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Predicting 1 year mortality in an outpatient haemodialysis population: a comparison of comorbidity instruments
Dana C Miskulin1, Alice A Martin, Richard Brown
1Division of Nephrology, Tufts-New England Medical Center, Boston, MA 02111, USA. dmiskulin@tufts-nemc.org
Insights
The Index of Coexistent Diseases (ICED) showed better 1-year mortality prediction in dialysis patients than other comorbidity indices. However, differences narrowed when factors like albumin and race were included, suggesting a need for improved comorbidity assessment tools.
Area of Science:
- Nephrology
- Biostatistics
- Public Health
Background:
- Accurate measurement of comorbidity burden in dialysis patients is crucial for unbiased clinical outcome comparisons.
- Existing comorbidity instruments require validation for their utility in predicting mortality in this population.
Purpose of the Study:
- To compare the discriminatory accuracy of four comorbidity instruments in predicting 1-year mortality in a US dialysis population.
- To evaluate the impact of additional clinical factors on the predictive performance of these instruments.
Main Methods:
- The Index of Coexistent Diseases (ICED) was used to score comorbidity in 1779 hemodialysis patients.
- Charlson Comorbidity Index (CCI), Wright-Khan, and Davies indices were also applied.
- Logistic regression and receiver-operating characteristic (ROC) curves (AUC) were used to assess predictive accuracy for 1-year mortality.
Main Results:
- The ICED demonstrated superior discrimination (AUC 0.72) compared to CCI (0.67), Wright-Khan (0.68), and Davies (0.68) indices when predicting mortality based on comorbidity and age alone.
- Inclusion of race and serum albumin improved predictive accuracy for all models, reducing the performance gap between instruments (ICED AUC 0.77, CCI AUC 0.75).
Conclusions:
- While ICED showed higher initial discriminatory ability, its advantage diminished when race and serum albumin were considered.
- Current comorbidity instruments demonstrate limited discriminatory power for mortality outcomes in dialysis patients.
- Developing a tailored comorbidity index for dialysis populations, focusing on key prognostic factors, could enhance predictive accuracy and practicality.
Background:
A valid and practical measure of comorbid illness burden in dialysis populations is greatly needed to enable unbiased comparisons of clinical outcomes. We compare the discriminatory accuracy of 1 year mortality predictions derived from four comorbidity instruments in a large representative US dialysis population.
Methods:
Comorbidity information was collected using the Index of Coexistent Diseases (ICED) in 1779 haemodialysis patients of a national dialysis provider between 1997 and 2000. Comorbidity was also scored according to the Charlson Comorbidity Index (CCI), Wright-Khan and Davies indices. Relationships of instrument scores with 1 year mortality were assessed in separate logistic regression analyses. Discriminatory ability was compared using the area under the receiver-operating characteristics curve (AUC), based on predictions of each regression model.
Results:
When mortality was predicted using comorbidity and age, the ICED better discriminated between survivors and those who died (AUC 0.72) as compared with the CCI (0.67), Wright-Khan (0.68) and Davies (0.68) indices. Upon addition of race and serum albumin, predictive accuracy of each model improved further (AUCs of the ICED, 0.77; CCI, 0.75; Wright-Khan Index, 0.75; Davies Index, 0.74).
Conclusions:
The ICED had greater discriminatory ability than the CCI, Davies and Wright-Khan indices, when age and a comorbidity index were used alone to predict 1 year mortality; however, the differences among instruments diminished once serum albumin, race and the cause of ESRD were accounted for. None of the currently available comorbidity instruments tested in this study discriminated mortality outcomes particularly well. Assessing comorbidity using the ICED takes significantly more time. Identifying the key prognostic comorbid conditions and weighting these according to outcomes in a dialysis population should increase accuracy and, with restriction to a finite number of items, provide a practical means for widespread comorbidity assessment.
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