Ting Yat Wong1,2, Sherry Kit Wa Chan1,3, Charlton Cheung1, Christy Lai Ming Hui1, Yi Nam Suen1, Wing Chung Chang1,3, Edwin Ho Ming Lee1, Eric Yu Hai Chen1,3. 1. Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR. 2. Department of Psychiatry, Perelman School of Medicine, Brain Behavior Laboratory, University of Pennsylvania, Philadelphia, PA 19104, USA. 3. The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR.
Abstract
OBJECTIVES: Patients with schizophrenia have a significant risk of self-harm. We aimed to explore the dynamic relationship between symptomatology, functioning and deliberate self-harm (DSH) and evaluate the feasibility of developing a self-harm risk prediction tool for patients with first-episode schizophrenia (FES). METHODS: Patients with FES (n = 1234) were followed up for 36 months. Symptomatology, functioning, treatment adherence and self-harm information were obtained monthly over the follow-up period. A time-varying vector autoregressive (VAR) model was used to study the contribution of clinical variables to self-harm over the 36th month. Random forest models for self-harm were established to classify the individuals with self-harm and predict future self-harm events. RESULTS: Over a 36-month period, 187 patients with FES had one or more self-harm events. The depressive symptoms contributed the most to self-harm prediction during the first year, while the importance of positive psychotic symptoms increased from the second year onwards. The random forest model with all static information and symptom instability achieved a good area under the receiver operating characteristic curve (AUROC = 0.77 ± 0.023) for identifying patients with DSH. With a sliding window analysis, the averaged AUROC of predicting a self-event was 0.65 ± 0.102 (ranging from 0.54 to 0.78) with the best model being 6-month predicted future 6-month self-harm for month 11-23 (AUROC = 0.7). CONCLUSIONS: Results highlight the importance of the dynamic relationship of depressive and positive psychotic symptoms with self-harm and the possibility of self-harm prediction in FES with longitudinal clinical data.
OBJECTIVES: Patients with schizophrenia have a significant risk of self-harm. We aimed to explore the dynamic relationship between symptomatology, functioning and deliberate self-harm (DSH) and evaluate the feasibility of developing a self-harm risk prediction tool for patients with first-episode schizophrenia (FES). METHODS: Patients with FES (n = 1234) were followed up for 36 months. Symptomatology, functioning, treatment adherence and self-harm information were obtained monthly over the follow-up period. A time-varying vector autoregressive (VAR) model was used to study the contribution of clinical variables to self-harm over the 36th month. Random forest models for self-harm were established to classify the individuals with self-harm and predict future self-harm events. RESULTS: Over a 36-month period, 187 patients with FES had one or more self-harm events. The depressive symptoms contributed the most to self-harm prediction during the first year, while the importance of positive psychotic symptoms increased from the second year onwards. The random forest model with all static information and symptom instability achieved a good area under the receiver operating characteristic curve (AUROC = 0.77 ± 0.023) for identifying patients with DSH. With a sliding window analysis, the averaged AUROC of predicting a self-event was 0.65 ± 0.102 (ranging from 0.54 to 0.78) with the best model being 6-month predicted future 6-month self-harm for month 11-23 (AUROC = 0.7). CONCLUSIONS: Results highlight the importance of the dynamic relationship of depressive and positive psychotic symptoms with self-harm and the possibility of self-harm prediction in FES with longitudinal clinical data.
Authors: Sherry Kit Wa Chan; Christy Lai Ming Hui; Wing Chung Chang; Edwin Ho Ming Lee; Eric Yu Hai Chen Journal: Schizophr Res Date: 2018-08-17 Impact factor: 4.939
Authors: Kristin Lie Romm; Jan Ivar Rossberg; Akiah Ottesen Berg; Elizabeth Ann Barrett; Ann Faerden; Ingrid Agartz; Ole A Andreassen; Ingrid Melle Journal: J Nerv Ment Dis Date: 2010-01 Impact factor: 2.254
Authors: Lindsay A Bornheimer; Jessica A Wojtalik; Juliann Li; Derin Cobia; Matthew J Smith Journal: Schizophr Res Date: 2021-01-23 Impact factor: 4.939