Criteria for Keratoconus Progression: A Systematic Review of Diagnostic Test Accuracy.

PURPOSE: The aim of this study was to perform a systematic review of diagnostic test accuracy of the criteria used to define keratoconus progression. METHODS: A systematic search of MEDLINE/PubMed, EMBASE, Web of Science Core Collection, and Cochrane Central Register of Controlled Trials (CENTRAL) databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines, from inception to December 31, 2024. The study protocol was preregistered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023391880). Risk of bias was assessed with the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2). Eligible references included randomized controlled trials, cohort studies, cross-sectional studies, and case-control studies assessing the diagnostic accuracy of criteria used to define keratoconus progression, calculating sensitivity, specificity, and diagnostic odds ratio. RESULTS: Fifteen studies (2 prospective and 13 retrospective) were included, comprising 3547 eyes from 2654 individual patients. Overall, best-performing diagnostic tests for keratoconus progression were Belin/Ambrósio Enhanced Ectasia Display (BAD-D); ABCD 1 criteria >95 confidence interval; and anterior best-fit sphere radius, with maximum mean sensitivity/specificity values of 0.82/0.98, 0.81/1.00, and 0.86/0.94, respectively. In 2 studies, maximum keratometry (Kmax) had high specificity (0.91 and 1.00), but low sensitivity (0.70 and 0.49). Image criteria were poorer discriminators: deep learning of color-coded maps showed very low specificity (below 0.60) while anterior segment optical coherence tomography lacked sensitivity (below 0.68). CONCLUSIONS: Composite indexes combining multiple data such as BAD-D and ABCD, or global measurements of the corneal surfaces, such as best-fit sphere radius, might be ideal criteria to define disease progression, instead of single-point measurements.