PMID- 27535081 OWN - NLM STAT- MEDLINE DCOM- 20170724 LR - 20201220 IS - 1745-1701 (Electronic) IS - 0586-7614 (Print) IS - 0586-7614 (Linking) VI - 43 IP - 2 DP - 2017 Mar 1 TI - Improving Prognostic Accuracy in Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive Models and Meta-analytical Sequential Testing Simulation. PG - 375-388 LID - 10.1093/schbul/sbw098 [doi] AB - Discriminating subjects at clinical high risk (CHR) for psychosis who will develop psychosis from those who will not is a prerequisite for preventive treatments. However, it is not yet possible to make any personalized prediction of psychosis onset relying only on the initial clinical baseline assessment. Here, we first present a systematic review of prognostic accuracy parameters of predictive modeling studies using clinical, biological, neurocognitive, environmental, and combinations of predictors. In a second step, we performed statistical simulations to test different probabilistic sequential 3-stage testing strategies aimed at improving prognostic accuracy on top of the clinical baseline assessment. The systematic review revealed that the best environmental predictive model yielded a modest positive predictive value (PPV) (63%). Conversely, the best predictive models in other domains (clinical, biological, neurocognitive, and combined models) yielded PPVs of above 82%. Using only data from validated models, 3-stage simulations showed that the highest PPV was achieved by sequentially using a combined (clinical + electroencephalography), then structural magnetic resonance imaging and then a blood markers model. Specifically, PPV was estimated to be 98% (number needed to treat, NNT = 2) for an individual with 3 positive sequential tests, 71%-82% (NNT = 3) with 2 positive tests, 12%-21% (NNT = 11-18) with 1 positive test, and 1% (NNT = 219) for an individual with no positive tests. This work suggests that sequentially testing CHR subjects with predictive models across multiple domains may substantially improve psychosis prediction following the initial CHR assessment. Multistage sequential testing may allow individual risk stratification of CHR individuals and optimize the prediction of psychosis. CI - (c) The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. FAU - Schmidt, Andre AU - Schmidt A AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. FAU - Cappucciati, Marco AU - Cappucciati M AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. FAU - Radua, Joaquim AU - Radua J AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - FIDMAG Germanes Hospitalaries, CIBERSAM, Barcelona, Spain. AD - Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. FAU - Rutigliano, Grazia AU - Rutigliano G AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. FAU - Rocchetti, Matteo AU - Rocchetti M AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. FAU - Dell'Osso, Liliana AU - Dell'Osso L AD - Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. FAU - Politi, Pierluigi AU - Politi P AD - Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. FAU - Borgwardt, Stefan AU - Borgwardt S AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - Department of Psychiatry, University of Basel, Basel, Switzerland. FAU - Reilly, Thomas AU - Reilly T AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. FAU - Valmaggia, Lucia AU - Valmaggia L AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. FAU - McGuire, Philip AU - McGuire P AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - OASIS Team, South London and the Maudsley NHS Foundation Trust, London, UK. FAU - Fusar-Poli, Paolo AU - Fusar-Poli P AD - Department of Psychosis Studies PO63, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. AD - OASIS Team, South London and the Maudsley NHS Foundation Trust, London, UK. LA - eng PT - Journal Article PT - Meta-Analysis PT - Review PT - Systematic Review PL - United States TA - Schizophr Bull JT - Schizophrenia bulletin JID - 0236760 SB - IM MH - Humans MH - *Models, Theoretical MH - *Prognosis MH - Psychotic Disorders/*diagnosis/diagnostic imaging/physiopathology PMC - PMC5605272 OTO - NOTNLM OT - clinical high-risk OT - early interventions OT - prediction OT - prognostic accuracy OT - psychosis OT - treatment prognosis EDAT- 2016/08/19 06:00 MHDA- 2017/07/25 06:00 PMCR- 2016/08/17 CRDT- 2016/08/19 06:00 PHST- 2016/08/19 06:00 [pubmed] PHST- 2017/07/25 06:00 [medline] PHST- 2016/08/19 06:00 [entrez] PHST- 2016/08/17 00:00 [pmc-release] AID - sbw098 [pii] AID - 10.1093/schbul/sbw098 [doi] PST - ppublish SO - Schizophr Bull. 2017 Mar 1;43(2):375-388. doi: 10.1093/schbul/sbw098.