Development of a multimorbidity index: Impact on quality of life using a rheumatoid arthritis cohort

被引:50
作者
Radner, Helga [1 ,2 ]
Yoshida, Kazuki [1 ,3 ]
Mjaavatten, Maria Dahl [1 ,4 ]
Aletaha, Daniel [2 ]
Frits, Michelle [1 ]
Lu, Bing [1 ]
Iannaccone, Christine [1 ]
Shadick, Nancy [1 ]
Weinblatt, Michael [1 ]
Hmamouchi, Ihsane [5 ]
Dougados, M. [6 ]
Smolen, Josef. S. [2 ]
Solomon, Daniel. H. [1 ]
机构
[1] Brigham & Womens Hosp, Div Rheumatol Immunol & Allergy, Boston, MA 02115 USA
[2] Med Univ Vienna, Dept Internal Med 3, Div Rheumatol, Vienna, Austria
[3] Harvard Univ, TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA
[4] Diakonhjemmet Hosp, Dept Rheumatol, Oslo, Norway
[5] Mohammed V Souissi Univ, Fac Med, Lab Biostat Clin Res & Epidemiol LBRCE, Rabat, Morocco
[6] Paris Descartes Univ, Hop Cochin, AP HP,Dept Rheumatol, EULAR Ctr Excellence,INSERM,U1153,Clin Epidemiol, Paris, France
基金
奥地利科学基金会;
关键词
Rheumatoid arthritis; Multimorbidity; Comorbidity; Health-related quality of life; COMORBIDITY INDEX; IDENTIFICATION; PREVALENCE; VALIDITY;
D O I
10.1016/j.semarthrit.2015.06.010
中图分类号
R5 [内科学];
学科分类号
100201 [内科学];
摘要
Objective: To develop a multimorbidity index (MMI) based on health-related quality of life (HRQol). Methods: The index was developed in an observational RA cohort. In all, 40 morbidities recommended as core were identified using ICD-9 codes. MMIs of two types were calculated: one by enumerating morbidities (MMI.count) and the other by weighting morbidities based on their association with HRQol as assessed by EQ-5D in multiple linear regression analysis (using beta-coefficients; MMI.weight). MMIs were compared to the Charlson comorbidity index (CCI) and externally validated in an international RA cohort (COMORA Study). Results: In all, 544 out of 876 patients were multimorbid. MMI.count was in the range 1-16 (median = 2) and MMI.weight in the range 0-38 (median = 1). Both indices were more strongly associated with EQ-5D than CCI (Spearman: MMI.count = -0.20, MMI.weight = -0.26, and CCI = -0.10; p < 0.01). R-2 obtained by linear regression using EQ-5D as a dependent variable and various indices as independent variables, adjusted for age and gender, was the highest for MMI (R-2: MMI.count = 0.05, MMI.weight = 0.11, and CCI = 0.02). When accounting for clinical disease activity index (CDAI) R-2 increased: MMI.count = 0.18, MMI.weight = 0.22, and CCI = 0.17, still showing higher values of MMI compared with CCI. External validation in different RA cohorts (COMORA, n = 3864) showed good performance of both indices (linear regression including age, gender, and disease activity R-2 = 0.30 for both MMIs). Conclusion: In our cohort, MMI based on EQ-5D performed better than did CCI. Findings were reproducible in another large RA cohort. Not much improvement was gained by weighting; therefore a simple counted index could be useful to control for the effect of multimorbidity on patient's overall well-being. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:167 / 173
页数:7
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