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• W4386573010 abstract "Abstract Background Accumulating evidence suggests individuals with psychotic disorder show abnormalities in metabolic and inflammatory processes. Recently, several studies have employed blood-based predictors in models predicting transition to psychotic disorder in risk-enriched populations. A systematic review of the performance and methodology of prognostic models using blood-based biomarkers in the prediction of psychotic disorder from risk-enriched populations is warranted. Methods Databases (PubMed, EMBASE and PsycINFO) were searched for eligible texts from 1998 to 15/05/2023 which detailed model development or validation studies. The checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) was used to guide data extraction from eligible texts and the Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess risk of bias and applicability of the studies. A narrative synthesis of included studies was performed. Results 17 eligible studies were identified: 16 eligible model development studies and one eligible model validation study. A wide range of biomarkers were assessed including nucleic acids, proteins, metabolites and lipids. The range of C-index (area under the curve) estimates reported for the models was 0.67-1.00. No studies assessed model calibration. According to PROBAST criteria, all studies were at high risk of bias in the analysis domain. Discussion While a wide range of potentially predictive biomarkers were identified in the included studies, most studies did not account for overfitting in model performance estimates, no studies assessed calibration, and all models were at high risk of bias according to PROBAST criteria. External validation of the models is needed to provide more accurate estimates of their performance. Future studies which follow the latest available methodological and reporting guidelines and adopt strategies to accommodate required sample sizes for model development or validation will clarify the value of including blood-based biomarkers in models predicting psychosis." @default.
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• W4386573010 date "2023-09-08" @default.
• W4386573010 modified "2023-09-30" @default.
• W4386573010 title "Prognostic models predicting transition to psychotic disorder using blood-based biomarkers: a systematic review and critical appraisal." @default.
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• W4386573010 doi "https://doi.org/10.1101/2023.09.08.23295245" @default.
• W4386573010 hasPublicationYear "2023" @default.
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