ArticleBreast cancer research and treatment2016
iPrevent®: a tailored, web-based, decision support tool for breast cancer risk assessment and management.
Article in Breast cancer research and treatment, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 42 citations in OpenAlex.
- A web-based personalized risk communication and decision-making tool for women with dense breasts: Design and methods of a randomized controlled trial within an integrated health care system.Contemporary clinical trials · 2017Trial
- Article
- A Case Report: 19-Year-Old Hispanic Young Woman with Early-Stage Breast Cancer and a Germline Pathogenic Variant.Medical research archives · 2025Article
- Consumer perspective on breast density notification in Australia.Ecancermedicalscience · 2025Article
- ASSIGN score and cancer risk in the Scottish Heart Health Extended Cohort (SHHEC) study.BJC reports · 2024Article
- Article
- iKNOW-Supporting the counseling of women with hereditary risk of breast and ovarian cancer with digital technologies: A randomized controlled trial.Genetics in medicine open · 2024Article
- Perceptions and Usability of PREVENTION: A Breast Cancer Risk Assessment e-Platform.Journal of personalized medicine · 2023Article
- Proactive breast cancer risk assessment in primary care: a review based on the principles of screening.British journal of cancer · 2023Review
- The co-development of personalised 10-year breast cancer risk communications: a 'think-aloud' study.BMC cancer · 2022Article
- Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study.Journal of medical Internet research · 2022Article
- A Machine-Learning-Based Risk-Prediction Tool for HIV and Sexually Transmitted Infections Acquisition over the Next 12 Months.Journal of clinical medicine · 2022Article
- Decision Aids for Preventive Treatment Alternatives forGeburtshilfe und Frauenheilkunde · 2021Article
- Key steps for effective breast cancer prevention.Nature reviews. Cancer · 2020Review
- Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.Breast (Edinburgh, Scotland) · 2020Article
- Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool.JNCI cancer spectrum · 2019Article
- Uptake of genetic testing for germline BRCA1/2 pathogenic variants in a predominantly Hispanic population.Cancer genetics · 2019Article
- The iPrevent Online Breast Cancer Risk Assessment and Risk Management Tool: Usability and Acceptability Testing.JMIR formative research · 2018Article
- Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data.Geburtshilfe und Frauenheilkunde · 2018Article
- Use of the BOADICEA Web Application in clinical practice: appraisals by clinicians from various countries.Familial cancer · 2018Article
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 2 countries.
Funding
Abstract
We aimed to develop a user-centered, web-based, decision support tool for breast cancer risk assessment and personalized risk management. Using a novel model choice algorithm, iPrevent(®) selects one of two validated breast cancer risk estimation models (IBIS or BOADICEA), based on risk factor data entered by the user. Resulting risk estimates are presented in simple language and graphic formats for easy comprehension. iPrevent(®) then presents risk-adapted, evidence-based, guideline-endorsed management options. Development was an iterative process with regular feedback from multidisciplinary experts and consumers. To verify iPrevent(®), risk factor data for 127 cases derived from the Australian Breast Cancer Family Study were entered into iPrevent(®), IBIS (v7.02), and BOADICEA (v3.0). Consistency of the model chosen by iPrevent(®) (i.e., IBIS or BOADICEA) with the programmed iPrevent(®) model choice algorithm was assessed. Estimated breast cancer risks from iPrevent(®) were compared with those attained directly from the chosen risk assessment model (IBIS or BOADICEA). Risk management interventions displayed by iPrevent(®) were assessed for appropriateness. Risk estimation model choice was 100 % consistent with the programmed iPrevent(®) logic. Discrepant 10-year and residual lifetime risk estimates of >1 % were found for 1 and 4 cases, respectively, none was clinically significant (maximal variation 1.4 %). Risk management interventions suggested by iPrevent(®) were 100 % appropriate. iPrevent(®) successfully integrates the IBIS and BOADICEA risk assessment models into a decision support tool that provides evidence-based, risk-adapted risk management advice. This may help to facilitate precision breast cancer prevention discussions between women and their healthcare providers.
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Registered trials
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 OpenQuestion graph.