Evidence map›Paper›PMID 39730985›Full record

ArticleJournal of racial and ethnic health disparities2026

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

Paul Rogers, Christine Merenda, Richardae Araojo, Christine Lee, Milena Lolic, Ying Zhang, Jessica Reese, Kimberly Malloy, Dong Wang, Wen Zou and 2 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Paul RogersNational Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, AR, USA. Paul.Rogers@fda.hhs.gov.ORCID 0000-0001-9420-1476
Christine MerendaOffice of the Commissioner, Office of Minority Health and Health Equity, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Richardae AraojoOffice of the Commissioner, Office of Minority Health and Health Equity, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Christine LeeOffice of the Commissioner, Office of Minority Health and Health Equity, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Milena LolicOffice of the Commissioner, Office of Minority Health and Health Equity, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Ying ZhangDepartment of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Jessica ReeseDepartment of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Kimberly MalloyDepartment of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Dong WangNational Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, AR, USA.
Wen ZouNational Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, AR, USA.
Joshua XuNational Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, AR, USA.
Elisa LeeDepartment of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Charlson Comorbidity Index (CCI) is a frequently used mortality predictor based on a scoring system for the number and type of patient comorbidities health researchers have used since the late 1980s. The initial purpose of the CCI was to classify comorbid conditions, which could alter the risk of patient mortality within a 1-year time frame. However, the CCI may not accurately reflect risk among American Indians because they are a small proportion of the US population and possibly lack representation in the original patient cohort. A motivating factor in calibrating a CCI for American Indians is that this population, as a whole, experiences a greater burden of comorbidities, including diabetes mellitus, obesity, cancer, cardiovascular disease, and other chronic health conditions, than the rest of the US population.

methodsThis study attempted to modify the CCI to be specific to the American Indian population utilizing the data from the still ongoing The Strong Heart Study (SHS) - a multi-center population-based longitudinal study of cardiovascular disease among American Indians. A 1-year survival analysis with mortality as the outcome was performed using the SHS morbidity and mortality surveillance data and assessing the impact of comorbidities in terms of hazard ratios with the training cohort. A Kaplan-Meier plot for a subset of the testing cohort was used to compare groups with selected mCCI-AI scores.

resultsA total of 3038 Phase VI participants from the SHS comprised the study population for whom mortality and morbidity surveillance data were available through December 2019. The weights generated by the SHS participants for myocardial infarction, congestive heart failure, and high blood pressure were greater than Charlson's original weights. In addition, the weights for liver illness were equivalent to Charlson's severe form of the disease. Lung cancer had the greatest overall weight derived from a hazard ratio of 8.31.

conclusionsThe mCCI-AI was a statistically significant predictor of 1-year mortality, classifying patients into different risk strata χ

Indexed as

Cardiovascular DiseasesComorbidityIndians, North AmericanAdultAgedFemaleHumansLongitudinal StudiesMaleMiddle AgedUnited StatesAmerican IndianCharlson comorbidity indexMorbidityMortality

Identifiers

PMID39730985
PMCPMC12795876

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