ArticleBreast cancer research : BCR2015
Breast cancer tumour growth modelling for studying the association of body size with tumour growth rate and symptomatic detection using case-control data.
Article in Breast cancer research : BCR, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 20 citations in OpenAlex.
- An esophageal stent integrated with wireless battery-free movable photodynamic-therapy unit for targeted tumor treatment.Materials today. Bio · 2025Article
- Optimizing breast cancer screening strategies for women with different BMI levels in Ghana: A simulation-based study on BMI-dependent tumor growth model.PLOS global public health · 2025Article
- Evaluation of optimal strategies for breast cancer screening in Ghana: A simulation study based on a continuous tumor growth model.PloS one · 2025Article
- Tumour Growth Models of Breast Cancer for Evaluating Early Detection-A Summary and a Simulation Study.Cancers · 2023Article
- Development and evaluation of a method for tumor growth simulation in virtual clinical trials of breast cancer screening.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Estimating Distributions of Breast Cancer Onset and Growth in a Swedish Mammography Screening Cohort.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022Article
- Radiological audit of interval breast cancers: Estimation of tumour growth rates.Breast (Edinburgh, Scotland) · 2020Article
- Joint models of tumour size and lymph node spread for incident breast cancer cases in the presence of screening.Statistical methods in medical research · 2019Article
- Long-term prognostic implications of risk factors associated with tumor size: a case study of women regularly attending screening.Breast cancer research : BCR · 2018Article
- E-Science technologies in a workflow for personalized medicine using cancer screening as a case study.Journal of the American Medical Informatics Association : JAMIA · 2017Article
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4 authors at 1 institution in 1 country.
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Abstract
introductionA large body size is associated with larger breast cancer tumours at diagnosis. Standard regression models for tumour size at diagnosis are not sufficient for unravelling the mechanisms behind the association.
methodsUsing Swedish case-control data, we identified 1352 postmenopausal women with incident invasive breast cancer diagnosed between 1993 and 1995. We used a novel continuous tumour growth model, which models tumour sizes at diagnosis through three submodels: for tumour growth, time to symptomatic detection, and screening sensitivity. Tumour size at other time points is thought of as a latent variable.
resultsWe quantified the relationship between body size with tumour growth and time to symptomatic detection. High body mass index and large breast size are, respectively, significantly associated with fast tumour growth rate and delayed time to symptomatic detection (combined P value = 5.0 × 10(-5) and individual P values = 0.089 and 0.022). We also quantified the role of mammographic density in screening sensitivity.
conclusionsThe times at which tumours will be symptomatically detected may vary substantially between women with different breast sizes. The proposed tumour growth model represents a novel and useful approach for quantifying the effects of breast cancer risk factors on tumour growth and detection.
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