Evidence map›Paper›PMID 33258447›Full record

Observational studyeLife2020

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

Daniel Shriner, Amy R Bentley, Jie Zhou, Kenneth Ekoru, Ayo P Doumatey, Guanjie Chen, Adebowale Adeyemo, Charles N Rotimi

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Daniel ShrinerCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.ORCID 0000-0003-1928-5520
Amy R BentleyCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
Jie ZhouCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
Kenneth EkoruCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
Ayo P DoumateyCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
Guanjie ChenCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
Adebowale AdeyemoCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
Charles N RotimiCenter for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, United States.
National Human Genome Research Institute · US

Funding

Genetic epidemiology of complex diseasesZIAHG200362 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ROTIMI, CHARLES · 2009 to 2025
$54.7M
Intramural NIH HHS ZIA HG200362NHGRI NIH HHS 1 ZIA HG200362
6 · The paper itself

Abstract

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.

Indexed as

HypertensionModels, BiologicalAdultAgedAged, 80 and overAge FactorsAge of OnsetBayes TheoremBlack or African AmericanCase-Control StudiesFemaleHumansLogistic ModelsMaleMexican AmericansMiddle Agedepidemiologyglobal healthhealth disparityhumanhypertensiontime-to-event

Identifiers

PMID33258447
PMCPMC7707825
OpenAlexW3110099723

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.