ArticleActa oncologica (Stockholm, Sweden)2015
Breast cancer specialists' views on and use of risk prediction models in clinical practice: a mixed methods approach.
Article in Acta oncologica (Stockholm, Sweden), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cost-Effectiveness Analyses of the 21-Gene Assay in Breast Cancer: Systematic Review and Critical Appraisal.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2018Pooled it
- Patient- and Physician-Identified Considerations for Clinical Implementation of a New Risk-Based Prediction Tool to Guide Surveillance Mammography in Breast Cancer Survivors.JCO oncology practice · 2026Article
- Risk-Prediction Models for Clinical Decision-Making in Sarcoma Care: An International Survey Among Soft-Tissue Sarcoma Clinicians.Annals of surgical oncology · 2025Article
- Improving shared decision-making about cancer treatment through design-based data-driven decision-support tools and redesigning care paths: an overview of the 4D PICTURE project.Palliative care and social practice · 2024Article
- Article
- A nomogram for individually predicting overall survival for elderly patients with early breast cancer: a consecutive cohort study.Frontiers in oncology · 2023Article
- Discussing personalized prognosis in amyotrophic lateral sclerosis: development of a communication guide.BMC neurology · 2020Article
- How to optimize the design and implementation of risk prediction tools: focus group with patients with IgA nephropathy.BMC medical informatics and decision making · 2020Article
- A Value of Information Analysis of Research on the 21-Gene Assay for Breast Cancer Management.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2019Article
- Use of the BOADICEA Web Application in clinical practice: appraisals by clinicians from various countries.Familial cancer · 2018Article
- Prognostic & predictive factors for planning adjuvant chemotherapy of early-stage breast cancer.The Indian journal of medical research · 2017Review
- The impact of doctor-patient communication on patients' perceptions of their risk of breast cancer recurrence.Breast cancer research and treatment · 2017Article
- Validity of the online PREDICT tool in older patients with breast cancer: a population-based study.British journal of cancer · 2016Article
- The predictive accuracy of PREDICT: a personalized decision-making tool for Southeast Asian women with breast cancer.Medicine · 2015Observational
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeRisk prediction models (RPM) in breast cancer quantify survival benefit from adjuvant systemic treatment. These models [e.g. Adjuvant! Online (AO)] are increasingly used during consultations, despite their not being designed for such use. As still little is known about oncologists' views on and use of RPM to communicate prognosis to patients, we investigated if, why, and how they use RPM.
methodsWe disseminated an online questionnaire that was based on the literature and individual and group interviews with oncologists.
resultsFifty-one oncologists (partially) completed the questionnaire. AO is the best known (95%) and most frequently used RPM (96%). It is used to help oncologists decide whether or not to recommend chemotherapy (>85%), to inform (86%) and help patients decide about treatment (>80%), or to persuade them to follow the proposed course of treatment (74%). Most oncologists (74%) believe that using AO helps patients understand their prognosis.
conclusionRPM have found a place in daily practice, especially AO. Oncologists think that using AO helps patients understand their prognosis, yet studies suggest that this is not always the case. Our findings highlight the importance of exploring whether patients understand the information that RPM provide.
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