Annual Reviews of Statistics just released a paper with an interesting title:
The Enemies of Reliable and Useful Clinical Prediction Models: A Review of Statistical and Scientific Challenges. Here.
Writing,
The current status of applied clinical prediction modeling is poor. Many models are developed with suboptimal methods and are not evaluated, and hence have little impact on clinical care. We review 12 challenges—provocatively labeled enemies—that jeopardize the creation of prediction models that make it to clinical practice to improve treatment decisions and clinical outcomes for individual patients.
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While the focus is on prediction algorithms, many of the challenges map easily onto the adoption, or disappearance, of diagnostic tests as well (e.g. MAAA predictors). The need for impact assessment and implementation studies is highlighted, topics close to genomics.
Their summary figure is worth highlighting (from Royen):
