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Prognostic models predicting transition to psychotic disorder using blood-based biomarkers-a systematic review and critical appraisal.pdf (2.06 MB)

Prognostic models predicting transition to psychotic disorder using blood-based biomarkers: a systematic review and critical appraisal

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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. 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 the risk of bias and applicability of the studies. A narrative synthesis of the included studies was performed. Seventeen 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. 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. 

Funding

Wellcome Flagship Innovations Award (IMPETUS - 220438Z/20/Z)

Science Foundation Ireland (SFI) under Grant Number 16/RC/3948

European Regional Development Fund

FutureNeuro industry partners

Health Research Board Investigator Led Project Grant (ILP-POR-2017-039)

European Research Council Consolidator Award (iHEAR 724809)

Health Research Board Investigator Led Project Grant (ILP-PHR-2019-009)

Irish Clinical Academic Training (ICAT) Programme supported by the Wellcome Trust and the Health Research Board (Grant Number 203930/B/16/Z)

Health Service Executive National Doctors Training and Planning

Health and Social Care, Research and Development Division, Northern Ireland

Health Research Board Psychosis Ireland Structured Training and Research (PSI-STAR) Programme

History

Comments

The original article is available at https://www.nature.com/

Published Citation

Byrne JF, et al. Prognostic models predicting transition to psychotic disorder using blood-based biomarkers: a systematic review and critical appraisal. Transl Psychiatry. 2023;13(1):333.

Publication Date

28 October 2023

PubMed ID

37898606

Department/Unit

  • Psychiatry
  • FutureNeuro Centre

Publisher

Springer Nature Limited

Version

  • Published Version (Version of Record)