ReviewBritish journal of cancer2022
The current status of risk-stratified breast screening.
Review in British journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 4 of them syntheses that pooled it.
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
76 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Contribution of mammographic imaging after initial ultrasound in women with focal breast complaints-systematic review.European radiology · 2026Pooled it
- Breast cancer risk prediction using machine learning: a systematic review.Frontiers in oncology · 2024Pooled it
- Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe.BMC cancer · 2023Pooled it
- Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study.BMJ (Clinical research ed.) · 2023Pooled it
- Risk of developing subsequent primary breast cancer among non-breast cancer survivors: a retrospective cohort study.Breast cancer (Tokyo, Japan) · 2026Article
- Real-World Evidence for Breast Cancer Risk Stratification: Insights from the P.I.N.K. Study.Cancers · 2026Article
- Perceptions of the Acceptability of Community-Based Breast Cancer Risk Assessment among Underserved Latinas in Maricopa County, Arizona.Journal of racial and ethnic health disparities · 2026Article
- Five-Year Breast Cancer Risk Prediction From Screening Breast Ultrasound Using Deep Learning.medRxiv : the preprint server for health sciences · 2026Article
- Polygenic Risk Scores for Breast Cancer Among African American Women With High Risk.JAMA network open · 2026Article
- Interventions to Improve Breast Screening Uptake for Black African Women in High Income Countries: A Systematic Review.Journal of racial and ethnic health disparities · 2026Review
- Explainable Artificial Intelligence in Mammography: A Systematic Review of Methods, Evaluation Practices, and Clinical Readiness.Diagnostics (Basel, Switzerland) · 2026Review
- Ensuring Epidemiological Consistency in Risk-Stratified Cancer Screening Models: A Novel Approach Based on Flemish Breast Cancer Screening.Applied health economics and health policy · 2026Article
- Article
- Ethically Integrating Genomics in Primary Care: An Invitation to Share Implementation Best Practices.Mayo Clinic proceedings · 2026Article
- Epidemiology, early detection, and management of breast cancer in China: A comprehensive review.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025Article
- WFIKKN2 is secreted and elevated in blood plasma of HER2-positive breast cancer patients - implications in cancer surveillance and recurrence monitoring.Biomarker research · 2025Article
- Artificial Intelligence-Driven Personalization in Breast Cancer Screening: From Population Models to Individualized Protocols.Cancers · 2025Review
- Alcohol consumption and breast lesions: targets for risk-based screening in high-risk Italian women.Breast cancer (Tokyo, Japan) · 2025Article
- A practical work around for breast density distribution discrepancies between mammographic images from different vendors.European radiology · 2025Article
- Structural equation modeling of factors influencing women's attitudes, comfort and willingness toward risk-stratified breast cancer screening.Scientific reports · 2025Article
16 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Apart from high-risk scenarios such as the presence of highly penetrant genetic mutations, breast screening typically comprises mammography or tomosynthesis strategies defined by age. However, age-based screening ignores the range of breast cancer risks that individual women may possess and is antithetical to the ambitions of personalised early detection. Whilst screening mammography reduces breast cancer mortality, this is at the risk of potentially significant harms including overdiagnosis with overtreatment, and psychological morbidity associated with false positives. In risk-stratified screening, individualised risk assessment may inform screening intensity/interval, starting age, imaging modality used, or even decisions not to screen. However, clear evidence for its benefits and harms needs to be established. In this scoping review, the authors summarise the established and emerging evidence regarding several critical dependencies for successful risk-stratified breast screening: risk prediction model performance, epidemiological studies, retrospective clinical evaluations, health economic evaluations and qualitative research on feasibility and acceptability. Family history, breast density or reproductive factors are not on their own suitable for precisely estimating risk and risk prediction models increasingly incorporate combinations of demographic, clinical, genetic and imaging-related parameters. Clinical evaluations of risk-stratified screening are currently limited. Epidemiological evidence is sparse, and randomised trials only began in recent years.
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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.