Unraveling the Influence of Age, IQ, Education, and Negative Symptoms on Neurocognitive Performance in Schizophrenia: A Conditional Inference Tree Analysis

作者：Xenia M. Hart, Yasue Mitsukura, Robert R. Bies, Hiroyuki Uchida · 发表于：Pharmacopsychiatry · 年份：2024 · DOI：10.1055/a-2258-0379 · 被引用次数：5 · 研究领域：Schizophrenia research and treatment、Mental Health Research Topics、Functional Brain Connectivity Studies

Abstract Introduction The complex nature of neurocognitive impairment in schizophrenia has been discussed in light of the mixed effects of antipsychotic drugs, psychotic symptoms, dopamine D2 receptor blockade, and intelligence quotient (IQ). These factors have not been thoroughly examined before. Methods This study conducted a comprehensive re-analysis of the CATIE data using machine learning techniques, in particular Conditional Inference Tree (CTREE) analysis, to investigate associations between neurocognitive functions and moderating factors such as estimated trough dopamine D2 receptor blockade with risperidone, olanzapine, or ziprasidone, Positive and Negative Syndrome Scale (PANSS), and baseline IQ in 573 patients with schizophrenia. Results The study reveals that IQ, age, and education consistently emerge as significant predictors across all neurocognitive domains. Furthermore, higher severity of PANSS-negative symptoms was associated with lower cognitive performance scores in several domains. CTREE analysis, in combination with a genetic algorithm approach, has been identified as particularly insightful for illustrating complex interactions between variables. Lower neurocognitive function was associated with factors such as age>52 years, IQ<94/95,<12/13 education years, and more pronounced negative symptoms (score<26). Conclusions These findings emphasize the multifaceted nature of neurocognitive functioning in patients with schizophrenia, with the PANSS-...