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Published on: June 16, 2014
Comparing Five Comorbidity Indices to Predict Mortality in Chronic Kidney Disease: A Retrospective Cohort Study
Eric McArthur1, Sarah E Bota1, Manish M Sood1,2
1Institute for Clinical Evaluative Sciences, London, ON, Canada.
Insights
Existing comorbidity indices fail to accurately predict mortality in patients with chronic kidney disease (CKD). New or modified indices are needed to improve risk assessment for this population.
Area of Science:
- Nephrology
- Epidemiology
- Health Services Research
Background:
- Comorbidity indices are used to assess patient risk and adjust analyses.
- Their performance in chronic kidney disease (CKD) populations is not well understood.
Purpose of the Study:
- To evaluate five common comorbidity indices for predicting 1-year mortality.
- The study focused on three CKD patient groups: kidney transplant recipients, maintenance dialysis patients, and those with low estimated glomerular filtration rate (eGFR).
Main Methods:
- A population-based retrospective cohort study was conducted in Ontario, Canada (2004-2014).
- Five indices (Charlson, CKD-modified Charlson, Johns Hopkins AGD, Elixhauser, Wright-Khan) were assessed.
- Model discrimination (c-statistics) and calibration were evaluated using derivation and validation samples.
Main Results:
- The study included over 200,000 patients across the three CKD groups.
- All five comorbidity indices demonstrated inadequate discrimination (median c-statistics < 0.7) for predicting 1-year mortality in all groups.
- Calibration of the models was also poor across all assessed indices and patient groups.
Conclusions:
- Current administrative data-based comorbidity indices do not accurately predict mortality in CKD patients.
- There is a need to develop new indices or modify existing ones with additional risk factors specific to CKD populations.
- Improved indices are crucial for better risk profiling and adjustment in research involving CKD patients.
Background:
Several different indices summarize patient comorbidity using health care data. An accurate index can be used to describe the risk profile of patients, and as an adjustment factor in analyses. How well these indices perform in persons with chronic kidney disease (CKD) is not well known.
Objective:
Assess the performance of 5 comorbidity indices at predicting mortality in 3 different patient groups with CKD: incident kidney transplant recipients, maintenance dialysis patients, and individuals with low estimated glomerular filtration rate (eGFR).
Design:
Population-based retrospective cohort study.
Setting:
Ontario, Canada, between 2004 and 2014.
Patients:
Individuals at the time they first received a kidney transplant, received maintenance dialysis, or were confirmed to have an eGFR less than 45 mL/min per 1.73m2.
Measurements:
Five comorbidity indices: Charlson comorbidity index, end-stage renal disease-modified Charlson comorbidity index, Johns Hopkins' Aggregated Diagnosis Groups score, Elixhauser score, and Wright-Khan index. Our primary outcome was 1-year all-cause mortality.
Methods:
Comorbidity indices were estimated using information in the prior 2 years. Each group was randomly divided 100 times into derivation and validation samples. Model discrimination was assessed using median c-statistics from logistic regression models, and calibration was evaluated graphically.
Results:
We identified 4111 kidney transplant recipients, 23 897 individuals receiving maintenance dialysis, and 181 425 individuals with a low eGFR. Within 1 year, 108 (2.6%), 4179 (17.5%), and 17 898 (9.9%) in each group had died, respectively. In the validation sample, model discrimination was inadequate with median c-statistics less than 0.7 for all 5 comorbidity indices for all 3 groups. Calibration was also poor for all models.
Limitations:
The study used administrative health care data so there is the potential for misclassification. Indices were modeled as continuous scores as opposed to indicators for individual conditions to limit overfitting.
Conclusions:
Existing comorbidity indices do not accurately predict 1-year mortality in patients with CKD. Current indices could be modified with additional risk factors to improve their performance in CKD, or a new index could be developed for this population.
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