Abstract
Weights assigned to comorbidities in predicting mortality may vary based on the type of index disease and advances in the management of comorbidities. We aimed to develop a modified version of the Charlson Comorbidity Index (CCI) using an Asian nationwide database (mCCI-A), enabling the precise prediction of mortality rates in this population. The main data source used in this study was the National Health Insurance Service-National Sample Cohort (NHIS-NSC) obtained from the National Health Insurance database, which includes health insurance claims filed between January 1, 2002, and December 31, 2013, in Korea. Of the 1,025,340 individuals included in the NHIS-NSC, 570,716 patients who were hospitalized at least once were analyzed in this study. In total, 399,502 patients, accounting for 70% of the cohort, were assigned to the development cohort, and the remaining patients (n = 171,214) were assigned to the validation cohort. The mCCI-A scores were calculated by summing the weights assigned to individual comorbidities according to their relative prognostic significance determined by a multivariate Cox proportional hazard model. The modified index was validated in the same cohort. The Cox proportional hazard model provided reassigned severity weights for 17 comorbidities that significantly predicted mortality. Both the CCI and mCCI-A were correlated with mortality. However, compared with the CCI, the mCCI-A showed modest but significant increases in the c statistics. According to the analyses using continuous net reclassification improvement, the mCCI-A improved the net mortality risk reclassification by 44.0% (95% confidence intervals (CI), 41.6–46.5; p < 0.001). The mCCI-A facilitates better risk stratification of mortality rates in Korean inpatients than the CCI, suggesting that the mCCI-A may be a preferable index for use in clinical practice and statistical analyses in epidemiological studies.
Highlights
Weights assigned to comorbidities in predicting mortality may vary based on the type of index disease and advances in the management of comorbidities
The recalibration and validation of comorbidities indices have been performed in various disease group such as the index of coexistent d isease[7], Davies index[8], Khan index[9], a modified version of the Charlson Comorbidity Index (CCI) in incident hemodialysis patients[10] and a modified version of the CCI in incident peritoneal dialysis patients[11]
The present study aimed to develop a modified version of the Charlson Comorbidity Index using an Asian nationwide database that reflected the recent changes of mortality due to the development of medical technology and the difference in prevalence of diseases from racial differences and to compare its performance with the original CCI
Summary
Weights assigned to comorbidities in predicting mortality may vary based on the type of index disease and advances in the management of comorbidities. In 1984, Charlson et al identified the clinical conditions to be included in the index by reviewing 559 hospital charts of patients admitted to medical services at a single hospital and assessed the associations of these comorbidities with the 1-year all-cause m ortality[2] The ability of this index to predict mortality has been validated in various disease subgroups, including cancer[3], renal disease4, stroke[5] and intensive care[6]. Because the management of inpatients and their comorbidities has advanced significantly over the past 30 years, the contribution of comorbidities to the mortality rate has likely changed This index is not suitable for predicting long-term outcomes in general hospitalized patients because in the development of the CCI, only a small sample and the one-year mortality rate were considered. The present study aimed to develop a modified version of the Charlson Comorbidity Index (mCCIA) using an Asian nationwide database that reflected the recent changes of mortality due to the development of medical technology and the difference in prevalence of diseases from racial differences and to compare its performance with the original CCI
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