Sexual dysfunction in first-episode schizophrenia patients: results from European First Episode Schizophrenia Trial

Sexual dysfunctions (SDs) occur frequently in schizophrenia patients and have a huge impact on quality of life and compliance. They are often associated with antipsychotic medication. Nicotine consumption, negative or depressive symptoms, and physical illness are also discussed as contributing factors. Data on SD in first-episode schizophrenia patients are scarce.As part of the European First Episode Schizophrenia Trial, first-episode schizophrenia patients were randomly assigned to 5 medication groups. We assessed SD by analyzing selected items from the Udvalg for Kliniske Undersugelser at baseline and at 5 following visits.Differences between antipsychotics were small for all SDs, and fairly little change in the prevalence of SDs was seen over the course of the study. A significantly larger increase of amenorrhea and galactorrhea was seen with amisulpride than with the other medications. In men, higher age, more pronounced Positive and Negative Syndrome Scale general psychopathology symptoms, and higher plasma prolactin levels predicted higher rates of erectile and ejaculatory dysfunctions. Positive and Negative Syndrome Scale negative symptoms and higher age were predictors for decreased libido.In women, higher prolactin plasma levels were identified as a predictor of amenorrhea. Positive and Negative Syndrome Scale negative symptoms predicted decreased libido.All evidence taken together underscores the influence of the disease schizophrenia itself on sexual functioning. In addition, there is a strong correlation between the prolactin-increasing properties of amisulpride and menstrual irregularities

AI-based prediction of depression symptomatology in first-episode psychosis patients: insights from the EUFEST and RAISE-ETP clinical trials

Background: Depressive symptoms are highly prevalent in first-episode psychosis (FEP) and worsen clinical outcomes. It is currently difficult to determine which patients will have persistent depressive symptoms based on a clinical assessment. We aimed to determine whether depressive symptoms and post-psychotic depressive episodes can be predicted from baseline clinical data, quality of life, and blood-based biomarkers, and to assess the geographical generalizability of these models. Methods: Two FEP trials were analyzed: European First-Episode Schizophrenia Trial (EUFEST) (n = 498; 2002–2006) and Recovery After an Initial Schizophrenia Episode Early Treatment Program (RAISE-ETP) (n = 404; 2010–2012). Participants included those aged 15–40 years, meeting Diagnostic and Statistical Manual of Mental Disorders IV criteria for schizophrenia spectrum disorders. We developed support vector regressors and classifiers to predict changes in depressive symptoms at 6 and 12 months and depressive episodes within the first 6 months. These models were trained in one sample and externally validated in another for geographical generalizability. Results: A total of 320 EUFEST and 234 RAISE-ETP participants were included (mean [SD] age: 25.93 [5.60] years, 56.56% male; 23.90 [5.27] years, 73.50% male). Models predicted changes in depressive symptoms at 6 months with balanced accuracy (BAC) of 66.26% (RAISE-ETP) and 75.09% (EUFEST), and at 12 months with BAC of 67.88% (RAISE-ETP) and 77.61% (EUFEST). Depressive episodes were predicted with BAC of 66.67% (RAISE-ETP) and 69.01% (EUFEST), showing fair external predictive performance. Conclusions: Predictive models using clinical data, quality of life, and biomarkers accurately forecast depressive events in FEP, demonstrating generalization across populations

Multivariable prediction of functional outcome after first-episode psychosis:a crossover validation approach in EUFEST and PSYSCAN

Several multivariate prognostic models have been published to predict outcomes in patients with first episode psychosis (FEP), but it remains unclear whether those predictions generalize to independent populations. Using a subset of demographic and clinical baseline predictors, we aimed to develop and externally validate different models predicting functional outcome after a FEP in the context of a schizophrenia-spectrum disorder (FES), based on a previously published cross-validation and machine learning pipeline. A crossover validation approach was adopted in two large, international cohorts (EUFEST, n = 338, and the PSYSCAN FES cohort, n = 226). Scores on the Global Assessment of Functioning scale (GAF) at 12 month follow-up were dichotomized to differentiate between poor (GAF current &lt; 65) and good outcome (GAF current ≥ 65). Pooled non-linear support vector machine (SVM) classifiers trained on the separate cohorts identified patients with a poor outcome with cross-validated balanced accuracies (BAC) of 65-66%, but BAC dropped substantially when the models were applied to patients from a different FES cohort (BAC = 50-56%). A leave-site-out analysis on the merged sample yielded better performance (BAC = 72%), highlighting the effect of combining data from different study designs to overcome calibration issues and improve model transportability. In conclusion, our results indicate that validation of prediction models in an independent sample is essential in assessing the true value of the model. Future external validation studies, as well as attempts to harmonize data collection across studies, are recommended.</p

Scalability of the Positive and Negative Syndrome Scale in first-episode schizophrenia assessed by Rasch models

Objective: Historically, assessment of the psychometric properties of the Positive and Negative Syndrome Scale (PANSS) has had several foci: (1) calculation of reliability indexes, (2) extraction of subdimensions from the scale, and (3) assessment of the validity of the total score. In this study, we aimed to examine the scalability and to assess the clinical performance of the 30-item PANSS total score as well as the scalability of a shorter version (PANSS-6) of the scale. Methods: A composite data set of 1073 patients with first-episode schizophrenia or schizophrenia spectrum disorder was subjected to Rasch analysis of PANSS data from baseline and 4–6 weeks follow-up. Results: The central tests of fit of the Rasch model failed to satisfy the statistical requirements behind item homogeneity for the PANSS-30 as well as the PANSS-6 total score. For the PANSS-30, Differential Item Functioning was pronounced both for the 7-point Likert scale rating categories and when dichotomizing the rating categories. Subsequently, the Rasch structure analysis in the context of dichotomized items was used to isolate and estimate a systematic error because of item inhomogeneity, as well as a random error. The size of the combined sources of error for the PANSS-30 total score approximated 20% which is often regarded as clinical cut-off between response versus no-response. Conclusion: The results demonstrate the operational consequences of a lack of statistical fit of the Rasch model and suggest that the calculated measure of uncertainty needs to be considered when using the PANSS-30 total score

Symptom Remission and Brain Cortical Networks at First Clinical Presentation of Psychosis: The OPTiMiSE Study

Individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, that may be particularly prominent, already at illness onset, in those more likely to have poorer symptom remission following treatment with the first antipsychotic. The identification of strong neuroanatomical markers of symptom remission could thus facilitate stratification and individualized treatment of patients with schizophrenia. We used magnetic resonance imaging at baseline to examine brain regional and network correlates of subsequent symptomatic remission in 167 medication-naïve or minimally treated patients with first-episode schizophrenia, schizophreniform disorder, or schizoaffective disorder entering a three-phase trial, at seven sites. Patients in remission at the end of each phase were randomized to treatment as usual, with or without an adjunctive psycho-social intervention for medication adherence. The final follow-up visit was at 74 weeks. A total of 108 patients (70%) were in remission at Week 4, 85 (55%) at Week 22, and 97 (63%) at Week 74. We found no baseline regional differences in volumes, cortical thickness, surface area, or local gyrification between patients who did or did not achieved remission at any time point. However, patients not in remission at Week 74, at baseline showed reduced structural connectivity across frontal, anterior cingulate, and insular cortices. A similar pattern was evident in patients not in remission at Week 4 and Week 22, although not significantly. Lack of symptom remission in first-episode psychosis is not associated with regional brain alterations at illness onset. Instead, when the illness becomes a stable entity, its association with the altered organization of cortical gyrification becomes more defined

The cross-sectional GRAS sample: A comprehensive phenotypical data collection of schizophrenic patients

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia.</p> <p>Methods</p> <p>For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected.</p> <p>Results</p> <p>The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail.</p> <p>Conclusions</p> <p>The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.</p