Dataset Information

Validation of an atrial fibrillation risk algorithm in whites and African Americans.

ABSTRACT: BACKGROUND:We sought to validate a recently published risk algorithm for incident atrial fibrillation (AF) in independent cohorts and other racial groups. METHODS:We evaluated the performance of a Framingham Heart Study (FHS)-derived risk algorithm modified for 5-year incidence of AF in the FHS (n = 4764 participants) and 2 geographically and racially diverse cohorts in the age range 45 to 95 years: AGES (the Age, Gene/Environment Susceptibility-Reykjavik Study) (n = 4238) and CHS (the Cardiovascular Health Study) (n = 5410, of whom 874 [16.2%] were African Americans). The risk algorithm included age, sex, body mass index, systolic blood pressure, electrocardiographic PR interval, hypertension treatment, and heart failure. RESULTS:We found 1359 incident AF events in 100 074 person-years of follow-up. Unadjusted 5-year event rates differed by cohort (AGES, 12.8 cases/1000 person-years; CHS whites, 22.7 cases/1000 person-years; and FHS, 4.5 cases/1000 person-years) and by race (CHS African Americans, 18.4 cases/1000 person-years). The strongest risk factors in all samples were age and heart failure. The relative risks for incident AF associated with risk factors were comparable across cohorts and race groups. After recalibration for baseline incidence and risk factor distribution, the Framingham algorithm, reported in C statistic, performed reasonably well in all samples: AGES, 0.67 (95% confidence interval [CI], 0.64-0.71); CHS whites, 0.68 (95% CI, 0.66-0.70); and CHS African Americans, 0.66 (95% CI, 0.61-0.71). Risk factors combined in the algorithm explained between 47.0% (AGES) and 63.6% (FHS) of the population-attributable risk. CONCLUSIONS:Risk of incident AF in community-dwelling whites and African Americans can be assessed reliably by routinely available and potentially modifiable clinical variables. Seven risk factors accounted for up to 64% of risk.

SUBMITTER: Schnabel RB

PROVIDER: S-EPMC3021784 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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Validation of an atrial fibrillation risk algorithm in whites and African Americans.

Schnabel Renate B RB Aspelund Thor T Li Guo G Sullivan Lisa M LM Suchy-Dicey Astrid A Harris Tamara B TB Pencina Michael J MJ D'Agostino Ralph B RB Levy Daniel D Kannel William B WB Wang Thomas J TJ Kronmal Richard A RA Wolf Philip A PA Burke Gregory L GL Launer Lenore J LJ Vasan Ramachandran S RS Psaty Bruce M BM Benjamin Emelia J EJ Gudnason Vilmundur V Heckbert Susan R SR

Archives of internal medicine 20101101 21

<h4>Background</h4>We sought to validate a recently published risk algorithm for incident atrial fibrillation (AF) in independent cohorts and other racial groups.<h4>Methods</h4>We evaluated the performance of a Framingham Heart Study (FHS)-derived risk algorithm modified for 5-year incidence of AF in the FHS (n = 4764 participants) and 2 geographically and racially diverse cohorts in the age range 45 to 95 years: AGES (the Age, Gene/Environment Susceptibility-Reykjavik Study) (n = 4238) and CHS ...[more]

PMID: 21098350

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Project description:Because existing risk prediction models for lung cancer were developed in white populations, they may not be appropriate for predicting risk among African-Americans. Therefore, a need exists to construct and validate a risk prediction model for lung cancer that is specific to African-Americans. We analyzed data from 491 African-Americans with lung cancer and 497 matched African-American controls to identify specific risks and incorporate them into a multivariable risk model for lung cancer and estimate the 5-year absolute risk of lung cancer. We performed internal and external validations of the risk model using data on additional cases and controls from the same ongoing multiracial/ethnic lung cancer case-control study from which the model-building data were obtained as well as data from two different lung cancer studies in metropolitan Detroit, respectively. We also compared our African-American model with our previously developed risk prediction model for whites. The final risk model included smoking-related variables [smoking status, pack-years smoked, age at smoking cessation (former smokers), and number of years since smoking cessation (former smokers)], self-reported physician diagnoses of chronic obstructive pulmonary disease or hay fever, and exposures to asbestos or wood dusts. Our risk prediction model for African-Americans exhibited good discrimination [75% (95% confidence interval, 0.67-0.82)] for our internal data and moderate discrimination [63% (95% confidence interval, 0.57-0.69)] for the external data group, which is an improvement over the Spitz model for white subjects. Existing lung cancer prediction models may not be appropriate for predicting risk for African-Americans because (a) they were developed using white populations, (b) level of risk is different for risk factors that African-American share with whites, and (c) unique group-specific risk factors exist for African-Americans. This study developed and validated a risk prediction model for lung cancer that is specific to African-Americans and thus more precise in predicting their risks. These findings highlight the importance of conducting further ethnic-specific analyses of disease risk.

Dataset Information

Validation of an atrial fibrillation risk algorithm in whites and African Americans.

Publications

Validation of an atrial fibrillation risk algorithm in whites and African Americans.

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