ArticleCurrent epidemiology reports2020
Factors to Consider in Developing Breast Cancer Risk Models to Implement into Clinical Care.
Article in Current epidemiology reports, 2020. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Performance of Statistical and Machine Learning Risk Prediction Models for Advanced Breast Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- Patient and Physician Perspectives on Using Risk Prediction to Support Breast Cancer Surveillance Decision Making.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- Performance of Statistical and Machine Learning Risk Prediction Models for Surveillance Benefits and Failures in Breast Cancer Survivors.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Effect of Psychological Intervention-Assisted Comfort Nursing Based on PERMA Model on Stress and Psychological Changes of Patients after Breast Cancer Surgery.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
purpose of the reviewThis article outlines considerations for individuals interested in developing and implementing breast cancer risk models and has relevance for individuals developing risk-models with the goal of implementing them into health systems. RECENT
findingsThere has been increased focus on developing risk models for clinical use-often with less attention model implementation. Epidemiologists developing risk-models must think through model outcomes including stakeholder needs, time horizons, terminology and reference groups and clarity on what actionable steps are for health systems, providers and patients following its implementation. SUMMARY: Model performance needs to be evaluated relative to complexity of the model to be implemented-not just from the risk-prediction perspective, but also from the burden on patients, providers and systems for the amount and frequency of required data collection and with clear actionable steps to be taken with the information collected.
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What OpenQuestion holds
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.