DxGoals: A Software Tool for Determining and Analyzing Clinically Meaningful Classification Accuracy Goals for Diagnostic Tests.

Background: To evaluate diagnostic tests for low prevalence conditions, classification accuracy metrics such as sensitivity, specificity, and positive likelihood ratio (PLR) and negative likelihood ratio (NLR) are advantageous because they are prevalence-independent and thus estimable in studies enriched for the condition. However, classification accuracy goals are often chosen without a clear understanding of whether they are clinically meaningful. Pennello (2021) proposed a risk stratification framework for determining classification accuracy goals. A software application is needed to determine the goals and provide data analysis.

Methods: We introduce DxGoals, a freely available, R-Shiny software application for determining, visualizing, and analyzing classification accuracy goals for diagnostic tests. Given prevalence p for the target condition and specification that a test's positive and negative predictive values PPVand NPV=1-cNPV should satisfy PPV>PPV* and cNPV

Results: We illustrate DxGoals on tests for penicillin allergy, ovarian cancer, and cervical cancer. The inputs cNPV*,p, and PPV* were informed by clinical management guidelines.

Conclusions: DxGoals facilitates determination, visualization, and analysis of clinically meaningful standalone and comparative classification accuracy goals. It is a potentially useful tool for diagnostic test evaluation.