Potential misinterpretations caused by collapsing upper categories of comorbidity indices: An illustration from a cohort of older breast cancer survivors

Abstract

BACKGROUND Comorbidity indices summarize complex medical histories into concise ordinal scales, facilitating stratification and regression in epidemiologic analyses. Low subject prevalence in the highest strata of a comorbidity index often prompts combination of upper categories into a single stratum ('collapsing'). OBJECTIVE We use data from a breast cancer cohort to illustrate potential inferential errors resulting from collapsing a comorbidity index. METHODS Starting from a full index (0, 1, 2, 3, and ≥4 comorbidities), we sequentially collapsed upper categories to yield three collapsed categorizations. The full and collapsed categorizations were applied to analyses of (1) the association between comorbidity and all-cause mortality, wherein comorbidity was the exposure; (2) the association between older age and all-cause mortality, wherein comorbidity was a candidate confounder or effect modifier. RESULTS COLLAPSING THE INDEX ATTENUATED THE ASSOCIATION BETWEEN COMORBIDITY AND MORTALITY (RISK RATIO, FULL VERSUS DICHOTOMIZED CATEGORIZATION: 4.6 vs 2.1), reduced the apparent magnitude of confounding by comorbidity of the age/mortality association (relative risk due to confounding, full versus dichotomized categorization: 1.14 vs 1.09), and obscured modification of the association between age and mortality on both the absolute and relative scales. CONCLUSIONS Collapsing categories of a comorbidity index can alter inferences concerning comorbidity as an exposure, confounder and effect modifier.