Background:

the identification of patients at higher risk of progressing to kidney failure is essential for treatment planning in chronic kidney disease, but it has not been possible to do this consistently. Predictive models could be a useful tool, however, their usability in chronic kidney disease is limited and the barriers and limitations are not well understood.

Methods:

a scoping review of the available literature on ESRD predictive models or prognostic rules in chronic kidney disease patients was developed. Searches were systematically executed on Cochrane, MEDLINE, and Embase. a blind and independent review was carried out by two evaluators to identify studies that reported on the development, validation, or impact assessment of a model constructed to predict the progression to an advanced stage of chronic kidney disease. A critical evaluation of the quality of the evidence provided with the GRADE system (Grading of Recommendations Assessment, Development and Evaluation) was made.

Findings:

of 1279 articles found, 19 studies were included for the final qualitative synthesis. Most of the studies were primary, with retrospective observational designs and a few corresponded to systematic reviews. No clinical practice guidelines were found. The qualitative synthesis showed high heterogeneity in the development of the models, as well as in the reporting of global performance measures, internal validity, and the lack of external validity in most of the studies. The evidence rating was of low overall quality, with inconsistency between studies and important methodological limitations.

Conclusions:

most of the available predictive models have not been adequately validated and, therefore, are of limited use to assess the individual prognosis of patients with chronic kidney disease. Therefore, additional efforts are required to focus the development and implementation of predictive models on external validity and usability and bridge the gap between generation, synthesis of evidence, and decision-making in the field of patient care.

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