TianHong Zhang1, LiHua Xu1, HuiJun Li2, Kristen A Woodberry3,4, Emily R Kline3, Jian Jiang1, HuiRu Cui1, YingYing Tang1, XiaoChen Tang1, YanYan Wei1, Li Hui5, Zheng Lu6, LiPing Cao7, ChunBo Li1, Margaret A Niznikiewicz8, Martha E Shenton9, Matcheri S Keshavan8, William S Stone3, JiJun Wang1,10,11. 1. Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai200030, China. 2. Department of Psychology, Florida A and M University, Tallahassee, Florida32307, USA. 3. Harvard Medical School Department of Psychiatry, Beth Israel Deaconess Medical Center, 75 Fenwood Rd, Boston, MA02115, USA. 4. Center for Psychiatric Research, Maine Medical Center Research Institute, Portland, Maine. 5. Institute of Mental Health, The Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou215137, Jiangsu, China. 6. Department of Psychiatry, Tongji Hospital, Tongji University, School of Medicine, Shanghai, China. 7. Department of Early Intervention, Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou510370, China. 8. Harvard Medical School Department of Psychiatry, Veteran's Administration Medical Center, Boston, MA02130, USA. 9. Departments of Psychiatry and Radiology, Brigham and Women's Hospital, and Harvard Medical School, and VA Boston Healthcare System, Boston, MA, USA. 10. Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai, China. 11. CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.
Abstract
BACKGROUND: Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program. METHOD: In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC. RESULTS: The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal. CONCLUSIONS: The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.
BACKGROUND: Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program. METHOD: In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC. RESULTS: The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal. CONCLUSIONS: The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.
Entities:
Keywords:
Outcome; prediction; prodromal psychosis; transition; ultra high risk