Magdalena Kotlicka-Antczak1, Michał S Karbownik2, Konrad Stawiski3, Agnieszka Pawełczyk4, Natalia Żurner5, Tomasz Pawełczyk6, Dominik Strzelecki7, Paolo Fusar-Poli8. 1. Department of Affective and Psychotic Disorders, Medical University of Lodz, ul. Czechosłowacka 8/10, 92-216 Lodz, Poland. Electronic address: magdalena.kotlicka-antczak@umed.lodz.pl. 2. Department of Pharmacology and Toxicology, Medical University of Lodz, ul. Żeligowskiego 7/9, 90-752 Lodz, Poland. Electronic address: michal.karbownik@umed.lodz.pl. 3. Department of Biostatistics and Translational Medicine, Medical University of Lodz, ul. Mazowiecka 15, 92-215 Lodz, Poland. Electronic address: konrad.stawiski@umed.lodz.pl. 4. Department of Affective and Psychotic Disorders, Medical University of Lodz, ul. Czechosłowacka 8/10, 92-216 Lodz, Poland. Electronic address: agnieszka.pawelczyk@umed.lodz.pl. 5. Adolescent Psychiatry Unit, Central Clinical Hospital, ul. Czechosłowacka 8/10, 92-216 Lodz, Poland. Electronic address: nzurner@gmail.com. 6. Department of Affective and Psychotic Disorders, Medical University of Lodz, ul. Czechosłowacka 8/10, 92-216 Lodz, Poland. Electronic address: tomasz.pawelczyk@umed.lodz.pl. 7. Department of Affective and Psychotic Disorders, Medical University of Lodz, ul. Czechosłowacka 8/10, 92-216 Lodz, Poland. Electronic address: dominik.strzelecki@umed.lodz.pl. 8. Early Psychosis: Interventions and Clinical Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park SE5 8AF London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. Electronic address: paolo.fusar-poli@kcl.ac.uk.
Abstract
OBJECTIVE: The predictive accuracy of the Clinical High Risk criteria for Psychosis (CHR-P) regarding the future development of the disorder remains suboptimal. It is therefore necessary to incorporate refined risk estimation tools which can be applied at the individual subject level. The aim of the study was to develop an easy-to use, short refined risk estimation tool to predict the development of psychosis in a new CHR-P cohort recruited in European country with less established early detection services. METHODS: A cohort of 105 CHR-P individuals was assessed with the Comprehensive Assessment of At Risk Mental States12/2006, and then followed for a median period of 36 months (25th-75th percentile:10-59 months) for transition to psychosis. A multivariate Cox regression model predicting transition was generated with preselected clinical predictors and was internally validated with 1000 bootstrap resamples. RESULTS: Speech disorganization and unusual thought content were selected as potential predictors of conversion on the basis of published literature. The prediction model was significant (p < 0.0001) and confirmed that both speech disorganization (HR = 1.69; 95%CI: 1.39-2.05) and unusual thought content (HR = 1.51; 95%CI: 1.27-1.80) were significantly associated with transition. The prognostic accuracy of the model was adequate (Harrell's c- index = 0.79), even after optimism correction through internal validation procedures (Harrell's c-index = 0.78). CONCLUSIONS: The clinical prediction model developed, and internally validated, herein to predict transition from a CHR-P to psychosis may be a promising tool for use in clinical settings. It has been incorporated into an online tool available at: https://link.konsta.com.pl/psychosis. Future external replication studies are needed.
OBJECTIVE: The predictive accuracy of the Clinical High Risk criteria for Psychosis (CHR-P) regarding the future development of the disorder remains suboptimal. It is therefore necessary to incorporate refined risk estimation tools which can be applied at the individual subject level. The aim of the study was to develop an easy-to use, short refined risk estimation tool to predict the development of psychosis in a new CHR-P cohort recruited in European country with less established early detection services. METHODS: A cohort of 105 CHR-P individuals was assessed with the Comprehensive Assessment of At Risk Mental States12/2006, and then followed for a median period of 36 months (25th-75th percentile:10-59 months) for transition to psychosis. A multivariate Cox regression model predicting transition was generated with preselected clinical predictors and was internally validated with 1000 bootstrap resamples. RESULTS: Speech disorganization and unusual thought content were selected as potential predictors of conversion on the basis of published literature. The prediction model was significant (p < 0.0001) and confirmed that both speech disorganization (HR = 1.69; 95%CI: 1.39-2.05) and unusual thought content (HR = 1.51; 95%CI: 1.27-1.80) were significantly associated with transition. The prognostic accuracy of the model was adequate (Harrell's c- index = 0.79), even after optimism correction through internal validation procedures (Harrell's c-index = 0.78). CONCLUSIONS: The clinical prediction model developed, and internally validated, herein to predict transition from a CHR-P to psychosis may be a promising tool for use in clinical settings. It has been incorporated into an online tool available at: https://link.konsta.com.pl/psychosis. Future external replication studies are needed.