A systematic review of prognostic prediction models describing clinical outcomes in patients diagnosed with visceral leishmaniasis

Background Visceral leishmaniasis (VL) is a neglected tropical disease prevalent in populations affected by poverty and poor nutrition. Without treatment, death is the norm. Prognostic models can steer important management decisions by identifying patients at high-risk of adverse outcomes. We therefore aim to identify, summarise, and appraise the available prognostic models predicting clinical outcomes in VL patients. Methods We reviewed all published studies that developed, validated, or updated models predicting clinical outcomes in VL patients. Five bibliographic databases were searched from database inception to March 1st 2023 with no language restriction. Screening, data extraction, and risk of bias assessment were performed in duplicate. Findings are presented with tables, figures, and a narrative review. Results Eight studies, published 2003-21, were identified describing 12 model developments and 19 external validations. All models predicted either in-hospital mortality (n=10 models) or registry-reported mortality (n=2), and were developed in either Brazilian or East African settings (n=9 and n=3 models respectively). Model discrimination (c-statistic) ranged from 0.62-0.92 when evaluated in new data (19 external validations, 10 models). Risk of bias was high for all model developments and validations: no studies presented calibration plots, 11 models were at high risk of overfitting due to small sample sizes, and six models presented risk scores that were inconsistent with reported regression coefficients. Conclusion With a high risk of bias identified for all models, caution must be exercised when interpreting model predictions and performance measures. Prior to model development or validation, we encourage investigators to review model reporting guidelines. No prognostic models were identified predicting treatment failure or relapse. Furthermore, despite South Asia representing the highest VL burden pre-2010, no models were developed in this population. In the context of the current South Asia elimination programme, these represent important evidence gaps where new model development should be prioritised. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any direct funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript and supplemental material