Evidence map›Paper›PMID 36336692›Full record

Observational studyBMC medicine2022

Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease.

Austin King, Lang Wu, Hong-Wen Deng, Hui Shen, Chong Wu

Registry-linked trialOpen access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07039123 (Polygenic Risk Score to Optimize Primary Prevention in Intermediate Risk Population), which is not on this map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.7field-weighted citation impact, top 6% 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.

NCT07039123 naactive not recruitingnot on this mapstarted 2025, after this paper: background citation

Polygenic Risk Score to Optimize Primary Prevention in Intermediate Risk Population (PERSONAL)

TypeinterventionalSponsorUniversity of BernRan2025 to 2027Enrolled205ConditionsPrimary Prevention of Cardiovascular DiseaseArmsPolygenic Risk Score for Coronary Artery Disease (PRS-CAD), Standardized Risk Communication Tool (SCORE2)
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Integrating Polygenic Risk Scores (PRS) for Personalized Diabetes Care: Advancing Clinical Practice with Tailored Pharmacological Approaches.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Review
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

5 authors at 4 institutions in 1 country.

Austin KingDepartment of Statistics, Florida State University, Tallahassee, FL, USA.
Lang WuCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA.
Hong-Wen DengCenter of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA.
Hui ShenCenter of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA.
Chong WuDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. cwu18@mdanderson.edu.ORCID 0000-0002-8400-1785
Tulane University · USFlorida State University · USThe University of Texas MD Anderson Cancer Center · USUniversity of Hawaiʻi at Mānoa · US

Funding

Uncovering causal protein markers to improve prostate cancer etiology understanding and risk prediction in Africans and EuropeansR01CA263494 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI Chong Wu, Lang Wu · 2022 to 2026
$3.5M
Intensive Lifestyle Intervention, Metabolomics, and Risk of Frailty Fracture in Overweight or Obese Patients with Type 2 DiabetesR01AG068232 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI JOHNSON, KAREN C, ZHAO, QI · 2021 to 2025
$3.1M
Identification of Metabolomic Profiles for Sarcopenia Traits in Older Whites and BlacksR01AG061917 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI SHEN, HUI, ZHAO, QI · 2019 to 2023
$3.0M
Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's DiseaseR03AG070669 · NIA · FLORIDA STATE UNIVERSITY · PI BRADLEY, JONATHAN RAY, WU, CHONG · 2021 to 2022
$296k
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NCI NIH HHS R01 CA263494NIA NIH HHS R01 AG061917NIA NIH HHS R03 AG070669
6 · The paper itself

Abstract

backgroundThe value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. 

methodsAn observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case-control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold.

resultsIn the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634-0.646), 0.718 (95% CI, 0.713-0.723), and 0.753 (95% CI, 0.748-0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and - 0.023 (95% CI, - 0.025 to - 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category.

conclusionsAddition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.

Indexed as

Coronary Artery DiseaseCohort StudiesHumansMiddle AgedPredictive Value of TestsRisk AssessmentRisk FactorsGenomic risk predictionIntegrated polygenic risk scorePooled cohort equations

Identifiers

PMID36336692
PMCPMC9639312
OpenAlexW4308298470

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.