Evidence map›Paper›PMID 40668165›Full record

ArticleJACC. CardioOncology2025

Cardiovascular Risk, Health Metrics, and Cancer Prediction: A Scoping Review.

Gretell Henriquez-Santos, Ji-Eun Kim, Sant J Kumar, Alicia A Livinski, Jacqueline B Vo, Fang Zhu, Jungnam Joo, Joseph J Shearer, Maryam Hashemian, Véronique L Roger

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JACC. CardioOncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

10 authors.

Gretell Henriquez-SantosHeart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Ji-Eun KimHeart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA; Institute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, South Korea.
Sant J KumarMedStar Georgetown University Hospital, Washington, DC, USA.
Alicia A LivinskiNational Institutes of Health Library, Office of Research Services, Office of the Director, National Institutes of Health, Bethesda, Maryland, USA.
Jacqueline B VoDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Fang ZhuHeart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Jungnam JooOffice of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Joseph J ShearerHeart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Maryam HashemianHeart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA. Electronic address: maryam.hashemian2@nih.gov.
Véronique L RogerHeart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiovascular disease (CVD) and cancer are leading global causes of morbidity and mortality. Given the shared risk factors, it is plausible that CVD risk scores and cardiovascular health (CVH) metrics could predict cancer risk.

objectivesThe authors sought to identify and summarize studies examining the association between CVD risk scores, CVH metrics, and incident cancer.

methodsA systematic search of 4 databases (Embase, PubMed, Scopus, Web of Science: Core) was conducted in April 2024 without language or date restrictions. Five reviewers (G.H., J.K., S.J.K., M.H., V.L.R.) independently screened records using Covidence software and extracted data from eligible prospective studies (adults aged ≥18 years; cancer incidence as outcome; CVD risk scores or CVH metrics as exposure).

resultsOf 4,165 records screened, 13 studies (14 CVD or CVH metrics) were included. Heterogeneity between scales precluded a meta-analysis. Four studies evaluated CVD risk scores (eg, atherosclerotic CVD) and 10 reported CVH metrics (eg, the American Heart Association's Life's Simple 7). Sample sizes ranged from 1,880 to 342,226, with median follow-up from 8.1 to 29.6 years. The majority included all types of cancer (71.4%), including breast, lung, colorectal, and prostate cancer types, with cancer events ranging from 387 to 11,643. Higher CVD risk scores were consistently associated with increased cancer risk incidence (HRs: 1.16-3.71). Ideal CVH metrics were associated with reduced risk (HRs: 0.49-0.95).

conclusionsDespite heterogeneity in CVD risk metrics and cancer types, most studies suggested that worse CVD risk scores or CVH metrics predict greater cancer risk. Future studies should focus on specific CVD risk metrics and cancer types to produce evidence suitable for a meta-analysis.

Indexed as

cancer riskcardiovascular diseasecardiovascular health metricscardiovascular risk scorespreventionrisk factorsrisk prediction

Identifiers

PMID40668165
PMCPMC12441625

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.