Original articleHow to measure comorbidity: a critical review of available methods
Introduction
As early as 1970, Alvan Feinstein noted that “the failure to classify and analyze comorbid diseases has led to many difficulties in medical statistics” [1], because comorbidity can affect the moment of detection, prognosis, therapy, and outcome. Comorbidity can play an important role in different types of research. In etiologic studies the relationship between comorbid conditions and an index disease can be investigated. Comorbidity can be the cause or the consequence of an index disease. It is also possible that the index disease and the comorbid conditions share the same risk factors. In diagnostic studies, comorbidity can obscure the relationship between the test under study and the index disease. In these fields of research it might be particularly useful to analyze every disease as a separate variable, to gain insight into the relationship between individual diseases and the index disease at issue. However, this method is not feasible in small studies, because of reduced efficiency of the analysis. Randomized controlled trials (RCTs) and prognostic studies can also be complicated by comorbidity. Comorbidity can either act as a confounder, threatening the internal validity, or as an effect modifier, threatening the internal and external validity of the study. For these purposes an efficient method is needed to measure comorbidity.
There are four important reasons for measuring comorbidity. The first reason is to be able to correct for confounding, and thus improve the internal validity of studies. The second reason is to be able to identify effect modification. A third reason is the desire to use comorbidity as a predictor of study outcome or natural history. Finally, a comprehensive comorbidity measure, including many cooccurring comorbid conditions in one valid variable, is needed for reasons of statistical efficiency.
Because an overview of available methods to measure comorbidity is still lacking, the following research question was formulated: Which methods are available for measuring comorbidity that can be used in RCTs and prognostic studies?
Section snippets
Methods
A search was made in the electronic databases of Medline (from January 1966 to September 2000) and Embase (from January 1988 to September 2000). The following keywords were used to identify potentially useful articles: comorbidity, multimorbidity, and coexisting disease. Articles in which the focus was on comorbidity assessment or comorbidity was an important (prognostic) variable were considered for inclusion. In the literature several terms are being used in comorbidity research. Also, there
Results
Thirteen different methods to assess comorbidity were identified and presented in alphabetical order in Table 1: one disease count and 12 indexes. Data on content and predictive validity were available for all measures, while data on construct validity were available for nine methods, data on concurrent validity for eight methods, data on interrater reproducibility for eight methods, and data on intrarater reliability for three methods.
The Burden of Disease (BOD) index [4] consists of 59
Discussion
Measuring comorbidity is an aspect of research that is receiving increasing attention in the literature. Several authors have discussed and compared the use of various selected methods to measure comorbidity 50, 51, 52, 53. This review describes methods that can be used to measure comorbidity in clinical research, without limiting the focus to certain index diseases or diagnostic groups. Thirteen different methods were identified. Six indexes used a carefully developed list of clearly defined
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