Inflammasome activation in obesity-related inflammatory diseases and autoimmunity

How should we design future mechanistic and/or efficacy clinical trials?

The emergence of new molecular targets, together with the development of new approaches to neuropsychiatric diseases, involving psychedelics as well as gene and cell therapies, are creating the need to improve the efficiency of mechanistic and/or efficacy clinical trials. This review article will discuss a number of issues that have hampered our ability to detect therapeutic signals, from excessive placebo/sham response rates to the imprecision of diagnostic and outcome assessments. In addition to reviewing the limitations of current efficacy and mechanistic neuropsychiatric clinical trials, this review presents some of the methodological approaches that may improve the overall performance of our neuropsychiatric trials, including the adoption of novel study designs such as the sequential parallel comparison design and independent confirmation of the appropriateness of subjects' enrollment. In addition, this review will discuss several designs that make mechanistic clinical trials more precise.

Lack of Efficacy of Suvorexant in People with Insomnia and Poorly Controlled Type 2 Diabetes

Objective/Background

Sleep disturbance is a common and underappreciated feature of diabetes and sleep may contribute to glycemic control in people with type 2 diabetes (T2D). We conducted a 3-month trial to examine the efficacy of suvorexant in improving sleep and health outcomes in people with suboptimally controlled T2D and insomnia.

Participants/Methods

This parallel, double-blind, randomized placebo-controlled trial was conducted using the sequential parallel comparison design (SPCD). Sixty-nine people with poorly controlled T2D (HbA1c ≥ 6.5) were randomized to placebo and/or suvorexant (10-20 mg). The primary outcome was subjective total sleep time (sTST), and secondary outcomes were Insomnia Severity Index (ISI) score and wake time after sleep onset (WASO). Exploratory outcomes included sleep efficiency, hemoglobin A1c (HbA1c), and C-reactive protein (CRP). Exploratory analyses were conducted on relationships between sleep and diabetes outcomes.

Results

There were no significant improvements in sTST (p = 0.27), ISI (p = 0.86), or WASO (p = 0.94) among participants taking suvorexant compared to placebo. There were also no significant changes in any of the exploratory endpoints. Improvements in sleep were associated with improvements in both objective (ie, HbA1c) and subjective (ie, Diabetes Distress Scale) measures of diabetes, as well as reductions in depressive symptoms, independent of treatment assignment.

Conclusion

The study did not find evidence that suvorexant is efficacious for insomnia in people with poorly controlled T2D. The associations of improved sleep with improvements in both diabetes-related metrics and depressive symptoms across groups highlight the importance of identifying and treating sleeping difficulties in this population.

CT Registration #

Nct03818581.

Sexual orientation differences among men in a randomized clinical trial of extended-release naltrexone and bupropion for methamphetamine use disorder

BACKGROUND

Methamphetamine use disorder (MethUD) disproportionately affects men who have sex exclusively with men or with men and women (collectively MSM/W), compared to men who have sex with women (MSW). This study is the first MethUD medication trial to compare treatment effect for these groups, hypothesizing that extended-release injectable naltrexone 380mg every 3 weeks plus oral extended-release bupropion 450mg daily would be less effective for MSM/W than MSW.

METHODS

Data come from men (N = 246) in a multi-site, double-blind, randomized, placebo-controlled trial with sequential parallel comparison design. In Stage 1 (6-weeks), participants were randomized to active treatment or placebo. In Stage 2 (6-weeks), Stage 1 placebo non-responders were rerandomized. Treatment response was ≥3 methamphetamine-negative urine samples, out of four obtained at the end of Stages 1 and 2. Treatment effect was the active-versus-placebo between-group difference in the weighted average Stages 1 and 2 responses.

RESULTS

MSM/W (n = 151) were more likely than MSW (n = 95) to be Hispanic, college-educated, and living with HIV. Adjusting for demographics, among MSM/W, response rates were 13.95 % (active treatment) and 2.78 % (placebo) in Stage 1; 23.26 % (active treatment) and 4.26 % (placebo) in Stage 2. Among MSW, response rates were 7.69 % (active treatment) and 5.80 % (placebo) in Stage 1; 3.57 % (active treatment) and 0 % (placebo) in Stage 2. Treatment effect was significantly larger for MSM/W (h = 0.1479) than MSW (h = 0.0227) (p = 0.04).

CONCLUSIONS

Findings suggest efficacy of extended-release naltrexone plus bupropion for MSM/W, a population heavily burdened by MethUD. While a secondary outcome, this intriguing finding merits testing in prospective trials.

A new method for analyzing clinical trials in depression based on individual propensity to respond to placebo estimated using artificial intelligence

One of the major reasons for trial failures in major depressive disorders (MDD) is the presence of unpredictable levels of placebo response as the individual baseline propensity to respond to placebo is not adequately controlled by the current randomization and statistical methodologies. The individual propensity to respond to any treatment or intervention assessed at baseline was considered as a major non-specific prognostic and confounding effect. The objective of this paper was to apply the propensity score methodology to control for potential imbalance at baseline in the propensity to respond to placebo in clinical trials in MDD. Individual propensity was estimated using artificial intelligence (AI) applied to observations collected in two pre-randomization occasions. Cases study are presented using data from two randomized, placebo-controlled trials to evaluate the efficacy of paroxetine in MDD. AI models were used to estimate the individual propensity probability to show a treatment non-specific placebo effect. The inverse of the estimated probability was used as weight in the mixed-effects analysis to assess treatment effect. The comparison of the results obtained with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect size significantly larger than the conventional analysis.

Artificial intelligence approach for the analysis of placebo-controlled clinical trials in major depressive disorders accounting for individual propensity to respond to placebo

Treatment effect in clinical trials for major depressive disorders (RCT) can be viewed as the resultant of treatment specific and non-specific effects. Baseline individual propensity to respond non-specifically to any treatment or intervention can be considered as a major non-specific confounding effect. The greater is the baseline propensity, the lower will be the chance to detect any treatment-specific effect. The statistical methodologies currently applied for analyzing RCTs doesn't account for potential unbalance in the allocation of subjects to treatment arms due to heterogenous distributions of propensity. Hence, the groups to be compared may be imbalanced, and thus incomparable. Propensity weighting methodology was used to reduce baseline imbalances between arms. A randomized, double-blind, placebo controlled, three arms, parallel group, 8-week, fixed-dose study to evaluate efficacy of paroxetine CR 12.5 and 25 mg/day is presented as a cases study. An artificial intelligence model was developed to predict placebo response at week 8 in subjects assigned to placebo arm using changes from screening to baseline of individual Hamilton Depression Rating Scale items. This model was used to predict the probability to respond to placebo in each subject. The inverse of the probability was used as weight in the mixed-effects model applied to assess treatment effect. The analysis with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect-size about twice larger than the non-weighted analysis. Propensity weighting provides an unbiased strategy to account for heterogeneous and uncontrolled placebo effect making patients' data comparable across treatment arms.

Usefulness of the placebo lead-in design for clinical trials with binary outcomes

BACKGROUND

In placebo-controlled clinical trials to develop new drugs for the treatment of psychiatric or neurological disorders, a high and sometimes greater-than-expected placebo response makes it difficult to show the superiority of an investigational drug over a corresponding placebo. To avoid such difficulty, a placebo lead-in design has been presented, but its usefulness has been open to discussion. Although the statistical properties of the placebo lead-in design are investigated in the context of continuous outcomes, whether these properties can be generalized for binary or ordinal cases remains unclear.

METHODS

We investigate whether the placebo lead-in design is useful in clinical trials with binary outcomes through mathematical formulae and a numerical investigation. Specifically, we compare the proportion of placebo responders, the drug-placebo difference, and the effect size between two populations: one enriched for placebo nonresponders and the other comprising the all-comers.

RESULTS

Under positive correlation of the data between the lead-in stage and the randomized stage for both treatment groups, we mathematically show that the proportion of responders in the population enriched for placebo nonresponders is less than that in the all-comers population, and whether the placebo lead-in design increases the drug-placebo difference depends on the variances of outcomes in both treatment groups as well as the correlations of the outcomes between two stages. Further, through a numerical investigation, we show that whether the placebo lead-in design increases the effect size strongly depends on the magnitude of the correlations and their difference.

CONCLUSION

If the correlation of the placebo-placebo group is much higher than that of the placebo-drug group, the placebo lead-in design is advantageous in most cases but has an impact on an estimand in placebo nonresponders. Therefore, we do not recommend using the placebo lead-in design for clinical trials with binary outcomes.

A generalized weighted combination test of treatment effect for clinical trials with a sequential parallel comparison design and binary endpoint

To address the issue of a large placebo effect in certain therapeutic areas, rather than the application of the traditional gold standard parallel group placebo-controlled design, different versions of the sequential parallel comparison design have been advocated. In general, the design consists of two consecutive stages and three treatment groups. Stage 1 placebo nonresponders potentially form a prespecified patient subgroup for formal between-treatment comparison at the final analysis. In this research, a version of the design is considered for a binary endpoint. To fully utilize all available data, a generalized weighted combination test is proposed in case placebo has a relatively small effect for some of the study endpoints. The weighted combination of the test based on stage 1 data and the test based on stage 2 data of stage 1 placebo nonresponders suggested in the literature uses only a part of the study data and is a special case of this generalized weighted combination test. A multiple imputation approach is outlined for handling missing not at random data. Simulation is conducted to evaluate the performances of the methods and a data example is employed to illustrate the applications of the methods.

Challenges and potential strategies utilizing external data for efficacy evaluation in small-sized clinical trials

In clinical trials for diseases with very small patient populations, trial investigators may encounter recruitment difficulties. It can be challenging to conduct clinical trials with enough power to detect a treatment effect, and randomization may not be feasible due to timeline, budget, and ethical concerns. To bring breakthrough therapies to the market quickly, it is important to come up with efficient approaches to utilizing individual patient data through improved study design and sound statistical methods. Emerging topics in this area include the use of Bayesian approaches to flexibly incorporate prior information into the current clinical trials, the use of historical controls to efficiently conduct trials that will reduce the number of subjects recruited and ease ethical considerations, and the use of innovative study designs, such as a platform design, to improve the efficiency and speed of the medical therapy development progress. In this paper, we describe three scenarios which highlight some of the challenges encountered in small-sized clinical trial development and provide potential statistical approaches to overcome the aforementioned challenges.

Practical Research Ethics in Psychiatric Clinical Trials: A Guide for Investigators

The conduct of clinical psychiatric research is critical to advance the science and efficacy of treatment while also safeguarding the interests of participants. This article emerges from the authors' experience, providing practical guidance to colleagues seeking input on how to design and implement clinical research protocols in accordance with key ethical considerations. Thus, the intent of this article is to provide (1) an overview of common ethical considerations when conducting psychiatric clinical research along with (2) practical advice for preparing Institutional Review Board applications and associated materials in the ethical conduct of psychiatric clinical research.

Bupropion and Naltrexone in Methamphetamine Use Disorder

BACKGROUND

The use of naltrexone plus bupropion to treat methamphetamine use disorder has not been well studied.

METHODS

We conducted this multisite, double-blind, two-stage, placebo-controlled trial with the use of a sequential parallel comparison design to evaluate the efficacy and safety of extended-release injectable naltrexone (380 mg every 3 weeks) plus oral extended-release bupropion (450 mg per day) in adults with moderate or severe methamphetamine use disorder. In the first stage of the trial, participants were randomly assigned in a 0.26:0.74 ratio to receive naltrexone-bupropion or matching injectable and oral placebo for 6 weeks. Those in the placebo group who did not have a response in stage 1 underwent rerandomization in stage 2 and were assigned in a 1:1 ratio to receive naltrexone-bupropion or placebo for an additional 6 weeks. Urine samples were obtained from participants twice weekly. The primary outcome was a response, defined as at least three methamphetamine-negative urine samples out of four samples obtained at the end of stage 1 or stage 2, and the weighted average of the responses in the two stages is reported. The treatment effect was defined as the between-group difference in the overall weighted responses.

RESULTS

A total of 403 participants were enrolled in stage 1, and 225 in stage 2. In the first stage, 18 of 109 participants (16.5%) in the naltrexone-bupropion group and 10 of 294 (3.4%) in the placebo group had a response. In the second stage, 13 of 114 (11.4%) in the naltrexone-bupropion group and 2 of 111 (1.8%) in the placebo group had a response. The weighted average response across the two stages was 13.6% with naltrexone-bupropion and 2.5% with placebo, for an overall treatment effect of 11.1 percentage points (Wald z-test statistic, 4.53; P<0.001). Adverse events with naltrexone-bupropion included gastrointestinal disorders, tremor, malaise, hyperhidrosis, and anorexia. Serious adverse events occurred in 8 of 223 participants (3.6%) who received naltrexone-bupropion during the trial.

CONCLUSIONS

Among adults with methamphetamine use disorder, the response over a period of 12 weeks among participants who received extended-release injectable naltrexone plus oral extended-release bupropion was low but was higher than that among participants who received placebo. (Funded by the National Institute on Drug Abuse and others; ADAPT-2 ClinicalTrials.gov number, NCT03078075.).

Pharmacological Treatment of Mood Disorders and Comorbid Addictions: A Systematic Review and Meta-Analysis: Traitement Pharmacologique des Troubles de L'humeur et des Dépendances Comorbides: Une Revue Systématique et une Méta-Analyse

OBJECTIVE

Addiction comorbidity is an important clinical challenge in mood disorders, but the best way of pharmacologically treating people with mood disorders and addictions remains unclear. The aim of this study was to assess the efficacy of pharmacological treatments for mood and addiction symptoms in people with mood disorders and addiction comorbidity.

METHODS

A systematic search of placebo-controlled randomized controlled trials investigating the effects of pharmacological treatments in people with bipolar disorder (BD) or major depressive disorder (MDD), and comorbid addictions was performed. Treatment-related effects on mood and addiction measures were assessed in a meta-analysis, which also estimated risks of participant dropout and adverse effects.

RESULTS

A total of 32 studies met systematic review inclusion criteria. Pharmacological therapy was more effective than placebo for improving manic symptoms (standardized mean difference [SMD] = -0.15; 95% confidence interval [95% CI], -0.29 to -0.02; P = 0.03) but not BD depressive symptoms (SMD = -0.09; 95% CI, -0.22 to 0.03; P = 0.15). Quetiapine significantly improved manic symptoms (SMD = -0.23; 95% CI, -0.39 to -0.06; P = 0.008) but not BD depressive symptoms (SMD = -0.07; 95% CI, -0.23 to 0.10; P = 0.42). Pharmacological therapy was more effective than placebo for improving depressive symptoms in MDD (SMD = -0.16; 95% CI, -0.30 to -0.03; P = 0.02). Imipramine improved MDD depressive symptoms (SMD = -0.58; 95% CI, -1.03 to -0.13; P = 0.01) but Selective serotonin reuptake Inhibitors (SSRI)-based treatments had no effect (SMD = -0.06; 95% CI, -0.30 to 0.17; P = 0.60). Pharmacological treatment improved the odds of alcohol abstinence in MDD but had no effects on opiate abstinence.

CONCLUSIONS

Pharmacological treatments were significantly better than placebo in improving manic symptoms, MDD depressive symptoms, and alcohol abstinence but were not better for bipolar depression symptoms. Importantly, quetiapine was not more effective than placebo in improving bipolar depression symptoms nor were SSRI's for the treatment of MDD depression. Our findings highlight the need for further high-quality clinical trials of treatments for mood disorders and comorbid addictions.

Complement activation in obesity, insulin resistance, and type 2 diabetes mellitus

Amplified inflammatory reaction has been observed to be involved in cardiometabolic diseases such as obesity, insulin resistance, diabetes, dyslipidemia, and atherosclerosis. The complement system was originally viewed as a supportive first line of defense against microbial invaders, and research over the past decade has come to appreciate that the functions of the complement system extend beyond the defense and elimination of microbes, involving in such diverse processes as clearance of the immune complexes, complementing T and B cell immune functions, tissue regeneration, and metabolism. The focus of this review is to summarize the role of the activation of complement system and the initiation and progression of metabolic disorders including obesity, insulin resistance and diabetes mellitus. In addition, we briefly describe the interaction of the activation of the complement system with diabetic complications such as diabetic retinopathy, nephropathy and neuropathy, highlighting that targeting complement system therapeutics could be one of possible routes to slow down those aforementioned diabetic complications.

Enrichment designs using placebo nonresponders

Enrichment designs that select placebo nonresponders have gained much attention during the last years in areas with high placebo response rates, eg, in depression. Proposals were made that re-randomize patients who did not respond to placebo during a first study phase as the sequential parallel design (SPD). This design uses in a second phase an enriched patient population where the treatment effect is expected to be more pronounced. This may be problematic if an effect in the overall population is claimed. Proposals were made to combine the treatment effects in the overall population from study phase 1 and the enriched population from study phase 2, alleviating but not solving the issue of a potential selection bias. This paper shows how this bias corresponding to the effect difference between the overall population and the enriched population depends on the variability of a potential subject-by-treatment interaction. Sample sizes are given, which lead to a significant result in the combining test with a given probability if actually the average effect in the overall population is zero. If, on the other hand, no subject-by-treatment interaction is given, the enrichment is shown to be inefficient. We conclude that enrichment designs using placebo nonresponders are not able to claim a positive average effect in the overall population if a subject-by-treatment interaction cannot be excluded. It cannot be used to demonstrate positive efficacy in the overall population in a pivotal phase III trial but may be used in early phases to demonstrate varying treatment effects between patients.

A phase 2, double-blind, placebo-controlled study of NSI-189 phosphate, a neurogenic compound, among outpatients with major depressive disorder

NSI-189 is a novel neurogenic compound independent of monoamine reuptake pathways. This trial evaluated oral NSI-189 as monotherapy in major depressive disorder. To improve signal detection, the sequential-parallel comparison design (SPCD) was chosen. Two hundred and twenty subjects were randomized to NSI-189 40 mg daily, 80 mg daily, or placebo for 12 weeks. The primary outcome measure was the Montogmery Asberg Depression Rating Scale (MADRS). Secondary subject-rated measures included the Symptoms of Depression Questionnaire (SDQ), the Cognitive and Physical Functioning Scale (CPFQ), the patient-rated version of the Quick Inventory of Depressive Symptomatology Scale (QIDS-SR), and subtests from the CogScreen and Cogstate cognitive tests. MADRS score reduction versus placebo did not reach significance for either dose (40 mg pooled mean difference -1.8, p = 0.22, 80 mg pooled mean difference -1.4, p = 0.34, respectively). However, the 40 mg dose showed greater overall reduction in SDQ (pooled mean difference -8.2; Cohen's d for Stages 1 and 2 = -0.11 and -0.64, p = 0.04), and CPFQ scores (pooled mean difference -1.9; Cohen's d for Stages 1 and 2 = -0.28 and -0.47, p = 0.03) versus placebo, as well as QIDS-SR scores in Stage 2 of SPCD (-2.5; Cohen's d Stages 1 and 2 = -0.03 and -0.68, p = 0.04). The 40 mg dose also showed advantages on some objective cognitive measures of the CogScreen (absolute Cohen's d ranged between 0.12 and 1.12 in favor of NSI-189, p values between 0.002 and 0.048 for those with overall significance), but not the Cogstate test. Both doses were well tolerated. These findings replicate those of phase 1b study, and warrant further exploration of the antidepressant and pro-cognitive effects of NSI-189.

Sequential parallel comparison design with two coprimary endpoints

A placebo-controlled randomized clinical trial is required to demonstrate that an experimental treatment is superior to its corresponding placebo on multiple coprimary endpoints. This is particularly true in the field of neurology. In fact, clinical trials for neurological disorders need to show the superiority of an experimental treatment over a placebo in two coprimary endpoints. Unfortunately, these trials often fail to detect a true treatment effect for the experimental treatment versus the placebo owing to an unexpectedly high placebo response rate. Sequential parallel comparison design (SPCD) can be used to address this problem. However, the SPCD has not yet been discussed in relation to clinical trials with coprimary endpoints. In this article, our aim was to develop a hypothesis-testing method and a method for calculating the corresponding sample size for the SPCD with two coprimary endpoints. In a simulation, we show that the proposed hypothesis-testing method achieves the nominal type I error rate and power and that the proposed sample size calculation method has adequate power accuracy. In addition, the usefulness of our methods is confirmed by returning to an SPCD trial with a single primary endpoint of Alzheimer disease-related agitation.

Comparison of novel methods in two-way enriched clinical trial design

Two-way enriched design (TED) is a novel approach addressing placebo response in clinical trials. It is a two-stage, randomized, placebo-controlled trial design with enrichment in placebo non-responders and treatment responders at the second stage. All data from the first stage and data from placebo non-responders and treatment responders in the second stage are used for the final analysis of the treatment effect. The existing methods for the analysis of TED data include score tests with one, two, and three degrees of freedom. All these methods are only applicable to binary outcomes. However, there is an interest in continuous outcomes in clinical trials in psychiatry. In this manuscript, we apply some novel methods, including a repeated measures model, a weighted repeated measures model with weights from propensity score, and weights from K-means clustering, to analyze TED data for both binary outcomes and continuous outcomes. The simulation study indicates that the repeated measures model performs consistently well in preserving the type I error and achieving the minimum mean standard error as well as a higher power. The performance of the weighted repeated measures model with weights from K-means clustering improves with increasing sample size. Investigators can choose from these analytic approaches under different scenarios.

Sequential parallel comparison design for "gold standard" noninferiority trials with a prespecified margin

Three-arm noninferiority trials (involving an experimental treatment, a reference treatment, and a placebo)-called the "gold standard" noninferiority trials-are conducted in patients with mental disorders whenever feasible, but often fail to show superiority of the experimental treatment and/or the reference treatment over the placebo. One possible reason is that some of the patients receiving the placebo show apparent improvement in the clinical condition. An approach to addressing this problem is the use of the sequential parallel comparison design (SPCD). Nonetheless, the SPCD has not yet been discussed in relation to gold standard noninferiority trials. In this article, our aim was to develop a hypothesis-testing method and its corresponding sample size calculation method for gold standard noninferiority trials with the SPCD. In a simulation, we show that the proposed hypothesis-testing method achieves the nominal type I error rate and power and that the proposed sample size calculation method has adequate power accuracy.

A commentary on: statistical inference problems in sequential parallel comparison designs

A Sequential Parallel Comparison Design has two stages, the first comparing drug to placebo and the second comparing drug to placebo among patients who did not respond to placebo in the first stage. The paper, Statistical Inference Problems in Sequential Parallel Comparison Designs, claims that the estimate of the treatment difference in the second stage is biased and that under certain circumstances, a suggested hypothesis test will reject the null hypothesis when it should be accepted. This rejoinder argues that the estimate in the second stage is not biased when the true target of estimation (estimand) is properly understood. Further, the null hypothesis that the authors posit is not the correct null hypothesis for clinical trials, and in the situation, they describe that the treatment should be considered to be effective.

A simple test for the treatment effect in clinical trials with a sequential parallel comparison design and negative binomial outcomes

In placebo-controlled, double-blinded, randomized clinical trials, the presence of placebo responders reduces the effect size for comparison of the active drug group with the placebo group. An attempt to resolve this problem is to use the sequential parallel comparison design (SPCD). Although there are SPCDs with dichotomous or continuous outcomes, an SPCD with negative binomial outcomes-with which investigators deal eg, in clinical trials involving multiple sclerosis, where the investigators are still concerned about the presence of placebo responders-has not yet been discussed. In this article, we propose a simple test for the treatment effect in clinical trials with an SPCD and negative binomial outcomes. Through simulations, we show that the analysis method achieves the nominal type I error rate and power, whereas the sample size calculation provides the sample size with adequate power accuracy.

Asymptotic and exact interval estimators of the common odds ratio under the sequential parallel comparison design

When studying treatments for psychiatric or mental diseases in a placebo-controlled trial, we may consider use of the sequential parallel comparison design to reduce the number of patients needed through the reduction of the high placebo response rate. Under the assumption that the odds ratio of responses is constant between phases in the sequential parallel comparison design, we derive the conditional maximum likelihood estimator for the odds ratio. On the basis of the conditional likelihood, we further derive three asymptotic interval and an exact interval estimators for the odds ratio of responses. We employ Monte Carlo simulation to evaluate the performance of these interval estimators in a variety of situations. We find that the asymptotic interval and exact interval estimators developed here can all perform well. We use the double-blind, placebo-controlled study assessing the efficacy of a low dose of aripiprazole adjunctive to antidepressant therapy for treating patients with major depressive disorder to illustrate the use of these estimators.

Exact and asymptotic tests under the sequential parallel comparison design

When one studies treatments for psychological or mental diseases in a double-blind placebo-controlled trial with a high placebo response rate, the sequential parallel comparison design (SPCD) has been proposed elsewhere to improve power. All procedures for testing equality of treatments under the SPCD have been so far derived from large sample theory. If the trial size is small, asymptotic test procedures can be theoretically invalid. Thus, the development of an exact test procedure assuring type I error rate to be less than or equal to the nominal α-level is of use and interest. Using the conditional arguments to remove nuisance parameters, we derive two exact and one asymptotic procedures for testing equality of treatments for the SPCD. On the basis of Monte Carlo simulation, we find that all three test procedures can control type I error rate well in a variety of situations. We use the data taken from a double-blind placebo-controlled SPCD trial to assess the efficacy of a low dose (2 mg/day) of aripiprazole adjunctive to antidepressant therapy in the treatment of patients with major depressive disorder with a history of inadequate response to prior antidepressant therapy to illustrate the use of these test procedures.

Efficacy and Safety of Intranasal Esketamine Adjunctive to Oral Antidepressant Therapy in Treatment-Resistant Depression: A Randomized Clinical Trial

Importance

Approximately one-third of patients with major depressive disorder (MDD) do not respond to available antidepressants.

Objective

To assess the efficacy, safety, and dose-response of intranasal esketamine hydrochloride in patients with treatment-resistant depression (TRD).

Design, Setting, and Participants

This phase 2, double-blind, doubly randomized, delayed-start, placebo-controlled study was conducted in multiple outpatient referral centers from January 28, 2014, to September 25, 2015. The study consisted of 4 phases: (1) screening, (2) double-blind treatment (days 1-15), composed of two 1-week periods, (3) optional open-label treatment (days 15-74), and (4) posttreatment follow-up (8 weeks). One hundred twenty-six adults with a DSM-IV-TR diagnosis of MDD and history of inadequate response to 2 or more antidepressants (ie, TRD) were screened, 67 were randomized, and 60 completed both double-blind periods. Intent-to-treat analysis was used in evaluation of the findings.

Interventions

In period 1, participants were randomized (3:1:1:1) to placebo (n = 33), esketamine 28 mg (n = 11), 56 mg (n = 11), or 84 mg (n = 12) twice weekly. In period 2, 28 placebo-treated participants with moderate-to-severe symptoms were rerandomized (1:1:1:1) to 1 of the 4 treatment arms; those with mild symptoms continued receiving placebo. Participants continued their existing antidepressant treatment during the study. During the open-label phase, dosing frequency was reduced from twice weekly to weekly, and then to every 2 weeks.

Main Outcomes and Measures

The primary efficacy end point was change from baseline to day 8 (each period) in the Montgomery-Åsberg Depression Rating Scale (MADRS) total score.

Results

Sixty-seven participants (38 women, mean [SD] age, 44.7 [10.0] years) were included in the efficacy and safety analyses. Change (least squares mean [SE] difference vs placebo) in MADRS total score (both periods combined) in all 3 esketamine groups was superior to placebo (esketamine 28 mg: -4.2 [2.09], P = .02; 56 mg: -6.3 [2.07], P = .001; 84 mg: -9.0 [2.13], P < .001), with a significant ascending dose-response relationship (P < .001). Improvement in depressive symptoms appeared to be sustained (-7.2 [1.84]) despite reduced dosing frequency in the open-label phase. Three of 56 (5%) esketamine-treated participants during the double-blind phase vs none receiving placebo and 1 of 57 participants (2%) during the open-label phase had adverse events that led to study discontinuation (1 event each of syncope, headache, dissociative syndrome, and ectopic pregnancy).

Conclusions and Relevance

In this first clinical study to date of intranasal esketamine for TRD, antidepressant effect was rapid in onset and dose related. Response appeared to persist for more than 2 months with a lower dosing frequency. Results support further investigation in larger trials.

Trial Registration

clinicaltrials.gov identifier: NCT01998958.

Estimation of the relative difference (or relative risk reduction) under the sequential parallel comparison design

To increase power or reduce the number of patients needed in trials studying treatments for psychiatric or mental disorders with a high placebo response rate, we may consider use of the sequential parallel comparison design proposed elsewhere. Because statistical significance does not necessarily imply that the difference between treatment and placebo is of clinical importance, it is always of importance to quantify the treatment effect in clinical trials. When the patient responses are dichotomous, the treatment and other covariates effects are not likely additive. Thus, using a weighted average of the risk differences over two phases may not be a meaningful summary index to measure the treatment effect. To alleviate this concern, we consider use of the relative difference or relative risk reduction to measure the treatment effect. We derive both point and interval estimators for the relative difference by use of the weighted-least-squares estimator and Mantel-Haenszel type estimator. We employ Monte Carlo simulation to evaluate the finite-sample performance of these estimators in a variety of situations. We also include a procedure for testing the homogeneity of the relative difference between phases under the sequential parallel comparison design. We use the placebo-controlled study to assess the efficacy of a low dose of aripiprazole adjunctive to antidepressant therapy in the treatment of patients with major depressive disorder to illustrate the use of estimators developed here.

Methods for assessing and controlling placebo effects

The placebo serves as an indispensable control in many randomized trials. When analyzing the benefit of a new treatment, researchers are often confronted with large placebo effects that diminish the treatment effect. Various alternative methods have been proposed for analyzing placebo and treatment effects in studies where large placebo effects are expected or have already occurred. This paper presents an overview of methodological work that has been proposed for assessing and/or controlling for placebo effects in randomized trials. Throughout this paper, two main approaches are discussed. The first approach considers designs that represent alternatives to the classical placebo-controlled randomized trial design. Separately, the second approach considers adopting new methods for the statistical analysis of placebo and treatment effects to be implemented after the data have been collected using a classical randomized trial design.

A case study in identifying targeted patients population in major depressive disorder by enhanced enrichment design

Despite advances in clinical trial design, failure rates near 80% in phase 2 and 50% in phase 3 have recently been reported. The challenges to successful drug development are particularly acute in central nervous system trials such as for pain, schizophrenia, mania, and depression because high-placebo response rates lessen assay sensitivity, diminish estimated treatment effect sizes, and thereby decrease statistical power. This paper addresses the importance of rigorous patient selection in major depressive disorder trials through an enhanced enrichment paradigm. This approach led to a redefinition of an ongoing, blinded phase 3 trial algorithm for patient inclusion (1) to eliminate further randomization of transient placebo responders and (2) to exclude previously randomized transient responders from the primary analysis of the double blind phase of the trial. It is illustrated for a case study for the comparison between brexpiprazole + antidepressant therapy and placebo + antidepressant therapy. Analysis of the primary endpoint showed that efficacy of brexpiprazole versus placebo could not be established statistically if the original algorithm for identification of placebo responders was used, but the enhanced enrichment approach did statistically demonstrate efficacy. Additionally, the enhanced enrichment approach identified a target population with a clinically meaningful treatment effect. Through its successful identification of a target population, the innovative enhanced enrichment approach enabled the demonstration of a positive treatment effect in a very challenging area of depression research.

The plan of enrichment designs for dealing with high placebo response

To deal with high placebo response in clinical trials for psychiatric and other diseases, different enrichment designs, such as the sequential parallel design, two-way enriched design, and sequential enriched design, have been proposed and implemented recently. Depending on the historical trial information and the trial sponsors' resources, detailed design elements are needed for determining which design to adopt. To assist in making more suitable decisions, we perform evaluations for selecting required design elements in terms of power optimization and sample size planning. We also discuss the implementation of the interim analysis related to its applicability.

Obsessive-compulsive disorder has a reduced placebo (and antidepressant) response compared to other anxiety disorders: A meta-analysis

BACKGROUND

Previous studies have indicated that obsessive-compulsive disorder (OCD) might have a reduced placebo response compared to other anxiety-related disorders including generalized anxiety disorder, panic disorder, post-traumatic stress disorder, and social anxiety disorder. No previous analysis has directly compared antidepressant and placebo responses between OCD and these conditions.

METHOD

We analyzed pre-post change scores within drug and placebo groups as well as between-groups change scores (i.e., drug compared to placebo) for all FDA-approved antidepressants for the treatment of these five anxiety-related disorders. Antidepressants included duloxetine, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, and venlafaxine. Random effects meta-analysis was used to examine all trials submitted to the FDA, plus additional post-approval trials available from manufacturer-sponsored clinical trial registers. Clinician-rated symptom inventories were the outcome measures for all conditions to facilitate comparisons across diagnoses.

RESULTS

Fifty-six trials met inclusion criteria. OCD had significantly lower pre-post effect sizes (ps<0.003) for both placebo (Hedges' g=0.49) and antidepressants (g=0.84) compared to the other four conditions (gs between 0.70 and 1.10 for placebo and 1.11 and 1.40 for antidepressants). However, the drug-placebo effect sizes did not significantly differ across diagnoses (Q(4)=6.09, p=0.193, I² =34.3% [95% CI: -7.0,59.7]), with gs between=0.26 and 0.39.

CONCLUSIONS

Overall pre-post change scores were smaller for OCD compared to other anxiety disorders for both antidepressants and placebo, although drug-placebo effects sizes did not significantly differ across disorders. Theoretical and clinical implications for the understanding and treatment of OCD are discussed.

A randomized controlled trial of ganaxolone in posttraumatic stress disorder

Preclinical and clinical research supports a role for neuroactive steroids in the pathophysiology of posttraumatic stress disorder (PTSD). We investigated ganaxolone (a synthetic 3β-methylated derivative of allopregnanolone, a GABAergic neuroactive steroid) for treatment of PTSD in a proof-of-concept, multisite, double-blind, placebo-controlled trial. Veteran and non-veteran participants (n = 112) were randomized to ganaxolone or placebo at biweekly escalating doses of 200, 400, and 600 mg twice daily for 6 weeks. During an open-label 6-week extension phase, the initial ganaxolone group continued ganaxolone, while the placebo group crossed over to ganaxolone. Eighty-six and 59 participants, respectively, completed the placebo-controlled and open-label phases. A modified intent-to-treat mixed model repeated measures analysis revealed no significant differences between the effects of ganaxolone and placebo on Clinician Administered PTSD Symptom (CAPS) scores, global well-being, negative mood, or sleep. Dropout rates did not differ between groups, and ganaxolone was generally well tolerated. Trough blood levels of ganaxolone at the end of the double-blind phase were, however, lower than the anticipated therapeutic level of ganaxolone in >35% of participants on active drug. Pharmacokinetic profiling of the ganaxolone dose regimen used in the trial and adverse event sensitivity analyses suggest that under-dosing may have contributed to the failure of ganaxolone to out-perform placebo. Future investigations of ganaxolone may benefit from higher dosing, rigorous monitoring of dosing adherence, a longer length of placebo-controlled testing, and targeting of treatment to PTSD subpopulations with demonstrably dysregulated pre-treatment neuroactive steroid levels. Clinicaltrials.gov identifier: NCT01339689.

Sample size re-estimation and other midcourse adjustments with sequential parallel comparison design

Sequential parallel comparison design (SPCD) was proposed to reduce placebo response in a randomized trial with placebo comparator. Subjects are randomized between placebo and drug in stage 1 of the trial, and then, placebo non-responders are re-randomized in stage 2. Efficacy analysis includes all data from stage 1 and all placebo non-responding subjects from stage 2. This article investigates the possibility to re-estimate the sample size and adjust the design parameters, allocation proportion to placebo in stage 1 of SPCD, and weight of stage 1 data in the overall efficacy test statistic during an interim analysis.

Remarks on designs enriching for placebo non-responders

BACKGROUND

High response under placebo constitutes a concern in clinical studies, particularly in psychiatry. Discontinuation of placebo responders identified during a placebo run-in is often recommended to avoid failures of clinical trials in the presence of high placebo effects. Evidence for the benefit of this approach is ambiguous.

PURPOSE

We investigate under which conditions a placebo lead-in can be beneficial in the context of continuous data, assuming that the data in the placebo run-in and the treatment stage follow a bivariate normal distribution. Placebo responders are defined as patients with an effect during placebo lead-in which is larger than a pre-defined threshold on the absolute value or the absolute or relative change from baseline or a combination thereof.

RESULTS

Data are less variable under either placebo or test treatment after placebo responders have been removed. Whether the effect of test over placebo increases or decreases after enrichment for placebo non-responders depends on the parameters of the distribution, in particular the covariance structure, and the threshold in the definition of placebo responders.

LIMITATIONS

The results apply in the continuous case, and the binary or ordinary case is not studied. The findings explain to some extent the ambiguity in the assessments of the usefulness of placebo lead-in periods in clinical trials; however, besides the clear statement on variability reduction, it is not straightforward to judge upfront whether placebo lead-in is useful. Concerns relating to the conduct and interpretation of results of such trials are mentioned.

Methodological issues associated with preclinical drug development and increased placebo effects in schizophrenia clinical trials

Recent failures to detect efficacy in clinical trials investigating pharmacological treatments for schizophrenia raise concerns regarding the potential contribution of methodological shortcomings to this research. This review provides an examination of two key methodological issues currently suspected of playing a role in hampering schizophrenia drug development; 1) limitations on the translational utility of preclinical development models, and 2) methodological challenges posed by increased placebo effects. Recommendations for strategies to address these methodological issues are addressed.

On clinical trials with a high placebo response rate

The basic problem that causes the frequent failure of a standard randomized parallel placebo-controlled clinical trial with a high placebo response rate is the underestimation of the treatment effect by the observed relative treatment difference. A two-period sequential parallel enrichment design has been proposed where the first period is a standard parallel design and at the end of the first period, the placebo non-responders are identified and re-randomized in the second period. Based on such a design, available methods have primarily focused on testing either the first period treatment null hypothesis or the global null hypothesis defined as the joint period 1 and period 2 treatment effect null hypothesis by a test statistic which is either derived from a combined statistic or defined directly as a weighted z-score where the weights are functions of some population and design parameters satisfying certain power optimality criterion. However, in some cases, it is not clear what their combined statistics are estimating and in others, the combined statistics are estimating the apparent treatment effect; but generally, there is no discussion of the need to provide a proper assessment of the treatment effect for the intended study population. It should be clear that an appropriate assessment of the treatment effect for the intended study population is critical for the benefit/risk analysis as well as the proper dosage recommendation. Any benefit/risk analysis and dosage recommendation that are based on an apparent treatment effect from a standard parallel design such as the first period of a sequential parallel enrichment design tend to underestimate the benefit/risk ratio which in turn may lead to overdosing recommendation. It is the purpose of this paper to introduce the concept of an adjusted treatment effect which is derived by adjusting the apparent treatment effect from the first period of a sequential parallel enrichment design with information from the second period subject to a consistency condition. The adjustment properly compensates for the high placebo response rate. It is proposed that this adjusted treatment effect should be used to assess the treatment effect for the intended study population and should be the basis for the benefit/risk analysis and the dosage recommendation.

A Novel Methodology to Estimate the Treatment Effect in Presence of Highly Variable Placebo Response

One of the main reasons for the inefficiency of multicenter randomized clinical trials (RCTs) in depression is the excessively high level of placebo response. The aim of this work was to propose a novel methodology to analyze RCTs based on the assumption that centers with high placebo response are less informative than the other centers for estimating the 'true' treatment effect (TE). A linear mixed-effect modeling approach for repeated measures (MMRM) was used as a reference approach. The new method for estimating TE was based on a nonlinear longitudinal modeling of clinical scores (NLMMRM). NLMMRM estimates TE by associating a weighting factor to the data collected in each center. The weight was defined by the posterior probability of detecting a clinically relevant difference between active treatment and placebo at that center. Data from five RCTs in depression were used to compare the performance of MMRM with NLMMRM. The results of the analyses showed an average improvement of ~15% in the TE estimated with NLMMRM when the center effect was included in the analyses. Opposite results were observed with MMRM: TE estimate was reduced by ~4% when the center effect was considered as covariate in the analysis. The novel NLMMRM approach provides a tool for controlling the confounding effect of high placebo response, to increase signal detection and to provide a more reliable estimate of the 'true' TE by controlling false negative results associated with excessively high placebo response.