ArticlePloS one2022
Personalized breast cancer onset prediction from lifestyle and health history information.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Personalized Lifestyle Interventions for Prevention and Treatment of Obesity-Related Cancers: A Call to Action.Cancers · 2025Article
- Survival models and longitudinal medical events for hospital readmission forecasting.BMC health services research · 2024Article
- An Effective Meaningful Way to Evaluate Survival Models.Proceedings of machine learning research · 2023Article
- Big data in breast cancer: Towards precision treatment.Digital healthReview
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We propose a method to predict when a woman will develop breast cancer (BCa) from her lifestyle and health history features. To address this objective, we use data from the Alberta's Tomorrow Project of 18,288 women to train Individual Survival Distribution (ISD) models to predict an individual's Breast-Cancer-Onset (BCaO) probability curve. We show that our three-step approach-(1) filling missing data with multiple imputations by chained equations, followed by (2) feature selection with the multivariate Cox method, and finally, (3) using MTLR to learn an ISD model-produced the model with the smallest L1-Hinge loss among all calibrated models with comparable C-index. We also identified 7 actionable lifestyle features that a woman can modify and illustrate how this model can predict the quantitative effects of those changes-suggesting how much each will potentially extend her BCa-free time. We anticipate this approach could be used to identify appropriate interventions for individuals with a higher likelihood of developing BCa in their lifetime.
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Registered trials
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