Evidence map›Paper›PMID 40331129›Full record

ArticleBreast care (Basel, Switzerland)2025

Analysis of Lifestyle and Genetic Risk Factors in Urban Women in China Who Had Malignant or Suspected Malignant Breast Nodules Identified via Breast Cancer Screening.

Jun-Luan Mo, Lin Lei, Xi Li, Hong-Hao Zhou, Li-Jun Zhang, Wen-Xu Hong, Ji-Ye Yin

Abstract read
In one paragraph

Article in Breast care (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

7 authors.

Jun-Luan MoShenzhen Center for Chronic Disease Control, Shenzhen, PR China.
Lin LeiShenzhen Center for Chronic Disease Control, Shenzhen, PR China.
Xi LiDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, PR China.
Hong-Hao ZhouDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, PR China.
Li-Jun ZhangMedical Genetics Center, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, PR China.
Wen-Xu HongShenzhen Center for Chronic Disease Control, Shenzhen, PR China.
Ji-Ye YinDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Breast cancer seriously endangers women's health. It is very important to analyze the lifestyle and genetic risk factors for people with malignant or suspected malignant nodules in breast cancer screening for the prevention of breast cancer. Methods: A total of 3,142 urban female residents in southern China completed a clinical screening for breast cancer. The participants completed questionnaires on living environmental factors and underwent clinical imaging examinations and genetic testing of 73 SNP loci. According to the BI-RADS classification results, the population was divided into positive and negative groups. Key factors were identified through intergroup differences and association analysis. Lifestyle models, SNP models, and lifestyle + PRS models were constructed. ROC curves and nomograms were used to evaluate the classification effect of the model. Results: There were 10 lifestyle factors that were significantly different between the groups, 4 of which were significantly associated with positive breast imaging results ( Conclusion: Advocating breastfeeding, reducing the intake of high-fat diets, and protecting breast health may help lower the risk of positive results in breast screenings. The combination of lifestyle factors and genetic factors can enhance the predictive power of the model.

Indexed as

Breast cancerLifestylePolygenic risk scoreRisk predictionSingle nucleotide polymorphisms

Identifiers

PMID40331129
PMCPMC12052347

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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.