Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the...

Area of Science:

• Epidemiology
• Biostatistics
• Public Health

Background:

• The Charlson Comorbidity Index (CCI) is a widely used mortality prediction tool.
• The CCI may not accurately represent mortality risk for American Indians due to population-specific health burdens and potential underrepresentation in original cohorts.
• American Indians face a higher prevalence of comorbidities like diabetes, obesity, cancer, and cardiovascular disease.

Purpose of the Study:

• To modify and validate the CCI for improved mortality risk prediction among American Indians.
• To develop a culturally relevant comorbidity index for a specific population.

Main Methods:

• Utilized data from The Strong Heart Study (SHS), a longitudinal study of American Indian cardiovascular disease.
• Performed 1-year survival analysis using SHS morbidity and mortality data.
• Assessed comorbidity impact via hazard ratios and employed Kaplan-Meier plots for validation.

Main Results:

• Modified CCI for American Indians (mCCI-AI) demonstrated significant predictor capabilities.
• Weights for myocardial infarction, congestive heart failure, and high blood pressure were higher in the mCCI-AI compared to the original CCI.
• Lung cancer exhibited the highest weight (hazard ratio 8.31), and liver illness weight was equivalent to the severe form in the original CCI.

Conclusions:

• The mCCI-AI is a statistically significant predictor of 1-year mortality in American Indians.
• The mCCI-AI effectively stratified patients into different risk categories.
• The developed index achieved 73% accuracy in discriminating between survivors and non-survivors.