Evidence map›Paper›PMID 40666099›Full record

SynthesisFrontiers in oncology2025

Impact of blood lipid levels on breast cancer prognosis: a systematic review and meta-analysis.

Jiaqing Song, Ying Jin, Qinghong Yu, Hongting Wu, Xiufei Gao

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Jiaqing SongThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Ying JinThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Qinghong YuThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Hongting WuThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Xiufei GaoThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast cancer has emerged as the predominant malignant neoplasm globally, with potential implications for patient prognosis based on blood lipid profiles. This study aims to systematically review and meta-analyze the influence of lipid levels on the prognostic outcomes of individuals with breast cancer. Methods: A thorough search was performed across multiple academic databases, including Embase, Cochrane, PubMed, Web of Science, CNKI, and Wanfang Database, up to March 2024. A meta-analysis was conducted to assess the impact of total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) on the prognosis of Breast Cancer. The primary outcome measure was hazard ratios (HR) for overall survival (OS) and/or disease-free survival (DFS). Results: Eight studies meeting inclusion criteria from a total of 13,292 were included in the meta-analysis. The systematic review and meta-analysis demonstrate an association between lower HDL-C levels and poorer survival outcomes. However, the statistical analysis did not find significant associations between HDL-C, TG, and LDL-C levels and the prognosis of breast cancer patients. Conclusion: While our analysis reveals a link between reduced HDL-C levels and unfavorable survival outcomes, the statistical evidence does not support significant connections between HDL-C, TG, and LDL-C concentrations and the prognostic landscape for breast cancer patients. Further research is warranted to explore these relationships more comprehensively. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42021297118.

Indexed as

blood lipid levelsbreast cancerdisease-free survivaloverall survivalprognosis

Identifiers

PMID40666099
PMCPMC12260459

What OpenQuestion holds

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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 OpenQuestion graph.