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.
journal_name
Clin Epidemioljournal_title
Clinical epidemiologyauthors
Ahern TP,Bosco JL,Silliman RA,Yood MU,Field TS,Wei F,Lash TLdoi
10.2147/clep.s5757subject
Has Abstractpub_date
2009-08-09 00:00:00pages
93-100issn
1179-1349journal_volume
1pub_type
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