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Review
. 2023 Feb 9;15(4):1124.
doi: 10.3390/cancers15041124.

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review

Louiza S Velentzis  1   2 , Victoria Freeman  1   3 , Denise Campbell  1 , Suzanne Hughes  1 , Qingwei Luo  1 , Julia Steinberg  1 , Sam Egger  1 , G Bruce Mann  4   5 , Carolyn Nickson  1   2
Affiliations
Review

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review

Louiza S Velentzis et al. Cancers (Basel). .

Abstract

Background: The benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose.

Methods: Population: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST.

Results: Of 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (n = 11), followed by Tyrer-Cuzick (n = 5), BRCAPRO and iCARE-Lit (n = 3). No tool was consistently well-calibrated across multiple studies and breast density or polygenic risk scores did not improve calibration. Most tools identified a risk group with higher rates of observed cancers, but few tools identified lower-risk groups across different settings. All tools demonstrated a high risk of bias.

Conclusion: Some risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.

Keywords: breast cancer screening; risk assessment; risk prediction models; risk-based screening.

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Conflict of interest statement

LSV, VF and DC have received salary support via the grant from the Australian Government, Department of Health (see funding section) paid to their institution. CN leads the ROSA project which has received the above-named funding.

Figures

Figure 1
Figure 1
Flow diagram based on the PRISMA 2020 flow chart summarising the article screening process.
Figure 2
Figure 2
Absolute risk calibration and observed rate of incident breast cancer by 5-year risk. The three groups shown are: (A) Tyrer-Cuzick vs. BCRAT or other tool comparisons; (B) BCRAT vs. BCRAT modifications; (C) BCRAT vs. other risk assessment tools. Plots are then presented according to first author name. (The number of data points in each graph is determined by the number of risk groups that were reported in each study. To assist with comparison of studies, the x-axis shows the percentile distribution of groups being reported, with data points shown for the mid-points of each group. Red squares show the ‘expected over observed’ ratio for each risk group (with 95% confidence intervals shown), indicating calibration between expected and observed cancers at a risk group level. Blue circles show the corresponding observed rate of breast cancers within the study group, indicating the gradient of rates across the risk groups (expected to increase from left to right in accordance with increases in estimated breast cancer risk). Italic font indicates the risk tool being assessed, with the study cohort abbreviation also shown). * tools were calibrated to local population.
Figure 2
Figure 2
Absolute risk calibration and observed rate of incident breast cancer by 5-year risk. The three groups shown are: (A) Tyrer-Cuzick vs. BCRAT or other tool comparisons; (B) BCRAT vs. BCRAT modifications; (C) BCRAT vs. other risk assessment tools. Plots are then presented according to first author name. (The number of data points in each graph is determined by the number of risk groups that were reported in each study. To assist with comparison of studies, the x-axis shows the percentile distribution of groups being reported, with data points shown for the mid-points of each group. Red squares show the ‘expected over observed’ ratio for each risk group (with 95% confidence intervals shown), indicating calibration between expected and observed cancers at a risk group level. Blue circles show the corresponding observed rate of breast cancers within the study group, indicating the gradient of rates across the risk groups (expected to increase from left to right in accordance with increases in estimated breast cancer risk). Italic font indicates the risk tool being assessed, with the study cohort abbreviation also shown). * tools were calibrated to local population.
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