Objective: To demonstrate how a researcher can investigate the appropriateness of a published comorbidity summary measure for use with a given sample.
Data source: Surveillance, Epidemiology, and End Results linked to Medicare claims data.
Study design: We examined Kaplan-Meier estimated survival curves for four diseases within strata of a comorbidity summary measure, the Charlson Comorbidity Index.
Data collection: We identified individuals with early-stage kidney cancer diagnosed from 1995 to 2009. We recorded comorbidities present in the year before diagnosis.
Principal findings: The use of many comorbidity summary measures is valid under appropriate conditions. One condition is that the relationships of the comorbidities with the outcome of interest in a researcher's own population are comparable to the relationships in a published algorithm's population. The original comorbidity weights from the Charlson Comorbidity Index seemed adequate for three of the diseases in our sample. We found evidence that the Charlson Comorbidity Index might underestimate the impact of one disease in our sample.
Conclusion: Examination of survival curves within strata defined by a comorbidity summary measure can be a useful tool for determining whether a published method appropriately accounts for comorbidities. A comorbidity score is only as good as those variables included.
Keywords: Comorbidity scores; SEER-Medicare; diagnostics; prognostic balance; prognostic scores.
© Health Research and Educational Trust.