ArticleThe British journal of radiology2016
Utility of relative and absolute measures of mammographic density vs clinical risk factors in evaluating breast cancer risk at time of screening mammography.
Article in The British journal of radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- The Prognostic Quality of Risk Prediction Models to Assess the Individual Breast Cancer Risk in Women: An Overview of Reviews.The breast journal · 2024Review
- Feature Selection Using Correlation Analysis and Principal Component Analysis for Accurate Breast Cancer Diagnosis.Journal of imaging · 2021Article
- Mammographic Breast Density Assessed with Fully Automated Method and its Risk for Breast Cancer.Journal of clinical imaging science · 2019Article
- Breast density scales: the metric matters.The British journal of radiology · 2017Article
- Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad.Diagnostics (Basel, Switzerland) · 2017Review
- Beyond breast density: a review on the advancing role of parenchymal texture analysis in breast cancer risk assessment.Breast cancer research : BCR · 2016Review
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Authors and funding
6 authors.
Funding
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Abstract
objectiveVarious clinical risk factors, including high breast density, have been shown to be associated with breast cancer. The utility of using relative and absolute area-based breast density-related measures was evaluated as an alternative to clinical risk factors in cancer risk assessment at the time of screening mammography.
methodsContralateral mediolateral oblique digital mammography images from 392 females with unilateral breast cancer and 817 age-matched controls were analysed. Information on clinical risk factors was obtained from the provincial breast-imaging information system. Breast density-related measures were assessed using a fully automated breast density measurement software. Multivariable logistic regression was conducted, and area under the receiver-operating characteristic (AUROC) curve was used to evaluate the performance of three cancer risk models: the first using only clinical risk factors, the second using only density-related measures and the third using both clinical risk factors and density-related measures.
resultsThe risk factor-based model generated an AUROC of 0.535, while the model including only breast density-related measures generated a significantly higher AUROC of 0.622 (p < 0.001). The third combined model generated an AUROC of 0.632 and performed significantly better than the risk factor model (p < 0.001) but not the density-related measures model (p = 0.097).
conclusionDensity-related measures from screening mammograms at the time of screen may be superior predictors of cancer compared with clinical risk factors. ADVANCES IN KNOWLEDGE: Breast cancer risk models based on density-related measures alone can outperform risk models based on clinical factors. Such models may support the development of personalized breast-screening protocols.
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