Time-to-event modeling of hypertension reveals the nonexistence of true controls.


Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
01 12 2020
Historique:
received: 10 09 2020
accepted: 13 11 2020
entrez: 1 12 2020
pubmed: 2 12 2020
medline: 9 3 2021
Statut: epublish

Résumé

Given a lifetime risk of ~90% by the ninth decade of life, it is unknown if there are true controls for hypertension in epidemiological and genetic studies. Here, we compared Bayesian logistic and time-to-event approaches to modeling hypertension. The median age at hypertension was approximately a decade earlier in African Americans than in European Americans or Mexican Americans. The probability of being free of hypertension at 85 years of age in African Americans was less than half that in European Americans or Mexican Americans. In all groups, baseline hazard rates increased until nearly 60 years of age and then decreased but did not reach zero. Taken together, modeling of the baseline hazard function of hypertension suggests that there are no true controls and that controls in logistic regression are cases with a late age of onset.

Identifiants

pubmed: 33258447
doi: 10.7554/eLife.62998
pii: 62998
pmc: PMC7707825
doi:
pii:

Types de publication

Journal Article Observational Study Research Support, N.I.H., Extramural Research Support, N.I.H., Intramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NHGRI NIH HHS
ID : 1 ZIA HG200362
Pays : United States

Déclaration de conflit d'intérêts

DS, AB, JZ, KE, AD, GC, AA, CR No competing interests declared

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Auteurs

Daniel Shriner (D)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Amy R Bentley (AR)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Jie Zhou (J)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Kenneth Ekoru (K)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Ayo P Doumatey (AP)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Guanjie Chen (G)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Adebowale Adeyemo (A)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

Charles N Rotimi (CN)

Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.

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Classifications MeSH