SynthesisBritish journal of cancer2019
A systematic review and quality assessment of individualised breast cancer risk prediction models.
Synthesis in British journal of cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 7 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
83 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- A systematic review of prediction models for risk of breast cancer.BMC cancer · 2025Pooled it
- Clinical prediction models using artificial intelligence approaches in dementia.Aging clinical and experimental research · 2025Pooled it
- Assessing the impact of direct-acting antivirals on hepatitis C complications: a systematic review and meta-analysis.Naunyn-Schmiedeberg's archives of pharmacology · 2024Pooled it
- Repeated measures of mammographic density and texture to evaluate prediction and risk of breast cancer: a systematic review of the methods used in the literature.Cancer causes & control : CCC · 2023Pooled it
- Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe.BMC cancer · 2023Pooled it
- Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature.Breast cancer research : BCR · 2022Pooled it
- Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges.Molecular psychiatry · 2022Pooled it
- Advanced Versus Invasive Breast Cancer Risk in a Screening Population: Implications for Risk-based Prevention and Screening Strategies.Journal of general internal medicine · 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
- 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
- Accelerating discovery of cancer causes for prevention in the era of rising early-onset cancers.Cell · 2026Review
- Knowledge-Guided Explainable Recommendation Tool for Cancer Risk Prediction Models Using Retrieval-Augmented Large Language Models: Development and Validation Study.JMIR medical informatics · 2026Article
- Underserved Latinas' Perceptions and Implications Around Breast Cancer Risk Assessment.Cancer medicine · 2026Article
- Article
- Identification and external validation of a prognostic signature based on myeloid-derived suppressor cells-related LncRNAs to evaluate survival prognosis and treatment efficacy in invasive breast carcinoma.Biochemistry and biophysics reports · 2025Article
- Pathogenic Variants, Family History, and Cumulative Risk of Breast Cancer in US Women.JAMA oncology · 2025Article
- Predicting short- to long-term breast cancer risk from longitudinal mammographic screening history.NPJ breast cancer · 2025Article
- Evaluating mammographic density's contribution to improve a breast cancer risk model with questionnaire-based and polygenic factors.NPJ breast cancer · 2025Article
- Second cancers in 475 000 women with early invasive breast cancer diagnosed in England during 1993-2016: population based observational cohort study.BMJ (Clinical research ed.) · 2025Observational
- Pre-diagnostic serum metabolome and breast cancer risk: a nested case-control study.Breast cancer research : BCR · 2025Article
23 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
backgroundIndividualised breast cancer risk prediction models may be key for planning risk-based screening approaches. Our aim was to conduct a systematic review and quality assessment of these models addressed to women in the general population.
methodsWe followed the Cochrane Collaboration methods searching in Medline, EMBASE and The Cochrane Library databases up to February 2018. We included studies reporting a model to estimate the individualised risk of breast cancer in women in the general population. Study quality was assessed by two independent reviewers. Results are narratively summarised.
resultsWe included 24 studies out of the 2976 citations initially retrieved. Twenty studies were based on four models, the Breast Cancer Risk Assessment Tool (BCRAT), the Breast Cancer Surveillance Consortium (BCSC), the Rosner & Colditz model, and the International Breast Cancer Intervention Study (IBIS), whereas four studies addressed other original models. Four of the studies included genetic information. The quality of the studies was moderate with some limitations in the discriminative power and data inputs. A maximum AUROC value of 0.71 was reported in the study conducted in a screening context.
conclusionIndividualised risk prediction models are promising tools for implementing risk-based screening policies. However, it is a challenge to recommend any of them since they need further improvement in their quality and discriminatory capacity.
Indexed as
Identifiers
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.