Evidence map›Paper›PMID 41071653›Full record

ArticleThe oncologist2025

Healthy lifestyles, screening, and breast cancer mortality in women with different risk of disease.

Haomin Yang, Hongli Huang, Tao Zhang, Yanyu Zhang, Shuqing Zou, Pingxiu Zhu, Wei He, Yixuan Lin

Abstract read
In one paragraph

Article in The oncologist, 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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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Haomin YangDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China.ORCID 0000-0002-2252-2606
Hongli HuangFuqing Center for Disease Control and Prevention, Fuzhou, Fujian 350399, China.
Tao ZhangDepartment of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian 350122, China.
Yanyu ZhangPeking University Clinical Research Institute, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0003-3354-7064
Shuqing ZouDepartment of Quality Control, Fujian Cancer Hospital, Fuzhou 350014, China.
Pingxiu ZhuPeking University Clinical Research Institute, Peking University Health Science Center, Beijing 100191, China.
Wei HeDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden.ORCID 0000-0003-0161-3274
Yixuan LinDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen 9713, The Netherlands.

Funding

Natural Science Foundation of China 82204132
6 · The paper itself

Abstract

backgroundHealthy lifestyles and screening are the two major interventions to prevent breast cancer mortality. However, their effects have not been compared simultaneously, and it remains unclear whether their benefits differ by women' baseline breast cancer risk.

methodsA prospective cohort study was conducted using the UK biobank linked to national cancer registries, including 261 398 women aged 40-70. Hazard ratios (HRs) and population attributable fractions (PAF) for breast cancer mortality were estimated in relation to healthy lifestyle index (HLI) and screening status, using a Cox regression model. We further examined the interaction between HLI, screening and breast cancer risk predictors (Tyrer-Cuzick score and polygenic risk score [PRS], using highest and lowest 20% as high- and low-risk groups) for breast cancer mortality by likelihood ratio (LR) test.

resultsWomen with a high Tyrer-Cuzick score and PRS were associated with increased breast cancer mortality. HLI was inversely associated with breast cancer mortality (HR = 0.55, 95%CI = 0.42-0.72), and the effect did not differ statistically according to the risk scores. Women who participated in screening programs were at reduced risk of breast cancer mortality (HR = 0.70, 95% CI = 0.52-0.95), particularly among those women with high Tyrer-Cuzick score (P for interaction = .048). The fraction of breast cancer mortality cases that might be prevented (PAF) by screening was 14.27% (95%CI = 4.44-24.09) and by healthy lifestyle was 9.63% (95%CI = 3.10-16.16).

conclusionsAlthough women with a high PRS or Tyrer-Cuzick score is associated with increased breast cancer mortality, deaths are preventable through changing lifestyles and screening. These findings support personalized, risk-based strategies.

Indexed as

Breast NeoplasmsEarly Detection of CancerHealthy LifestyleAdultAgedFemaleHumansMiddle AgedProspective StudiesRisk FactorsUnited Kingdombreast cancerhealthy lifestylesmortalityrisk predictorsscreening

Identifiers

PMID41071653
PMCPMC12605817

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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.