Symptomatic, functional and quality of life measures of remission in 194 outpatients with schizophrenia followed naturalistically in a 6-month, non-interventional study of aripiprazole once-monthly.

An important goal in the treatment of patients with schizophrenia is remission in various domains, i.e., of symptoms, psychosocial functioning and subjective well-being. We undertook a post hoc analysis of pre-stabilized outpatients with schizophrenia and complete outcome data who had been enrolled in a 6-month non-interventional study of aripiprazole once-monthly (AOM) at 75 German sites. Key outcomes were (i) symptomatic remission (cross-sectional Andreasen et al. criteria (≤mild positive and negative key symptoms on the Brief Psychiatric Rating Scale (BPRS))); (ii) functional remission (Global Assessment of Functioning (GAF) scale score >70), and (iii) subjective well-being remission (WHO-5 scale score ≥13) at week 24. Of 242 enrolled patients, 194 (80.2%) (age = 43.9 ± 15.3 years; 51.5% male, illness duration = 14.0 ± 12.0 years) with complete data were analyzed. While 61.3% of the patients achieved symptomatic remission and 76.8% achieved remission regarding subjective well-being, only 24.7% achieved psychosocial functioning remission at 6 months. Remission rates were similar for men and women and across strata of disease duration with, on average, less remission in patients with longer illness duration. Correlations of improvements on the BPRS and GAF were weak, with the weakest correlation between the BPRS depressive mood item and the GAF scale, but similarly high correlation between BPRS subscales or the BPRS depressive mood item and subjective well-being. These findings suggest that while treatment with AOM can lead to symptomatic remission and remission regarding subjective well-being, additional interventions such as psychosocial therapy or supported employment and education may be necessary to achieve functional remission.

New insight into the CATIE study by constrained confidence partitioning. An innovative technique towards personalized antipsychotic drug therapy in schizophrenia treatment.

The CATIE schizophrenia trial was a very influential randomized controlled trial in patients with chronic schizophrenia. Patients were followed for up to 18 months under treatment with a randomly assigned antipsychotic. The primary endpoint, time to discontinuation of treatment for any reason, is influenced by individual patient characteristics, external factors as well as effects of drug treatment. New insight is obtained by applying an innovative survival analysis based on constrained confidence partitioning (SA-C2P). Through this data-driven approach we identify homogeneous collectives of patients with similar patient characteristics differing from the study population in the primary endpoint, enabling us to predict patient individual outcome more precisely. A subgroup of patients treated with olanzapine featuring neither an anxiety disorder in the past month, drug abuse in the past five years nor hospitalizations in the past year discontinued drug therapy substantially later compared to patients meeting at least one of the named parameters. Moreover, differences in the primary outcome between second-generation antipsychotics increased compared to the original CATIE analysis when looking into this subgroup in the entire study sample. Our findings suggest that SA-C2P may assist in identifying relevant responder subgroups, probably missed by conventional statistical methods, making it a potential tool for personalized medicine.

Additive scales in degenerative disease--calculation of effect sizes and clinical judgment.

BACKGROUND: The therapeutic efficacy of an intervention is often assessed in clinical trials by scales measuring multiple diverse activities that are added to produce a cumulative global score. Medical communities and health care systems subsequently use these data to calculate pooled effect sizes to compare treatments. This is done because major doubt has been cast over the clinical relevance of statistically significant findings relying on p values with the potential to report chance findings. Hence in an aim to overcome this pooling the results of clinical studies into a meta-analyses with a statistical calculus has been assumed to be a more definitive way of deciding of efficacy. METHODS: We simulate the therapeutic effects as measured with additive scales in patient cohorts with different disease severity and assess the limitations of an effect size calculation of additive scales which are proven mathematically. RESULTS: We demonstrate that the major problem, which cannot be overcome by current numerical methods, is the complex nature and neurobiological foundation of clinical psychiatric endpoints in particular and additive scales in general. This is particularly relevant for endpoints used in dementia research. 'Cognition' is composed of functions such as memory, attention, orientation and many more. These individual functions decline in varied and non-linear ways. Here we demonstrate that with progressive diseases cumulative values from multidimensional scales are subject to distortion by the limitations of the additive scale. The non-linearity of the decline of function impedes the calculation of effect sizes based on cumulative values from these multidimensional scales. CONCLUSIONS: Statistical analysis needs to be guided by boundaries of the biological condition. Alternatively, we suggest a different approach avoiding the error imposed by over-analysis of cumulative global scores from additive scales.

Preferences of psychiatric practitioners for core symptoms of major depressive disorder: a hidden conjoint analysis.

According to ICD-10 and DSM-V, symptoms of depressive disorder are considered to be equally important for severity judgment. It was the goal to investigate the weight of selected symptom complexes for severity judgment. In workaday life severity judgment results from an overall impression rather than from calculating severity in different symptom complexes, separately. In fact, the drivers for overall judgment may not be known explicitly to the psychiatrist himself. A method of choice to resolve this is conjoint analysis. Based on the Montgomery-Asberg Depression Scale (MADRS) and the Sheehan Disability Scale (SDS) case vignettes were constructed. Different symptom severity in the domains mood, vegetative symptoms, cognition/inhibition, suicidality, and everyday functioning were worked into the vignettes. Different symptom complexes influence the severity judgment by clinical psychiatrists to a rather different extent. Mood has a greater impact on severity judgment than suicidality, cognition/inhibition, vegetative symptoms, and everyday functioning. We conclude that core complexes of major depressive disorder are valued with different clinical relevance by psychiatrists. Thus, diagnosis and appraisal of therapeutic efficacy are subject to individual preferences of clinical psychiatrists and prevalence and therapeutic efficacy may be over- or under-estimated unless these differences in preferences are taken into account.