medicine Ltd.
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Received: 12 June 2017
Accepted: 24 August 2017
Published online: 13 March 2018
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Development and validation of a claims-based approach to proxy ECOG performance status across ten tumor groups. (2018) Journal of Comparative Effectiveness Research. DOI: 10.2217/cer-2017-0040
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