Leading beyond regulatory approval: Opportunities for statisticians to optimize evidence generation and impact clinical practice.

The role and value of statistical contributions in drug development up to the point of health authority approval are well understood. But health authority approval is only a true 'win' if the evidence enables access and adoption into clinical practice. In today's complex and evolving healthcare environment, there is additional strategic evidence generation, communication, and decision support that can benefit from statistical contributions. In this article, we describe the history of medical affairs in the context of drug development, the factors driving post-approval evidence generation needs, and the opportunities for statisticians to optimize evidence generation for stakeholders beyond health authorities in order to ensure that new medicines reach appropriate patients.

Parahydrogen-Induced Polarization of a Labeled, Cancer-Targeting DNA Aptamer.

Enhancing NMR signals of biomacromolecules by hyperpolarization offers exciting opportunities for diagnostic applications. However, their hyperpolarization via parahydrogen remains challenging as specific catalytic interactions are required, which are difficult to tune due to the large size of the biomolecule and its insolubility in organic solvents. Herein, we show the unprecedented hyperpolarization of the cancer-targeting DNA aptamer AS1411. By screening different molecular motifs for an unsaturated label in nucleosides and in DNA oligomers, we were able to identify structural prerequisites for the hyperpolarization of AS1411. Finally, adjusting the polarity of AS1411 by complexing the DNA backbone with amino polyethylene glycol chains allowed the hydrogenation of the label with parahydrogen while the DNA structure remains stable to maintain its biological function. Our results are expected to advance hyperpolarized molecular imaging technology for disease detection in the future.

Combination of several matching adjusted indirect comparisons (MAICs) with an application in psoriasis.

In health technology assessment (HTA), beside network meta-analysis (NMA), indirect comparisons (IC) have become an important tool used to provide evidence between two treatments when no head-to-head data are available. Researchers may use the adjusted indirect comparison based on the Bucher method (AIC) or the matching-adjusted indirect comparison (MAIC). While the Bucher method may provide biased results when included trials differ in baseline characteristics that influence the treatment outcome (treatment effect modifier), this issue may be addressed by applying the MAIC method if individual patient data (IPD) for at least one part of the AIC is available. Here, IPD is reweighted to match baseline characteristics and/or treatment effect modifiers of published data. However, the MAIC method does not provide a solution for situations when several common comparators are available. In these situations, assuming that the indirect comparison via the different common comparators is homogeneous, we propose merging these results by using meta-analysis methodology to provide a single, potentially more precise, treatment effect estimate. This paper introduces the method to combine several MAIC networks using classic meta-analysis techniques, it discusses the advantages and limitations of this approach, as well as demonstrates a practical application to combine several (M)AIC networks using data from Phase III psoriasis randomized control trials (RCT).

What matters most? Different stakeholder perspectives on estimands for an invented case study in COPD.

In drug development, we ask ourselves which population, endpoint and treatment comparison should be investigated. In this context, we also debate what matters most to the different stakeholders that are involved in clinical drug development, for example, patients, physicians, regulators and payers. With the publication of draft ICH E9 addendum on estimands in 2017, we now have a common framework and language to discuss such questions in an informed and transparent way. This has led to the estimand discussion being a key element in study development, including design, analysis and interpretation of a treatment effect. At an invited session at the 2018 PSI annual conference, PSI hosted a role-play debate where the aim of the session was to mimic a regulatory and payer scientific advice discussion for a COPD drug. Including role-play views from an industry sponsor, a patient, a regulator and a payer. This paper presents the invented COPD case-study design and considerations relating to appropriate estimands are discussed by each of the stakeholders from their differing viewpoints with the additional inclusion of a technical (academic) perspective. The rationale for each perspective on approaches for handling intercurrent events is presented, with a key emphasis on the application of while-on-treatment and treatment policy estimands in this context. It is increasingly recognised that the treatment effect estimated by the treatment policy approach may not always be of primary clinical interest and may not appropriately communicate to patients the efficacy they can expect if they take the treatment as directed.

A statistical method to convert published response rates into marginal distributions with an example application in psoriasis.

Assessment of severity is essential for the management of chronic diseases. Continuous variables like scores obtained from the Hamilton Rating Scale for Depression or the Psoriasis Area and Severity Index (PASI) are standard measures used in clinical trials of depression and psoriasis. In clinical trials of psoriasis, for example, the reduction of PASI from baseline in response to therapy, in particular the proportion of patients achieving at least 75%, 90%, or 100% improvement of disease (PASI 75, PASI 90, or PASI 100), is typically used to evaluate treatment efficacy. However, evaluation of the proportions of patients reaching absolute PASI values (eg, ≤1, ≤2, ≤3, or ≤5) has recently gained greater clinical interest and is increasingly being reported. When relative versus absolute scores are standard, as is the case with the PASI in psoriasis, it is difficult to compare absolute changes using existing published data. Thus, we developed a method to estimate absolute PASI levels from aggregated relative levels. This conversion method is based on a latent 2-dimensional normal distribution for the absolute score at baseline and at a specific endpoint with a truncation to allow for baseline inclusion criterion. The model was fitted to aggregated results from simulations and from 3 phase III studies that had known absolute PASI proportions. The predictions represented the actual results quite precisely. This model might be applied to other conditions, such as depression, to estimate proportions of patients achieving an absolute low level of disease activity, given absolute values at baseline and proportions of patients achieving relative improvements at a subsequent time point.

Structured Benefit-risk assessment: a review of key publications and initiatives on frameworks and methodologies.

Introduction The conduct of structured benefit-risk assessment (BRA) of pharmaceutical products is a key area of interest for regulatory agencies and the pharmaceutical industry. However, the acceptance of a standardized approach and implementation are slow. Statisticians play major roles in these organizations, and have a great opportunity to be involved and drive the shaping of future BRA. Method We performed a literature search of recent reviews and initiatives assessing BRA methodologies, and grouped them to assist those new to BRA in learning, understanding, and choosing methodologies. We summarized the key points and discussed the impact of this emerging field on various stakeholders, particularly statisticians in the pharmaceutical industry. Results We provide introductory, essential, special interest, and further information and initiatives materials that direct readers to the most relevant materials, which were published between 2000 and 2013. Based on recommendations in these materials we supply a toolkit of advocated BRA methodologies. Discussion Despite initiatives promoting these methodologies, there are still barriers, one of which being the lack of a consensus on the most appropriate methodologies among stakeholders. However, this opens up opportunities, for statisticians in the pharmaceutical industry especially, to champion appropriate BRA methodology use throughout the pharmaceutical product lifecycle. Conclusions This article may serve as a starting point for discussions and to reach a mutual consensus for methodology selection in a particular situation. Regulators and pharmaceutical industry should continue to collaborate to develop and take forward BRA methodologies, and by clear communication develop a mutual understanding of the key issues. Copyright © 2015 John Wiley & Sons, Ltd.

Patient expectations in the treatment of painful diabetic polyneuropathy: results from a non-interventional study.

OBJECTIVE: Pain control is the main objective when treating patients with painful diabetic peripheral neuropathic pain (DPNP). However, DPNP is associated with further substantial patient burden that often is not appropriately addressed. Our study identified patients' needs and asked patients what they expected from DPNP treatment. METHODS: Baseline data were collected in a German prospective, non-interventional study in patients with DPNP starting or switching pain medication at the discretion of the investigator. DPNP severity was evaluated using Brief Pain Inventory (BPI) and Clinician/Patient Global Impression-Severity (CGI-S/PGI-S). Primary objective of this study was to evaluate for which interference item of the BPI DPNP patients expected most to improve due to DPNP therapy. RESULTS: We enrolled 2,576 patients with DPNP from 307 outpatient centers (mean [standard deviation {SD}] age: 65.8 years [11.5], 51.2% female). Mean (SD) CGI-S and PGI-S at baseline were 4.4 (0.91) and 4.5 (1.05), respectively. BPI average pain score was 5.1 (2.04). The BPI interference score was 4.8 (2.18); items most impaired at baseline were walking ability 5.5 (2.60) and general activity 5.4 (2.37). The most frequently chosen BPI interference items expected to improve as a result of the pain treatment were: General activity (29.3%; 95% confidence interval [CI] 27.5-31.0%) and walking ability (24.4%; 95% CI 22.8-26.1%), followed by sleep (14.7%), enjoyment of life (13.6%), mood (8.3%), normal work (7.7%), and relations with other people (1.9%). CONCLUSIONS: The majority of patients identified "general activity" and "walking ability" as most relevant BPI interference items for which they expect improvement from DPNP treatment.

Antidepressants in the treatment for chronic low back pain: questioning the validity of meta-analyses.

OBJECTIVES: To contrast the analgesic effect of duloxetine with antidepressants reported in other published randomized clinical trials (RCTs) and review articles in patients with chronic low back pain (CLBP). METHODS: In this narrative review, the results of 13 RCTs and 5 systematic reviews examining the analgesic effect of various antidepressants in CLBP were contrasted with those of 3 placebo-controlled duloxetine RCTs. Treatment effects based on the Brief Pain Inventory (BPI) average score in the duloxetine RCTs were assessed in all completers (by study and overall) and in last-observation-carried-forward (LOCF) analyses (extracted from study reports). 30%- and 50%-reduction response rates were compared between duloxetine and placebo. RESULTS: Eleven different antidepressants were examined in 13 individual RCTs. Sample sizes, treatment durations, and analysis methods varied across studies. Reviews each included 5 to 9 of the RCTs and came to different conclusions regarding the analgesic effect of antidepressants: 2 found no evidence while 3 reported some evidence. The completer analysis showed greater improvements in BPI average scores with duloxetine vs. placebo (significant in 2 studies). Overall, the least square mean (standard error) difference between treatments was - 0.7 (0.15) (P < 0.0001). Overall response rates were significantly larger with duloxetine than with placebo. CONCLUSIONS: Due to the diversity of previous studies and the pooling methods used, the conclusions regarding the analgesic effect of antidepressants in CLBP drawn from systematic reviews must be interpreted with caution. Appropriately designed and powered studies similar to recently published duloxetine studies are recommended to demonstrate the analgesic effect of antidepressants.

Early switch strategy in patients with major depressive disorder: a double-blind, randomized study.

OBJECTIVE: Antidepressant switch is a commonly used strategy in the absence of an adequate response, but optimum timing is not well established. We compared the efficacy of an early and a conventional antidepressant switch strategy in patients with major depressive disorder. METHODS: Patients with no or minimal improvement (<30% reduction in baseline 17-item Hamilton Depression Rating Scale [HAMD17] score) after 4 weeks on escitalopram 10 mg/d were randomized to either early switch strategy with duloxetine 60 to 120 mg/d for 12 weeks (arm A) or conventional switch strategy (arm B): 4 further weeks on escitalopram 10 to 20 mg/d; then, in case of nonresponse (response, ≥ 50% reduction in HAMD17), switch to duloxetine 60 to 120 mg/d for 8 weeks, or continued escitalopram in responders. Co-primary end points were time to confirmed response and remission (HAMD17, ≤ 7). Strategies were compared using Kaplan-Meier, logistic regression, and repeated-measures analyses. RESULTS: Sixty-seven percent (566 of 840) of patients showed no or minimal improvement and were randomized to arm A (282 patients) or arm B (284 patients). No between-strategy differences in time to confirmed response (25% Kaplan-Meier estimates, 3.9 vs 4.0 weeks, P = 0.213) or remission (6.0 vs 7.9 weeks, P = 0.075) were found. Rates of confirmed responders were similar (64.9% vs 64.1%); however, more patients randomized to early switch achieved confirmed remission (43.3% vs 35.6%; P = 0.048). CONCLUSIONS: Although no differences in the primary end points were found, a higher remission rate was seen with the early switch strategy. Our findings suggest that further investigations to reevaluate the conventional approach to antidepressant switch strategy would be worthwhile.

Does atomoxetine improve executive function, inhibitory control, and hyperactivity? Results from a placebo-controlled trial using quantitative measurement technology.

The primary objective of this study was to evaluate the efficacy of atomoxetine (ATX) on attention-deficit/hyperactivity disorder (ADHD)-related symptoms assessed as standard variables of a computer-based continuous performance test (cb-CPT) combined with a motion-tracking (MT) device. This was a 2-arm, 8-week, randomized, double-blind, placebo-controlled study in patients with ADHD (6-12 years). Therapy with ATX started with 0.5 mg/kg per day for 1 week, followed by 7 weeks on the target dosage of 1.2 mg/kg per day. Primary outcomes were cb-CPT/MT standard scores after 8 weeks using mixed models for repeated measurements. In addition, investigator-rated ADHD Rating Scale (ADHD-RS), Weekly Ratings of Evening and Morning Behavior (WREMB), and Clinical Global Impression - Severity-ADHD (CGI-S-ADHD) scores were assessed. Of 128 patients randomized, 125 were evaluated (ATX/placebo: 63/62). Baseline characteristics were comparable in both groups (overall, 80.2% boys; mean [SD] age, 9.0 [1.79] years; comorbid Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnosis, 40.0% oppositional defiant disorder/conduct disorder; prior stimulant treatment, 24.8%; ADHD-RS total score, 36.99 [11.56]). At week 8, all cb-CPT/MT q-scores were significantly reduced versus placebo (all P < 0.001) with effect sizes (ESs) of reaction time (RT) variation (ES = 0.71), mean RT (ES = 0.41), number of microevents (ES = 1.00), commission error rate (ES = 0.50), distance of movement (ES = 0.90), area of movement (ES = 1.08), omission error rate (ES = 0.70), time active (ES = 0.69), motion simplicity (ES = 0.38), and normalized variance of RT (ES = 0.50). Secondary end points also improved significantly in favor of ATX: ADHD-RS (total score ES = 1.30, P < 0.001; hyperactivity/impulsivity subscore ES = 1.37, P < 0.001; inattention subscore ES = 1.07, P < 0.001), WREMB (total score ES = 1.00, P < 0.001; morning subscore ES = 0.59, P = 0.002; evening subscore ES = 1.02, P < 0.001), CGI-S-ADHD (ES = 1.11, P < 0.001). The results of this study show that ATX for 8 weeks significantly reduced ADHD-related symptoms as measured by the cb-CPT/MT.

Differential 3-year effects of first- versus second-generation antipsychotics on subjective well-being in schizophrenia using marginal structural models.

OBJECTIVE: This study examined the differential effects of first- (FGAs) versus second-generation antipsychotics (SGAs) on subjective well-being in patients with schizophrenia. METHOD: Data were collected in an observational 3-year follow-up study of 2224 patients with schizophrenia. Subjective well-being was assessed with the Subjective Well-being under Neuroleptic Treatment Scale (SWN-K). Differential effects of FGAs versus SGAs were analyzed using marginal structural models in those patients taking antipsychotic monotherapy. RESULTS: The marginal structural model, which analyzed the differential effect on the SWN-K total score, revealed that patients on SGAs had significantly higher SWN-K total scores, starting at 6 months (3.02 points; P = 0.0061, d = 0.20) and remaining significant thereafter (end point: 5.35 points; P = 0.0074, d = 0.36). CONCLUSIONS: Results of this large observational study are consistent with a small but clinically relevant superiority of SGAs over FGAs in subjective well-being extending previous positive findings of differential effects on quality of life.

Effect of atomoxetine on quality of life and family burden: results from a randomized, placebo-controlled, double-blind study in children and adolescents with ADHD and comorbid oppositional defiant or conduct disorder.

PURPOSE: To evaluate the effect of atomoxetine on quality of life (QoL) and family burden in children and adolescents with attention deficit/hyperactivity disorder (ADHD) and comorbid oppositional defiant (ODD) or conduct disorder (CD). METHODS: This secondary analysis was based on a randomized, double-blind, 9-week study of atomoxetine (target dose 1.2 mg/kg body weight) versus placebo. The study included 180 patients (atomoxetine 121, placebo 59), aged 6-17 years. QoL was measured using the KINDL-R questionnaire. The total score encompasses six dimensions (or subscales) measuring QoL in terms of "physical well-being", "emotional well-being", "self-esteem", "friends", "family", and "school". Family burden of illness was measured using the FaBel questionnaire. RESULTS: With atomoxetine, the KINDL-R total score improved significantly (P = 0.021) more than with placebo. This improvement also applied to the subscales except for "physical well-being" (opposite effect) and "school" (no effect). No significant treatment group differences were seen on the FaBel questionnaire. No differences were found between the fast and slow titration groups in terms of ADHD, ODD, and disruptive behavior severity. Furthermore, no such differences were observed for QoL and family burden. CONCLUSIONS: This study suggests positive effects of atomoxetine on quality of life, as measured by the KINDL-R scores on emotional well-being, self-esteem, friends and family, in children and adolescents with ADHD and comorbid ODD/CD. No significant treatment effects were seen on family burden, as measured by FaBel total score.

Quality of life and attention-deficit/hyperactivity disorder core symptoms: a pooled analysis of 5 non-US atomoxetine clinical trials.

The objective of this pooled analysis was to correlate parameters related to quality of life with attention-deficit/hyperactivity disorder (ADHD) core symptoms analyzing data of 5 atomoxetine clinical trials in children and adolescents with ADHD. Data from 5 clinical trials (4 from Europe and 1 from Canada) with similar inclusion/exclusion criteria and similar duration (8-12 weeks' follow-up) were included. All studies used the Child Health and Illness Profile, Child Edition (CHIP-CE), parent rating form at baseline and end point. Correlation coefficients and effect sizes to ADHD-Rating Scale (ADHD-RS) scores were calculated. A total of 794 patients aged 6 to 15 years (mean, 9.7 years), with mean (SD) baseline Clinical Global Impression of Severity of 4.8 (0.89) and ADHD-RS of 41.8 (8.04), were included. Baseline total CHIP-CE mean t score (standard, 50 [10]) was 28.9 (11.76), and the strongest impairments were seen in risk avoidance (30.2 [14.62]) and achievement (30.5 [10.4]) domains. At baseline, CHIP-CE versus ADHD-RS correlation was low (total, -0.345) except for the risk avoidance domain (total, -0.517). For changes from baseline to end point, a low correlation between the scales was found (total, -0.364; placebo-controlled studies only, n = 372). Quality of life impairment in ADHD was found in CHIP-CE total score and several domains. Correlations between CHIP-CE and ADHD-RS at baseline, end point, and for change from baseline to end point were low to moderate. These findings suggest that measuring quality of life adds clinically relevant insight beyond core symptom evaluation in children and adolescents with ADHD.

Modeling Heterogeneity in Patients' Preferences for Psoriasis Treatments in a Multicountry Study: A Comparison Between Random-Parameters Logit and Latent Class Approaches.

BACKGROUND: Either a random-parameters logit (RPL) or latent class (LC) model can be used to model or explain preference heterogeneity in discrete-choice experiment (DCE) data. The former assumes continuous distribution of preferences across the sample, while the latter assumes a discrete distribution. This study compared RPL and LC models to explore preference heterogeneity when analyzing patient preferences for psoriasis treatments. METHODS: Using DCE data collected from respondents with moderate-to-severe plaque psoriasis, we calculated and compared preference weights derived from RPL and LC models. We then compared how RPL and LC explain preference heterogeneity by exploring differences across subgroups defined by observed characteristics (i.e., country, age, gender, marital status, and psoriasis severity). RESULTS: While RPL and LC models resulted in the same mean preference weights, different preference-heterogeneity patterns emerged from the two approaches. In both models, country of residence and self-reported disease severity could be linked to systematic differences in preferences. The RPL also identified gender and marital status, but not age, as sources of heterogeneity; the LC membership probability model indicated that age was a significant factor, but not gender or marital status. CONCLUSIONS: Using data from a psoriasis patient survey to compare two widely used methods for exploring heterogeneity identified differences in results between stated-preferences: subgroup analysis in the RPL model and inclusion of subgroup characteristics in the class membership probability function of the LC model. Researchers should model data using the most adaptable approach to address the initial study question.

Multilevel network meta-regression for population-adjusted treatment comparisons.

Standard network meta-analysis (NMA) and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any effect modifiers are balanced across populations. Population adjustment methods relax this assumption using individual patient data from one or more studies. However, current matching-adjusted indirect comparison and simulated treatment comparison methods are limited to pairwise indirect comparisons and cannot predict into a specified target population. Existing meta-regression approaches incur aggregation bias. We propose a new method extending the standard NMA framework. An individual level regression model is defined, and aggregate data are fitted by integrating over the covariate distribution to form the likelihood. Motivated by the complexity of the closed form integration, we propose a general numerical approach using quasi-Monte-Carlo integration. Covariate correlation structures are accounted for by using copulas. Crucially for decision making, comparisons may be provided in any target population with a given covariate distribution. We illustrate the method with a network of plaque psoriasis treatments. Estimated population-average treatment effects are similar across study populations, as differences in the distributions of effect modifiers are small. A better fit is achieved than a random effects NMA, uncertainty is substantially reduced by explaining within- and between-study variation, and estimates are more interpretable.

Effects of clozapine and olanzapine on cytokine systems are closely linked to weight gain and drug-induced fever.

The second generation antipsychotics clozapine and olanzapine are known to cause weight gain. However, only clozapine is associated with drug-induced fever. Cytokines have been linked to the induction of both weight gain and drug-induced fever. We investigated these potential side effects of clozapine and olanzapine and studied their differential effects on cytokine secretion. Thirty patients suffering from schizophrenia, schizophreniform disorder or schizoaffective disorder were treated with either clozapine (mean modal dose: 266.7+/-77.9mg) or olanzapine (21.2+/-2.5mg) in a randomized, double-blind, 6-week study. Body mass index (BMI), tympanic temperature, and plasma levels of leptin and cytokines (tumor necrosis factor-alpha (TNF-alpha), soluble TNF receptor 1 and 2 (sTNFR-1/2), soluble interleukin-2 receptors (sIL-2R), interleukin-6) were determined weekly. BMI, leptin and cytokines significantly increased over time, except interleukin-6 and sTNFR-1 in the olanzapine group. All cytokines numerically increased compared to baseline already during the first week of treatment in both groups. Leptin, TNF-alpha, sTNFR-1, sTNFR-2 and sIL-2R levels correlated with the BMI. Five patients who received clozapine (33%) developed drug-induced fever (>/=38 degrees C). In these, interleukin-6 peak levels were significantly (p<0.01) higher than in those patients treated with clozapine who did not develop fever. In conclusion, increase of BMI appears to be related to clozapine's and olanzapine's similar effects on cytokine systems, whilst drug-induced fever appears to be related to clozapine's differential effects on interleukin-6.

Long-term patterns of subjective wellbeing in schizophrenia: cluster, predictors of cluster affiliation, and their relation to recovery criteria in 2842 patients followed over 3 years.

OBJECTIVE: To study the longitudinal patterns of subjective wellbeing in schizophrenia using cluster analysis and their relation to recovery criteria, further to examine predictors for cluster affiliation, and to evaluate the sensitivity and specificity of baseline subjective wellbeing cut-offs for cluster affiliation. METHODS: Data was collected in an observational 36-month follow-up study of 2842 patients with schizophrenia in Germany. Subjective wellbeing was assessed using the SWN-K scale. Cluster analyses were applied based on Ward's procedure. Predictors were analyzed using logistic regression models. Optimal SWN-K total score cut-off points for cluster affiliation were analyzed using Cohen's kappa. RESULTS: 4 distinct clusters were identified: a stable low (33%), a stable moderate (31%), a stable high (16%), and a cluster with distinct initial improvement and then stable high subjective wellbeing (20%). Highly concordant patterns were also observed for symptoms, social functioning, and quality of life. Sensitivity and specificity of SWN-K total score cut-offs at baseline were 82.8% and 63.8% for or=80 points for the stable high cluster. Affiliation to the stable low cluster was related to a 0.6% chance of being in recovery at 3-year endpoint. CONCLUSIONS: Long-term patterns of subjective wellbeing are stable and highly concordant with course of symptoms, functioning level, and quality of life. Baseline subjective wellbeing cut-off points were found to be sufficient predictors of outcome, which, particularly in case of impaired subjective wellbeing and low baseline functioning level, make early treatment adaptations mandatory.

Atomoxetine improves patient and family coping in attention deficit/hyperactivity disorder: a randomized, double-blind, placebo-controlled study in Swedish children and adolescents.

This 10-week study assessed the efficacy of atomoxetine in combination with psychoeducation compared to placebo and psychoeducation in the improvement of Quality of Life in Swedish stimulant-naive children and adolescents with attention deficit/hyperactivity disorder. A total of 99 patients were treated with atomoxetine (49 patients) or placebo (50 patients) for 10 weeks and assessed regarding broader areas of functioning using the Quality of Life measures Child Health and Illness Profile-Child Edition (CHIP-CE), Family Strain Index [FSI; equivalent to the Family Burden of Illness Module used in the study], Appraisal of Stress in Child-Rearing (ASCR), Five to fifteen (FTF), "I think I am" ("Jag tycker jag är"), and Children's Depression Rating Scale-Revised (CDRS-R) before and after the active treatment phase. Simultaneously, the patients' parents participated in a 4-session psychoeducation program. A statistically significant difference in favor of atomoxetine was seen in the improvement from baseline to study endpoint for the CHIP-CE domains "Achievement" and "Risk avoidance", for the FSI total score, for the ASCR section (I) domain "Child as a burden", for all FTF domains except for "Language and Speech", and for the CDRS-R total score. No difference between treatment groups was observed in the patient-assessed evaluation of self-esteem using the "I think I am" scale. Atomoxetine combined with psychoeducation had a positive effect on various everyday coping abilities of the patients as well as their families during 10 weeks of treatment, whereas the patients' self-image and the parents' image of the climate in the family were not significantly improved.

Validation of a Clinical Global Impression Scale for Aggression (CGI-A) in a sample of 558 psychiatric patients.

OBJECTIVE: Clinical management of aggression depends on the availability of easily administrable measurements allowing reliable evaluation. The present study's aim is to validate a Clinical Global Impression-Severity of Aggression scale (CGI-A). METHOD: 558 inpatients with psychiatric disorders and an agitated-aggressive syndrome at baseline were continuously assessed over 5 days using CGI-A and the Positive and Negative Syndrome Scale-Excited Component (PANSS-EC). Equipercentile linking, correlation analyses and linear regression were applied. RESULTS: Relationship between CGI-A and PANSS-EC total score was found to be linear. On a 5-level CGI-A scale, values of 1 to 5 points were found to correspond to PANSS-EC scores of 12.2, 16.7, 21.3, 25.8, and 30.4, respectively (average increase: 4.6). All findings remained stable when only data from patients with schizophrenia spectrum disorders were analyzed. CONCLUSIONS: The CGI-A is proposed as a quickly administrable scale for the assessment of patients' aggressiveness.

Patterns of physician and patient rated quality of life during antipsychotic treatment in outpatients with schizophrenia.

Quality of life (QoL) in patients with schizophrenia has been assessed both from physician and patient perspectives, but little is known about agreement between these perspectives and predictors of agreement. The aim of this study was to analyze a large sample of patients with schizophrenia to discover patterns of physician and patient-rated QoL in patients with schizophrenia and identify predictors for these patterns. This study (EASE) was designed to investigate the QoL and subjective well-being in out-patients with schizophrenia during antipsychotic treatment in a naturalistic setting. Assessments were carried out at baseline and at 3, 6, 9 and 12 months, using the quality of life scale (QLS) and the subjective well-being on neuroleptics scale (SWN-K). A hierarchical cluster analysis was used to define groups of patients based on the SWN-K and QLS total scores at all visits. 1174 patients were included in the cluster analyses that were based on SWN-K and QLS total scores over time. Four distinct clusters were identified: patients with: (1) continuously high QoL (23.2%), (2) continuously moderate QoL (45.8%), (3) continuously low QoL (11.2%), and (4) improving QoL (19.9%). Clusters 1-3 were stable in terms of QoL, whilst cluster 4 changed towards improvement. Various predictors for the four clusters were identified. In the cluster with improving QoL, the absence of treatment with an oral conventional antipsychotic pre-study and no medication change due to lack of efficacy at baseline were predictors for improvement. In the cluster with continuously high QoL, no medication change due to lack of efficacy and lowest CGI-S scores at baseline were predictors. Oral conventional antipsychotic treatment pre-study was predictive for the cluster with continuously moderate QoL. In the cluster with continuously low QoL, medication change due to lack of efficacy and highest CGI-S scores were predictors. These findings suggest that various factors may predict whether a patient with schizophrenia experiences a continuously high QoL, a continuously moderate QoL, a continuously low QoL, or improving QoL whilst on antipsychotic treatment.