School of Public Health, University of Saskatchewan, 107 Wiggins Road, Saskatoon, SK, Canada.
Osteoporos Int. 2011 Oct;22(10):2633-43. doi: 10.1007/s00198-010-1516-7. Epub 2011 Jan 11.
The performance of five comorbidity measures, including the Charlson and Elixhauser indices, was investigated for predicting mortality, hospitalization, and fracture outcomes in two osteoporosis cohorts defined from administrative databases. The optimal comorbidity measure depended on the outcome of interest, although overall the Elixhauser index performed well.
Studies that use administrative data to investigate population-based health outcomes often adopt risk-adjustment models that include comorbidities, conditions that coexist with the index disease. There has been limited research about the measurement of comorbidity in osteoporotic populations. The study purpose was to compare the performance of comorbidity measures for predicting mortality, fracture, and health service utilization outcomes in two cohorts with diagnosed or treated osteoporosis.
Administrative data were from the province of Saskatchewan, Canada. Osteoporosis cohorts were identified from diagnoses in hospital and physician data and prescriptions for osteo-protective medications using case definitions with high sensitivity or high specificity. Five diagnosis- and medication-based comorbidity measures and five 1-year outcomes, including mortality, hospitalization (two measures), osteoporotic-related fracture, and hip fracture, were defined. Performance of the comorbidity measures was assessed using the c-statistic (discrimination) and Brier score (prediction error) for multiple logistic regression models.
In the specific cohort (n = 9,849) for the mortality outcome, the Elixhauser index resulted in the largest improvement (8.96%) in the c-statistic and lowest Brier score compared to a model that contained demographic and socioeconomic variables, followed by the Charlson index (6.06%). For hospitalization, the number of different diagnoses resulted in the largest improvement (14.01%) in the c-statistic. The Elixhauser index resulted in significant improvements in the c-statistic for osteoporosis-related and hip fractures. Similar results were observed for the sensitive cohort (n = 28,068).
Recommendations about the optimal comorbidity measure will vary with the outcome under investigation. Overall, the Elixhauser index performed well.
研究五种合并症指标(包括 Charlson 和 Elixhauser 指数)在两个基于行政数据库的骨质疏松队列中预测死亡率、住院和骨折结局的表现。尽管 Elixhauser 指数总体表现良好,但最佳合并症指标取决于所关注的结果。
使用行政数据研究基于人群的健康结果的研究通常采用包括合并症(与索引疾病共存的疾病)的风险调整模型。对于骨质疏松人群的合并症测量,研究有限。研究目的是比较两种诊断或治疗骨质疏松症的队列中,用于预测死亡率、骨折和卫生服务利用结局的合并症指标的性能。
行政数据来自加拿大萨斯喀彻温省。使用高灵敏度或高特异性的病例定义,从医院和医生数据以及骨保护药物处方中确定骨质疏松症队列。使用诊断和药物的五种合并症指标和五种 1 年结局(包括死亡率、住院(两种指标)、骨质疏松性相关骨折和髋部骨折)进行定义。使用多个逻辑回归模型的 C 统计量(区分度)和 Brier 评分(预测误差)评估合并症指标的性能。
在特定的死亡率结局队列(n=9849)中,Elixhauser 指数导致 C 统计量的最大改善(8.96%),Brier 评分最低,其次是 Charlson 指数(6.06%)。对于住院,不同诊断的数量导致 C 统计量的最大改善(14.01%)。Elixhauser 指数对骨质疏松相关和髋部骨折的 C 统计量有显著改善。在敏感队列(n=28068)中也观察到了类似的结果。
关于最佳合并症指标的建议将根据所调查的结果而有所不同。总体而言,Elixhauser 指数表现良好。