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.
Highlights
Individualised breast cancer risk prediction models may be key for planning risk-based screening approaches
We found a systematic review of Anothaisintawee et al.,[7] which we used as a source of primary studies
Agreements and disagreements with other reviews In this systematic review, we found that the number of individualised breast cancer risk prediction models has increased steadily over the past three decades
Summary
Individualised 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. We included studies reporting a model to estimate the individualised risk of breast cancer in women in the general population. CONCLUSION: Individualised risk prediction models are promising tools for implementing risk-based screening policies. Personalised risk-based screening going beyond the current ‘one-size fits all' recommendation may increase the effectiveness and benefit-harm balance of breast cancer screening. Individualised risk prediction models for breast cancer are a key element to develop risk-based screening approaches since they are designed to quantify the risk that can predict whether an individual woman would develop breast cancer in a defined period.[6]
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