Evidence map›Paper›PMID 42488102›Full record

ArticleFrontiers in oncology2026

Higher Framingham steatosis index is associated with prevalent breast cancer in women: cross-sectional evidence from NHANES 1999-2018 and an exploratory hospital-based dataset.

Shuling Tang, Yong Mo, Tiansheng Su, Guangxiang Huang, Jiachao Lu, Jianbin Bi, Hui Li, Ligen Mo, Jun Yan

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Article in Frontiers in oncology, 2026. 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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5 · Who and what money

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9 authors.

Shuling Tang *Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Yong Mo *Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Tiansheng SuDepartment of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Guangxiang HuangDepartment of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Jiachao LuDepartment of Neurosurgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Jianbin BiDepartment of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Hui LiDepartment of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Ligen MoDepartment of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Jun YanDepartment of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Metabolic dysfunction and hepatic steatosis-related phenotypes have increasingly been linked to extrahepatic malignancies, including breast cancer. The association between the Framingham Steatosis Index (FSI), a composite index incorporating age and multiple metabolic components, and prevalent breast cancer in women has not been well characterized. Methods: We conducted a cross-sectional analysis of female participants in the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Multivariable logistic regression models were used to evaluate the association between FSI and prevalent breast cancer, with FSI analyzed as both a continuous variable and by quartiles. Restricted cubic spline analysis and generalized additive modeling were applied to assess potential non-linearity, and two-piecewise logistic regression was used to explore a possible threshold effect. Component-level and AUC analyses compared FSI with its individual components. An exploratory hospital-based supportive dataset was analyzed to assess whether the continuous association showed a similar direction in a different clinical setting. Results: Among 21,042 women in NHANES, 531 (2.5%) reported a history of breast cancer. In the fully adjusted model, each 1-unit increase in FSI was associated with higher odds of prevalent breast cancer (OR 1.10, 95% CI 1.05-1.16). After additional adjustment for age, the association was substantially attenuated and no longer statistically significant (OR 1.02, 95% CI 0.96-1.07). Higher FSI quartiles were also associated with greater odds of prevalent breast cancer. Restricted cubic spline analysis suggested a non-linear association. In component-level analyses, age showed the strongest association and discriminatory performance among the FSI components, whereas adding FSI to the base model only modestly increased the AUC. In the exploratory hospital-based dataset, FSI was positively associated with breast cancer case status when modeled continuously, but the quartile-based dose-response pattern was not reproduced after full adjustment. Conclusions: In the primary NHANES analysis, higher FSI was associated with prevalent breast cancer status in women; however, this association was substantially attenuated after additional adjustment for age. FSI should therefore be interpreted as a composite marker of metabolic-hepatic burden rather than as an age-independent hepatic steatosis effect or causal biomarker.

Indexed as

breast cancercross-sectional studyFramingham steatosis indexhepatic steatosismetabolic dysfunctionNHANES

Identifiers

PMID42488102
PMCPMC13388184

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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.