Background: Weights assigned to comorbidities to predict mortality may vary based on the type of index disease and advances in the management of comorbidities. We aimed to develop a modified Charlson comorbidity index (CCI) in incident hemodialysis patients (mCCI-IHD), thereby improving risk stratification for mortality. Methods: Data on 24,738 Koreans who received their first hemodialysis treatment between 2005 and 2008 were obtained from the Korean Health Insurance dataset. The mCCI-IHD score were calculated by summing up the weights which were assigned to individual comorbidities according to their relative prognostic significance determined by multivariate Cox proportional hazards model. The modified index was validated in an independent nationwide prospective cohort (n=1,100). Results: The Cox proportional hazards model revealed that all comorbidities in the CCI except ulcers significantly predicted mortality. Thus, the mCCI-IHD included 14 comorbidities with reassigned severity weights. In the validation cohort, both the CCI and the mCCI-IHD were correlated with mortality. However, the mCCI-IHD showed modest but significant increases in c statistics compared with the CCI at 6 months and 1 year. The analyses using continuous net reclassification improvement revealed that the mCCI-IHD improved net mortality risk reclassification by 24.6% (95% CI, 2.5-46.7; P=0.03), 26.2% (95% CI, 1.0-51.4; P=0.04) and 42.8% (95% CI, 4.9-80.8; P=0.03) with respect to the CCI at 6 months and 1 and 2 years, respectively. Conclusions: The mCCI-IHD facilitates better risk stratification for mortality in incident hemodialysis patients compared with the CCI, suggesting that it may be a preferred index for use in clinical practice and the statistical analysis of epidemiological studies.
Bibliographical noteFunding Information:
This work was supported by a grant from the Korean Healthcare Technology R&D Project, Ministry for Health and Welfare, Republic of Korea (HI10C2020).
© 2015 Park et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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