Evidence map›Paper›PMID 33842335›Full record

ReviewFrontiers in oncology2021

Metabolic Syndrome and Breast Cancer: Prevalence, Treatment Response, and Prognosis.

Shuwen Dong, Zheng Wang, Kunwei Shen, Xiaosong Chen

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 3 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

64 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  7. International journal of molecular sciences · 2026
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  15. Age-Related Trends in Breast Cancer Incidence.International journal of breast cancer · 2026
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4 more citing papers are in PubMed but not listed here.

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

4 authors.

Shuwen DongDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zheng WangDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Kunwei ShenDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaosong ChenDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic syndrome is a type of multifactorial metabolic disease with the presence of at least three factors: obesity, diabetes mellitus, low high-density lipoprotein, hypertriglyceridemia, and hypertension. Recent studies have shown that metabolic syndrome and its related components exert a significant impact on the initiation, progression, treatment response, and prognosis of breast cancer. Metabolic abnormalities not only increase the disease risk and aggravate tumor progression but also lead to unfavorable treatment responses and more treatment side effects. Moreover, biochemical reactions caused by the imbalance of these metabolic components affect both the host general state and organ-specific tumor microenvironment, resulting in increased rates of recurrence and mortality. Therefore, this review discusses the recent advances in the association of metabolic syndrome and breast cancer, providing potential novel therapeutic targets and intervention strategies to improve breast cancer outcome.

Indexed as

breast cancerincidencemetabolic syndromeobesityprognosistreatment response

Identifiers

PMID33842335
PMCPMC8027241

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.