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Comorbidity indices: how should they be developed?

In 1970 the term ‘comorbidity’ was introduced by Alvan Feinstein, who defined it as the presence of ‘any distinct additional clinical entity that . . . may occur during the clinical course of a patient who has the index disease under study.’ He noted that patients who are similar in terms of diagnosis, demography, and anatomy may have different outcomes, based on major differences in comorbid disease, and that it was necessary to take this into account when reporting vital statistics (e.g. mortality rates, causes of death) and in analyzing the results of therapeutic trials. Valderas et al. state that comorbidity has been defined in three ways: (1) to indicate conditions that exist simultaneously but independently with another condition (stroke and diabetes); (2) to refer to disorders that either cause the index condition or are caused by it (cerebral palsy [CP] and osteoporosis); and (3) in reference to conditions that exist simultaneously, irrespective of their causal relationship (CP and depression). In these situations, comorbidity is defined in relation to an index condition. Another term, multimorbidity, refers to the coexistence of a number of acute or chronic conditions, without designating any one as the index condition. This latter term is often used in geriatrics, where the identification of an index condition may be neither obvious nor useful. These distinctions may appear to be of academic interest only, but they dictate what should or should not be included in any scale. Whitney and Kamdar report on the development of a new comorbidity index for adults with CP: the Whitney Comorbidity Index (WCI). It is a CP-specific index, based on data from an administrative database, used primarily for billing purposes. Of note, the criterion for selecting a condition to be in the scale was its ability to predict 2-year mortality. The article raises a number of issues. What do we mean by comorbidity? What is the purpose of such an index? How should it be constructed? For what questions should it be used and should it not be used? Comorbidity indices can serve many purposes. Feinstein proposed using them in the context of research; to exclude patients with associated diseases from clinical trials, or as covariates during the analysis. Similarly, they are important in highlighting problems in sampling that may lead to artefactual associations among disorders. From a clinical perspective, they can be used to predict mortality, as is the case with the WCI and the Charlson Comorbidity Index, or to assist in designing treatments for individual patients. As with the definition of comorbidity, the ultimate use of an index will influence the conditions that are included and excluded. The authors based their scale on clinical theory, a review of the literature, and two existing comorbidity indices. As mentioned, though, the list of conditions was guided by two considerations: they must predict 2-year mortality and they had to exist in an administrative database. This meant that they excluded disorders that are prevalent in CP but not associated with mortality (e.g. psychoses, sleep disorder, anxiety); had poor sensitivity or specificity for claims-based research (obesity); were not available in insurance claims data (gross motor function); or that require the judgement of an adult CP specialist (fatigue). Thus, while the WCI may prove useful for predicting mortality, it remains an open question whether it can be used for other purposes, such as choosing the optimal treatment for a specific patient; as a stratification variable in participant allocation to groups; or as a covariate in the analysis of treatment group differences.