Modeling the Longitudinal Effects of Insight on Depression, Quality of Life and Suicidality in Schizophrenia Spectrum Disorders: Results from the FACE-SZ Cohort

International audienceBackground: Up to half of the patients with schizophrenia attempt suicide during their lifetime. Better insight is associated with better functioning but also with increased suicidality. The direction of the relationship between insight and suicidality is not clear, hence we aimed to provide new elements using structural equation modeling. Methods: Insight, quality of life (QoL), depression, and suicidality were measured at baseline and at 12 months in individuals with schizophrenia spectrum disorders. The relationships between these variables were investigated by latent difference score models, controlling for chlorpromazine doses, positive and negative symptoms, and general psychopathology. Results: 738 patients were included, and 370 completed the study. Baseline levels of insight predicted changes in suicidality, whereas baseline levels of suicidality did not predict changes in insight, suggesting that better insight underlies suicidality and predicts its worsening. Our results suggest this temporal sequence: better insight → worse QoL → increased depression → increased suicidality, while insight also affects the three variables in parallel. Conclusion: Better insight predicts a worsening of QoL, depression and suicidality. These findings contribute to our global understanding of the longitudinal influence of insight on suicidality. We advocate that insight-targeted interventions should not be proposed without the monitoring of depression and suicide prevention

Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset

International audienceSchizophrenia is characterized by the most salient medication adherence problems among severe mental disorders, but limited prospective data are available to predict and improve adherence in this population. This investigation aims to identify predictors of medication adherence over a 1-year period in a large national cohort using clustering analysis. Outpatients were recruited from ten Schizophrenia Expert Centers and were evaluated with a day-long standardized battery including clinician and patient-rated medication adherence measures. A two-step cluster analysis and multivariate logistic regression were conducted to identify medication adherence profiles based on the Medication Adherence rating Scale (MARS) and baseline predictors. A total of 485 participants were included in the study and medication adherence was significantly improved at the 1-year follow-up. Higher depressive scores, lower insight, history of suicide attempt, younger age and alcohol use disorder were all associated with poorer adherence at 1 year. Among the 203 patients with initially poor adherence, 86 (42%) switched to good adherence at the 1-year follow-up, whereas 117 patients (58%) remained poorly adherent. Targeting younger patients with low insight, history of suicide, alcohol use disorder and depressive disorders should be prioritized through literacy and educational therapy programs. Adherence is a construct that can vary considerably from year to year in schizophrenia, and therefore may be amenable to interventions for its improvement. However, caution is also warranted as nearly one in five patients with initially good adherence experienced worsened adherence 1 year later

Convergence of patient- and physician-reported outcomes in the French National Registry of Facioscapulohumeral Dystrophy

International audienceFacioscapulohumeral muscular dystrophy (FSHD) is among the most prevalent muscular dystrophies and currently has no treatment. Clinical and genetic heterogeneity are the main challenges to a full comprehension of the physiopathological mechanism. Improving our knowledge of FSHD is crucial to the development of future therapeutic trials and standards of care. National FSHD registries have been set up to this end. The French National Registry of FSHD combines a clinical evaluation form (CEF) and a self-report questionnaire (SRQ), filled out by a physician with expertise in neuromuscular dystrophies and by the patient, respectively. Aside from favoring recruitment, our strategy was devised to improve data quality. Indeed, the pairwise comparison of data from 281 patients for 39 items allowed for evaluating data accuracy. Kappa or intra-class coefficient (ICC) values were calculated to determine the correlation between answers provided in both the CEF and SRQ. Results Patients and physicians agreed on a majority of questions common to the SRQ and CEF (24 out of 39). Demographic, diagnosis- and care-related questions were generally answered consistently by the patient and the medical practitioner (kappa or ICC values of most items in these groups were greater than 0.8). Muscle function-related items, i.e. FSHD-specific signs, showed an overall medium to poor correlation between data provided in the two forms; the distribution of agreements in this section was markedly spread out and ranged from poor to good. In particular, there was very little agreement regarding the assessment of facial motricity and the presence of a winged scapula. However, patients and physicians agreed very well on the Vignos and Brooke scores. The report of symptoms not specific to FSHD showed general poor consistency. Conclusions Patient and physician answers are largely concordant when addressing quantitative and objective items. Consequently, we updated collection forms by relying more on patient-reported data where appropriate. We hope the revised forms will reduce data collection time while ensuring the same quality standard. With the advent of artificial intelligence and automated decision-making, high-quality and reliable data are critical to develop top-performing algorithms to improve diagnosis, care, and evaluate the efficiency of upcoming treatments