Evidence map›Paper›PMID 24100805›Full record

ReviewClinical chemistry2014

Cardiovascular disease risk prediction in women: is there a role for novel biomarkers?

Nina P Paynter, Brendan M Everett, Nancy R Cook

Abstract readReview
In one paragraph

Review in Clinical chemistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Biomarkers of cardiovascular disease risk in women.Metabolism: clinical and experimental · 2015
    Review
  11. Observational
  12. Article
  13. Article
  14. Article
  15. Contribution of organically grown crops to human health.International journal of environmental research and public health · 2014
    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

3 authors.

Nina P PaynterDivision of Preventive Medicine, Brigham and Women's Hospital, Boston, MA.
Brendan M Everett
Nancy R Cook

Funding

Novel Applications of Risk Reclassification Methods in CVD Risk PredictionR01HL113080 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI COOK, NANCY R · 2013 to 2016
$1.3M
Harvard Clinical and Translational Science Center (KL2)KL2TR000168 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2012 to 2013
$965k
NCATS NIH HHS 8KL2TR000168-05NCATS NIH HHS KL2 TR000168NHLBI NIH HHS 1R01HL113080NHLBI NIH HHS R01 HL113080
6 · The paper itself

Abstract

backgroundRisk prediction is an integral part of the current US guidelines for cardiovascular disease in women. Although current risk prediction algorithms exist to identify women at increased 10-year risk of cardiovascular disease (CVD), clinicians and researchers have been interested in developing novel biomarkers that might improve predictive accuracy further. These biomarkers have led to important insights into the pathophysiology of CVD, but results for their ability to improve prediction or guide preventive therapy have been mixed. The incidence of CVD is lower in women than men, and the effects of a number of traditional biomarkers on CVD risk differ in women compared to men. Both of these factors influence the ability to accurately predict CVD risk. CONTENT: We review the distinctive aspects of CVD risk prediction in women, discuss the statistical challenges to improved risk prediction, and discuss a number of biomarkers in varying stages of development with a range of performance in prediction. SUMMARY: A variety of biomarkers from different pathophysiologic pathways have been evaluated for improving CVD risk. While many have been incompletely studied or have not been shown to improve risk prediction in women, others, such as high-sensitivity troponin T, have shown promise in improving risk prediction. Increasing inclusion of women in CVD studies will be crucial to providing opportunities to evaluate future biomarkers.

Indexed as

BiomarkersCardiovascular DiseasesFemaleHumansPredictive Value of TestsRisk FactorsBiomarkers

Identifiers

PMID24100805
PMCPMC3877731

What OpenQuestion holds

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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.