Test-set training is linked to increased breast screening cancer detection rates

Abstract

Mammographic test sets are a simulation-based training methodology for radiologists to assess and improve their performance. However, while test-set records have indicated over-time improvements in participants' performance within the tests, little is known about how those improvements translate into breast-screening readers’ performance in the clinic. This study investigated how the performance of readers who completed test-set training in the BreastScreen Reader Assessment Strategy (BREAST) platform have evolved in comparison to readers who have no history of test-set participation. Investigating 10-year clinical audit data of 46 breast screening readers in New South Wales, Australia indicated that BREAST readers improved their positive predictive value (PPV) (p=0.001) in association with their testset participation. They also had higher detection rates for invasive cancers (p=0.01), ductal carcinoma in situ (DCIS) (p=0.03), and the detection rate of all cancers and DCIS (p=0.01). In comparison, non-BREAST readers improved their recall rate in subsequent screens (p=0.03) and PPV (p=0.02). In conclusion, test-set participation is linked to enhanced capability of cancer detection, which can be due to the high proportion of cancer cases in the test sets in comparison to normal practice.