Development and Validation of the Modified Charlson Comorbidity Index in Incident Peritoneal Dialysis Patients: A National Population-Based Approach.
♦ BACKGROUND: The utility of applying the Charlson comorbidity index (CCI) to peritoneal dialysis (PD) patients is disputed because the relative weight of each comorbidity in PD patients may be different from those in other chronic diseases. We aimed to develop and validate a modified CCI in incident PD patients (mCCI-IPD) for better risk stratification and prediction of mortality. ♦ METHODS: The mCCI-IPD was developed using data from all Korean adult incident PD patients between 2005 and 2008 (n = 7,606). Multivariate Cox regression was used to determine new weights for the individual comorbidities in the CCI. The prognostic performance of the mCCI-IPD was validated in an independent cohort (n = 664) through c-statistics and continuous net reclassification improvement (cNRI). ♦ RESULTS: A total of 75.5% of the patients in the development cohort had 1 or more comorbidities. The Cox proportional hazards model provided reassigned severity weights for the 11 comorbidities that significantly predicted mortality. In the validation cohort, the CCI and mCCI-IPD scores were both correlated with survival and showed no differences in their c-statistics. However, multivariate analyses using cNRI revealed that the mCCI-IPD provided a 38.2% improvement in mortality risk assessment compared with the CCI (95% confidence interval [CI], 15.3 - 61.0; p < 0.001). These significant reclassification improvements were observed consistently in subjects with events (cNRIEvent, 28.2% [95% CI, 6.9 - 49.5; p = 0.009]) and without events (cNRINon-event, 10.0% [95% CI, 1.7 - 18.2; p = 0.019]). ♦ CONCLUSIONS: Compared with the CCI, the mCCI-IPD showed better performance in mortality prediction for incident PD patients. Therefore, this tool may be used as a preferred index for statistical analysis and clinical decision-making.
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
Hyunjeong
H
Cho
Department of Dental Hygiene, College of Health Science, Eulji University, Gyeonggi-do, Korea.
Myoung-Hee
MH
Kim
Department of Internal Medicine, Dongguk University Gyeongju Hospital, Gyeongju-si, Gyeongsangbuk-do, Korea.
Hyo Jin
HJ
Kim
Department of Internal Medicine, Dongguk University Ilsan Hospital, Gyeonggi-do, Korea.
Jae Yoon
JY
Park
Department of Internal Medicine and Ewha Medical Research Institute, School of Medicine, Ewha Womans University, Seoul, Korea.
Dong-Ryeol
DR
Ryu
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
Hajeong
H
Lee
Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea.
Jung Pyo
JP
Lee
Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea.|Kidney Research Institute, Seoul National University, Seoul, Korea.
Chun-Soo
CS
Lim
Department of Public Health, Graduate School, Korea University, Seoul, Korea.
Kyoung Hoon
KH
Kim
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.|Kidney Research Institute, Seoul National University, Seoul, Korea.
Kook-Hwan
KH
Oh
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.|Kidney Research Institute, Seoul National University, Seoul, Korea.
Kwon Wook
KW
Joo
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.|Kidney Research Institute, Seoul National University, Seoul, Korea.
Yon Su
YS
Kim
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea dkkim73@gmail.com.|Kidney Research Institute, Seoul National University, Seoul, Korea.
Dong Ki
DK
Kim
D000328:Adult; D000367:Age Factors; D000368:Aged; D002423:Cause of Death; D015331:Cohort Studies; D015897:Comorbidity / Q000639:trends*; D016208:Databases, Factual; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D007676:Kidney Failure, Chronic / Q000175:diagnosis / Q000401:mortality / Q000628:therapy*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010530:Peritoneal Dialysis / Q000009:adverse effects / Q000379:methods / Q000401:mortality*; D016016:Proportional Hazards Models; D056910:Republic of Korea; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D012737:Sex Factors
Comorbidity; index; mortality; peritoneal dialysis