ArticleBMC cancer2020
Relationship between formulaic breast volume and risk of breast cancer based on linear measurements.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
The trial behind it
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Difference in breast size between the first and third trimesters of pregnancy and changes in a woman's body size, subcutaneous fat tissue, and biochemical parameters.Scientific reports · 2026Article
- Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.Journal of applied clinical medical physics · 2025Article
- Comparative assessment of breast volume using a smartphone device versus MRI.Breast cancer (Tokyo, Japan) · 2025Article
- Machine learning-based classification model to differentiate subtypes of invasive breast cancer using MRI.Frontiers in oncology · 2025Article
- Evaluation of the accuracy of heart dose prediction by machine learning for selecting patients not requiring deep inspiration breath‑hold radiotherapy after breast cancer surgery.Experimental and therapeutic medicine · 2023Article
- [GMIA-Breast Oncoplastic and Reconstruction Society consensus on operative standards of breast cancer surgery].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements, was present by applying propensity score matching (PSM).
methodsThe study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders.
resultsThere was a significant difference in breast volume between the two groups before propensity score matching (P = 0.014). Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group(P = 0.009, OR = 1.002, 95%CI:1.000 ~ 1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446).
conclusionsAfter PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.
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