Individualized Prediction of Transition to Psychosis in 1,676 Individuals at Clinical High Risk: Development and Validation of a Multivariable Prediction Model Based on Individual Patient Data Meta-Analysis - Malda, Aaltsje; Boonstra, Nynke; Barf, Hans; de Jong, Steven; Aleman, Andre; Addington, Jean; Pruessner, Marita; Nieman, Dorien; de Haan, Lieuwe; Morrison, Anthony; Riecher-Rössler, Anita; Studerus, Erich; et al. (Frontiers in Psychiatry, 2019)
Background: The Clinical High Risk state for Psychosis (CHR-P) has become the cornerstone of modern preventive psychiatry. The next stage of clinical advancements in this field rests on the ability to formulate a more accurate prognostic estimate at the individual subject level. Individual Participant Data Meta-Analyses (IPD-MA) are robust evidence synthesis methods that can also offer powerful approaches to the development and validation of personalized prognostic models. We present here the first IPD-MA in CHR-P individuals. Methods: A literature search was performed between January 30th 2016 and February 6th, 2016 consulting PubMed, Psychinfo, Picarta, Embase and ISI Web of Science, using search terms ("ultra high risk" OR "clinical high risk" OR "at risk mental state") AND ((conver* OR transition* OR onset OR emerg* OR develop*) AND function* AND psychosis) for both longitudinal and intervention studies that included CHR-P individuals. Clinical knowledge was used to a priori select predictors to be used in the IPD-MA: age, gender, CHR-P subgroup, the severity of attenuated positive symptoms, the severity of attenuated negative psychotic symptoms and level of functioning at baseline. The model thus developed was validated with an extended form of internal validation. Results: Fifteen of the 43 studies identified agreed to share IPD, for a total sample size of 1676. 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% CIs 0.627 - 0.682). Conclusion: This is the first IPD-MA conducted in the largest samples of CHR-P ever collected to date. An individualized prognostic model that was based on clinical predictors available in clinical routine was developed and internally validated, reaching only moderate prognostic performance. Future developments may include the refinement of the prognostic model and its external validation. However, because of the current high diagnostic, prognostic and therapeutic heterogeneity of CHR-P studies, IPD-MAs in this population may have an limited intrinsic power to deliver robust prognostic models.