Evidence map›Paper›PMID 41789338›Full record

ReviewReviews in cardiovascular medicine2026

Potential Similarity of Serum Cholesterol Multivariate Coefficients in the Prediction of Coronary Heart Disease Across Populations: A Review From the Seven Countries Study.

Alessandro Menotti, Paolo Emilio Puddu

Abstract readReview
In one paragraph

Review in Reviews in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Alessandro MenottiAssociation for Cardiac Research, 00182 Rome, Italy.ORCID https://orcid.org/0000-0002-6209-8416
Paolo Emilio PudduAssociation for Cardiac Research, 00182 Rome, Italy.ORCID https://orcid.org/0000-0002-6191-7838

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to review the unique contribution of the Seven Countries Study (SCS) of cardiovascular diseases to the possible non-heterogeneity in multivariate coefficients of serum cholesterol in predicting coronary heart disease (CHD) mortality across different populations. This study reviewed five published analyses from the SCS, which together encompassed 16 cohorts of middle-aged men from eight nations across seven countries in the USA, northern and southern Europe, and Japan. In total, these analyses included 12,763 participants and follow-up periods ranging from 25 to 60 years after the baseline examination. Serum cholesterol was measured using uniform, standardized procedures that differed from those reported in the literature. Marked differences in mortality rates were observed, with higher rates in the USA and northern Europe and lower rates in the other regions. A systematic comparison of serum cholesterol coefficients did not reveal significant heterogeneity across cohort combinations or follow-up durations of 25, 40, 50, and 60 years for CHD mortality. In all cases, coefficients were adjusted for three additional risk factors: age, cigarette smoking, and systolic blood pressure. Variations in CHD mortality rates across populations were explained by differences in serum cholesterol levels. In contrast, the magnitudes of serum cholesterol coefficients were relatively similar across groups, although not necessarily homogeneous. These findings support the idea that predictive models of CHD mortality developed for a specific population can also be applied to other populations, since the expectation, at least for serum cholesterol, is to obtain similar relative risk estimates, not absolute risk, which aligns with the limited evidence that is available in the current literature.

Indexed as

absolute versus relative risksCHD mortalitycholesterolcoefficients non-heterogeneitycross-population studiesSeven Countries Study

Identifiers

PMID41789338
PMCPMC12960010

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