Prognostic prediction models for diabetic retinopathy progression: a systematic review

With the increasing incidence of diabetic retinopathy and its improved detection, there is increased demand for diabetic retinopathy treatment services. Prognostic prediction models have been used to optimise services but these were intended for early detection of sight-threatening retinopathy and are mostly used in diabetic retinopathy screening services. We wanted to look into the predictive ability and applicability of the existing models for the higher-risk patients referred into hospitals. We searched MEDLINE, EMBASE, COCHRANE CENTRAL, conference abstracts and reference lists of included publications for studies of any design using search terms related to diabetes, diabetic retinopathy and prognostic models. Search results were screened for relevance to the review question. Included studies had data extracted on model characteristics, predictive ability and validation. They were assessed for quality using criteria specified by PROBAST and CHARMS checklists, independently by two reviewers. Twenty-two articles reporting on 14 prognostic models (including four updates) met the selection criteria. Eleven models had internal validation, eight had external validation and one had neither. Discriminative ability with c-statistics ranged from 0.57 to 0.91. Studies ranged from low to high risk of bias, mostly due to the need for external validation or missing data. Participants, outcomes, predictors handling and modelling methods varied. Most models focussed on lower-risk patients, the majority had high risk of bias and doubtful applicability, but three models had some applicability for higher-risk patients. However, these models will also need updating and external validation in multiple hospital settings before being implemented into clinical practice.