Background Our objective was to perform a systematic review and meta-analysis comparing the breast cancer detection rate (CDR), invasive CDR, recall rate, and positive predictive value 1 (PPV1) of digital mammography (DM) alone, combined digital breast tomosynthesis (DBT) and DM, combined DBT and synthetic 2-dimensional mammography (S2D), and DBT alone. Methods MEDLINE and Embase were searched until April 2020 to identify comparative design studies reporting on patients undergoing routine breast cancer screening. Random effects model proportional meta-analyses estimated CDR, invasive CDR, recall rate, and PPV1. Meta-regression modeling was used to compare imaging modalities. All statistical tests were 2-sided. Results Forty-two studies reporting on 2 606 296 patients (13 003 breast cancer cases) were included. CDR was highest in combined DBT and DM (6.36 per 1000 screened, 95% confidence interval [CI] = 5.62 to 7.14, P < .001), and combined DBT and S2D (7.40 per 1000 screened, 95% CI = 6.49 to 8.37, P < .001) compared with DM alone (4.68 per 1000 screened, 95% CI = 4.28 to 5.11). Invasive CDR was highest in combined DBT and DM (4.53 per 1000 screened, 95% CI = 3.97 to 5.12, P = .003) and combined DBT and S2D (5.68 per 1000 screened, 95% CI = 4.43 to 7.09, P < .001) compared with DM alone (3.42 per 1000 screened, 95% CI = 3.02 to 3.83). Recall rate was lowest in combined DBT and S2D (42.3 per 1000 screened, 95% CI = 37.4 to 60.4, P<.001). PPV1 was highest in combined DBT and DM (10.0%, 95% CI = 8.0% to 12.0%, P = .004), and combined DBT and S2D (16.0%, 95% CI = 10.0% to 23.0%, P < .001), whereas no difference was detected for DBT alone (7.0%, 95% CI = 6.0% to 8.0%, P = .75) compared with DM alone (7.0%, 95.0% CI = 5.0% to 8.0%). Conclusions Our findings provide evidence on key performance metrics for DM, DBT alone, combined DBT and DM, and combined DBT and S2D, which may inform optimal application of these modalities for breast cancer screening.

Objective: To evaluateProstate Imaging Reporting and Data System (PI-RADS) category three lesions impact on diagnostic test accuracy (DTA) of MRI for prostate cancer (PC) and to derive prevalence of PC within each PI-RADS category. Methods: MEDLINE and Embase were searched for studies reporting on the DTA of MRI by PI-RADS category. Accuracy metrics were calculated using a bivariate random-effects meta-analysis with PI-RADS three lesions treated as a positive test, negative test, and excluded from the analysis. Differences in DTA were assessed utilizing meta-regression.PC prevalenceby PI-RADS category was estimated with proportional meta-analysis. Results: Twenty-six studies reporting on 12,913 patients (4,853 with PC) were included.Sensitivity for PC in the positive, negative, and excluded test groups was 96% (95%-confidence interval [CI]92–98), 82% (CI75-87), and 95% (CI91-97), respectively. Specificity for the positive, negative, and excluded test groups were 33%(CI23-44), 71% (CI62-79),and 52% (CI37-66), respectively. Meta-regression demonstrated higher sensitivity (p < 0.001) and lower specificity (p < 0.001) in the positive test group compared to the negative group. Clinically significant PC prevalence was 5.9% (CI0-17.1), 11.4% (CI 6.5–17.3), 24.9% (CI18.4–32.0), 55.7% (CI47.8–63.5), and 81.4% (CI75.9–86.4)for PI-RADS categories 1, 2, 3, 4, and 5, respectively. Conclusion: PI-RADS three lesions can significantly impact the DTA of MRI for PC detection. A low prevalence of clinically significant PC is noted in PI-RADS category1 and 2 cases. Advances in knowledge: Inclusion or exclusion of PI-RADS category three lesions impacts the DTA of MRI for PC detection.