Facing the coronavirus 2019 pandemic, authors worldwide have developed an astonishing amount of diagnostic and prognostic models in a short amount of time. Models should be validated and updated in larger, international datasets representative of the target population and thoroughly peer reviewed before using them in clinical applications. Eventually, those models might help to detect COVID-19 infections in patients with symptoms and predict the course of a diagnosed COVID-19 infection with a high discriminative performance.
However, if not carefully validated for a representative population, models could do more harm than good.
Wynants, L., B. Van Calster, M. M. J. Bonten, G. S. Collins, T. P. A. Debray, M. De Vos, M. C. Haller, G. Heinze, K. G. M. Moons, R. D. Riley, E. Schuit, L. J. M. Smits, K. I. E. Snell, E. W. Steyerberg, C. Wallisch and M. van Smeden (2020). “Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal.” Bmj 369: m1328.