Evidence mapPaperPMID 42068528Full record

SynthesisCardiovascular drugs and therapy2026

Sources of Heterogeneity in the Efficacy of Statins for Primary Prevention of Cardiovascular Diseases: A Systematic Review with Meta-Regression and Meta-Analysis of Within-Study Subgroup Differences.

Yujun Long, Jianzhao Liu, Jiaxin Cai, Qiongqi Zhuang, Ting Cai, Junwen Zhou, Sanbao Chai, Tengfei Lin, Zhirong Yang

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Cardiovascular drugs and therapy, 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

9 authors.

Yujun Long *Department of Computational Biology and Medical Big Data, Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China.
Jianzhao Liu *Department of Computational Biology and Medical Big Data, Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China.
Jiaxin CaiDepartment of Computational Biology and Medical Big Data, Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China.
Qiongqi ZhuangDepartment of Computational Biology and Medical Big Data, Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China.
Ting CaiNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Junwen ZhouNuffield Department of Population Health, University of Oxford, Oxford, UK.
Sanbao ChaiDepartment of Endocrinology and Metabolism, Peking University International Hospital, Beijing, China.
Tengfei LinShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. lintengfei@smu.edu.cn.
Zhirong YangDepartment of Computational Biology and Medical Big Data, Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China. zr.yang@siat.ac.cn.

Funding

National Natural Science Foundation of China 72274193Shenzhen Medical Research Fund A2403063Shenzhen Science and Technology Innovation Program JCYJ20220530154409021
6 · The paper itself

Abstract

purposeEvidence regarding sources of heterogeneity in the efficacy of statins for primary prevention of cardiovascular disease (CVD) remains limited. This study aimed to identify trial-level factors contributing to such heterogeneity.

methodsRelevant studies were systematically identified from a previous systematic review and through searches in PubMed, Embase, and Cochrane up to 20 January 2026. The protocol was registered in PROSPERO (CRD42024579932). Randomized controlled trials (RCTs) in adults without prior CVD that investigated statin treatment were included. Risk of bias was assessed using the Cochrane Risk of Bias tool. Meta-analyses were conducted to pool risk ratios (RRs) and 95% confidence intervals (CIs) for major adverse cardiovascular events (MACE), myocardial infarction (MI), stroke, and cardiovascular death. Univariate meta-regression analyses were conducted to assess the impact of trial-level covariates on the effect sizes, expressed as the ratio of risk ratios (RRR). Within-study subgroup differences were meta-analyzed by pooling ratio of effect sizes. Meta-regression analyses were conducted using complete-case trial-level data.

results25 RCTs (102,667 participants) were included. Compared to no statin treatment, statin treatment was associated with a reduced risk of MACE (RR, 0.73[95% CI, 0.67 to 0.80], P < 0.001), MI (RR, 0.68[95% CI, 0.60 to 0.77], P < 0.001), stroke (RR, 0.76[95% CI, 0.65 to 0.89], P = 0.001) and cardiovascular death (RR, 0.81[95% CI, 0.71 to 0.95], P = 0.008). Univariate meta-regression indicated that higher baseline total cholesterol (RRR, 1.29 [95% CI, 1.07 to 1.57], P = 0.008), higher low-density lipoprotein cholesterol (LDL-C) (RRR, 1.31 [95% CI, 1.07 to 1.62], P = 0.010), higher triglycerides (RRR, 1.81 [95% CI, 1.17 to 2.81], P = 0.008) and lower statin intensity (RRR, 0.74 [95% CI, 0.59 to 0.94], P = 0.015) were significantly associated with reduced efficacy of statins for stroke prevention at the trial level.

conclusionsStatin therapy demonstrated consistent efficacy in CVD prevention across diverse populations, except that baseline lipid profiles and statin intensity may represent exploratory, hypothesis-generating signals of potential effect modification for stroke prevention, warranting further investigation.

Indexed as

CholesterolMeta-analysisPrimary preventionStatinStrokeTreatment effect heterogeneity

Identifiers

What Socratic holds

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Registered trials

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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.