TY - JOUR
T1 - A comorbidity index for mortality prediction in Chinese patients with ESRD receiving hemodialysis
AU - Chen, Jinn Yang
AU - Tsai, Shin Hung
AU - Chuang, Pei Hung
AU - Chang, Chia Hao
AU - Chuang, Chiao Lin
AU - Chen, Hui Ling
AU - Chen, Ping Ling
PY - 2014/3/7
Y1 - 2014/3/7
N2 - Background and objectives Chinese patients with ESRD have different comorbidity patterns than white patients with ESRD and require a validated comorbidity index. The objective of this study was to develop a new index for mortality prediction in 2006-2009 Taiwanese incident hemodialysis patients. Design, setting, participants, & measurements Data were retrieved from 2005 to 2010 Taiwan National Health Insurance claimrecords, and follow-upwas available until December 31, 2010. The same comorbid conditions as the US Renal Data System (USRDS) index that occurred during a 12-month period from 9 months before to 3 months after dialysis initiation were used to construct the index. Integer weight of the comorbid conditions was derived from coefficient estimates of Cox regression for all-cause mortality, and the index was internally validated. The performance of the index was assessed by discrimination, calibration, and reclassification. Results A total of 30,303 hemodialysis patients were included in this study. The weight for individual comorbid conditions of this index differed fromthat of the USRDS index. The performance of this index was similar to that of USRDS and Charlson indices in terms of model fit statistics, overall predictive ability, discrimination, and calibration. Hosmer-Lemeshow test showed that all three indices demonstrated significant differences between predicted and observed mortality rates. When patients were categorized by the predicted 2.5-year survival probabilities, the index achieved a net reclassification improvement of 4.71% (P,0.001), referenced to USRDS index. Conclusions ComparedwithUSRDS index, this new index demonstrated better reclassification ability, but future studies should address the clinical significance.
AB - Background and objectives Chinese patients with ESRD have different comorbidity patterns than white patients with ESRD and require a validated comorbidity index. The objective of this study was to develop a new index for mortality prediction in 2006-2009 Taiwanese incident hemodialysis patients. Design, setting, participants, & measurements Data were retrieved from 2005 to 2010 Taiwan National Health Insurance claimrecords, and follow-upwas available until December 31, 2010. The same comorbid conditions as the US Renal Data System (USRDS) index that occurred during a 12-month period from 9 months before to 3 months after dialysis initiation were used to construct the index. Integer weight of the comorbid conditions was derived from coefficient estimates of Cox regression for all-cause mortality, and the index was internally validated. The performance of the index was assessed by discrimination, calibration, and reclassification. Results A total of 30,303 hemodialysis patients were included in this study. The weight for individual comorbid conditions of this index differed fromthat of the USRDS index. The performance of this index was similar to that of USRDS and Charlson indices in terms of model fit statistics, overall predictive ability, discrimination, and calibration. Hosmer-Lemeshow test showed that all three indices demonstrated significant differences between predicted and observed mortality rates. When patients were categorized by the predicted 2.5-year survival probabilities, the index achieved a net reclassification improvement of 4.71% (P,0.001), referenced to USRDS index. Conclusions ComparedwithUSRDS index, this new index demonstrated better reclassification ability, but future studies should address the clinical significance.
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U2 - 10.2215/CJN.03100313
DO - 10.2215/CJN.03100313
M3 - Article
C2 - 24311712
AN - SCOPUS:84896871233
SN - 1555-9041
VL - 9
SP - 513
EP - 519
JO - Clinical Journal of the American Society of Nephrology
JF - Clinical Journal of the American Society of Nephrology
IS - 3
ER -