Can structured integration of BI-RADS criteria by a clinical decision rule reduce the number of unnecessary biopsies in BI-RADS 4 lesions? A systematic review and meta-analysis

Abstract

Aim: This systematic review and meta-analysis investigate the added value of structured integration of Breast Imaging Reporting and Data System (BI-RADS) criteria using the Kaiser score (KS) to avoid unnecessary biopsies in BI-RADS 4 lesions.

Material and methods: A systematic review and meta-analysis were conducted using predefined criteria. Eligible articles, published in English until May 2024, dealt with KS in the context of BI-RADS 4 MRI. Two reviewers extracted study characteristics, including true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN). Sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio were calculated using bivariate random effects. Fagan nomograms identified the maximum pre-test probability at which post-test probabilities of a negative MRI aligned with the 2% malignancy rate benchmark for downgrading BI-RADS 4 to BI-RADS 3. I² statistics and meta-regression explored sources of heterogeneity. p-values < 0.05 were considered significant.

Results: Seven studies with 1877 lesions (833 malignant, 1044 benign) were included. The average breast cancer prevalence was 47.3%. Pooled sensitivity was 94.3% (95%-CI 88.9%-97.1%), and pooled specificity was 68.1% (95%-CI 56.6%-77.7%) using a random effects model. Overall, 52/833 cases were FNs (6.2%). Fagan nomograms showed that KS could rule out breast cancer in BI-RADS 4 lesions at a pre-test probability of 20.3% for all lesions, 25.4% for masses, and 15.2% for non-mass lesions.

Conclusions: In MRI-assessed BI-RADS 4 lesions, applying structured BI-RADS criteria with the KS reduces unnecessary biopsies by 70% with a 6.2% FN rate. Breast cancer can be ruled out up to pre-test probabilities of 20.3%.

Key points: Question What, if any, value is added by structured integration of BI-RADS criteria using the Kaiser Score (KS) to avoid unnecessary biopsies in BI-RADS 4 lesions? Findings The structured integration of BI-RADS criteria using the Kaiser Score (KS) reduces unnecessary biopsies in BI-RADS 4 lesions by 70%. Clinical relevance The structured approach offered by the Kaiser Score (KS) avoids unnecessary recalls, potentially reducing patient anxiety, lessening the burden on medical personnel, and the need for further imaging and biopsies due to more objective and thus efficient clinical decision-making in evaluating BI-RADS 4 lesions.

Keywords: Breast; Clinical decision rule; Evidence-based medicine; Imaging; Sensitivity and specificity.

Fig. 1

Preferred reporting items for systematic reviews and meta-analyses 2020 flowchart showing the systematic search results and the selection process towards the included studies. CEM, contrast-enhanced mammography

Fig. 2

QUADAS-2 assessment. Results show a low risk of bias and no concerns regarding the applicability of the included studies

Fig. 3

Forest plot of sensitivity and specificity data synthesis using a random effects model (Kaiser score readings)

Fig. 4

Summary ROC curve derived from bivariate modeling of sensitivity and specificity from individual studies utilizing the Kaiser score in BI-RADS 4 lesions

Fig. 5

Fagan nomograms based on pooled (random effects modeling) negative likelihood ratios for all lesions (A), mass lesions (B), and non-mass lesions (C). Thick lines represent the pooled summary estimate, while the thin lines represent its 95% CI. The lines focus on the 2% post-test probability benchmark for BI-RADS 3. The left part of the nomogram thus depicts the pre-test probability range up to which a negative structured BI-RADS assessment using the Kaiser score can downgrade BI-RADS 4 lesions to BI-RADS 3 to potentially avoid biopsy