Development and validation of a multivariable prediction model based on individual patient data meta-analysis

Summary

The Clinical High Risk state for Psychosis (CHR-P) has become the cornerstone of modern preventive psychiatry. The next stage of clinical advancements rests on the ability to formulate a more accurate prognostic estimate at the individual subject level. Individual participant data meta-analyses are robust evidence synthesis methods that can also offer powerful approaches to the development and validation of personalized prognostic models. In this study, we first conducted a systematic review and extracted 43 studies. Fifteen of the 43 studies identified agreed to share individual participant data, for a total sample size of 1,676. There was a high level of heterogeneity between the CHR-P studies with regard to inclusion criteria, type of assessment instruments, transition criteria, preventive treatment offered. The internally validated prognostic performance of the model was higher than chance but only moderate [Harrell’s C-statistic 0.655, 95% confidence interval (CIs), 0.627–0.682]. To deliver robust prognostic models, studies with less heterogeneity will be needed.

 

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