Does a placebo run-in or a placebo treatment cell affect the efficacy of antidepressant medications?

The effect of nightly use of 150 mg cannabidiol on daytime neurocognitive performance in primary insomnia: a randomized controlled pilot trial

RATIONALE

Cannabidiol (CBD) is increasingly used as a sleep aid for insomnia; yet neurocognitive and subjective state effects following daily therapeutic use are unclear.

OBJECTIVES

To measure the effect of daily CBD use on neurocognitive performance and daily subjective mood in a population with primary insomnia.

METHODS

This study used a randomized, placebo-controlled, parallel design incorporating a single-blind placebo run-in week followed by a two-week double-blind dosing period, during which participants consumed 150 mg CBD (N = 15) or placebo (N = 15) sublingually 60-minutes daily before bed. Attention, executive function, reasoning, information processing, working and episodic memory were assessed using the CogPro system at the beginning of the placebo run-in, after 1-week and 2-weeks of dosing. Subjective states using visual analogue scales and side effects were recorded daily.

RESULTS

Cognitive performance was unaffected by nightly CBD supplementation (all p > 0.05). From baseline to trial conclusion, those receiving CBD reported greater experience of calmness, clear-headedness, coordination and were more likely to report side-effects of dry mouth relative to placebo (all p < 0.05).

CONCLUSIONS

Relative to placebo, daytime cognitive functioning following nightly supplementation as a therapeutic aid for primary insomnia was preserved under trial conditions. Results suggested an overall favourable safety profile, with larger controlled trials and thorough analyses of varying insomnia phenotypes necessary to corroborate these findings.

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.

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.

The future of psychopharmacology: a critical appraisal of ongoing phase 2/3 trials, and of some current trends aiming to de-risk trial programmes of novel agents

Despite considerable progress in pharmacotherapy over the past seven decades, many mental disorders remain insufficiently treated. This situation is in part due to the limited knowledge of the pathophysiology of these disorders and the lack of biological markers to stratify and individualize patient selection, but also to a still restricted number of mechanisms of action being targeted in monotherapy or combination/augmentation treatment, as well as to a variety of challenges threatening the successful development and testing of new drugs. In this paper, we first provide an overview of the most promising drugs with innovative mechanisms of action that are undergoing phase 2 or 3 testing for schizophrenia, bipolar disorder, major depressive disorder, anxiety and trauma-related disorders, substance use disorders, and dementia. Promising repurposing of established medications for new psychiatric indications, as well as variations in the modulation of dopamine, noradrenaline and serotonin receptor functioning, are also considered. We then critically discuss the clinical trial parameters that need to be considered in depth when developing and testing new pharmacological agents for the treatment of mental disorders. Hurdles and perils threatening success of new drug development and testing include inadequacy and imprecision of inclusion/exclusion criteria and ratings, sub-optimally suited clinical trial participants, multiple factors contributing to a large/increasing placebo effect, and problems with statistical analyses. This information should be considered in order to de-risk trial programmes of novel agents or known agents for novel psychiatric indications, increasing their chances of success.

An exploratory machine learning approach to identify placebo responders in pharmacological binge eating disorder trials

Randomized, placebo-controlled trials for binge eating disorder (BED) have revealed highly variable, and often marked, rates of short-term placebo response. Several quantitative based analyses in patients with BED have inconsistently demonstrated which patient factors attribute to an increase in placebo response. The objective of this study is to utilize machine learning (ML) algorithms to identify moderators of placebo response in patients with BED. Data were pooled from 12 randomized placebo-controlled trials evaluating different treatment options for BED. The final dataset consisted of 189 adults receiving placebo with complete information of baseline variables. Placebo responders were defined as patients experiencing ≥75% reduction in binge eating frequency (BEF) at study end point. Nine patient prerandomization variables were included as predictors. Patients were divided into training and testing subsets according to an 75%:25% distribution while preserving the proportion of placebo responders. All analysis was performed in the software Pumas 2.0. Gaussian Naïve Bayes algorithm showed the best cross-validation accuracy (~64%) and was chosen as the final algorithm. Shapley analysis suggested that patients with low baseline BEF and anxiety status were strong moderators of placebo response. Upon applying the final algorithm on the test dataset, the resulting sensitivity was 88% and prediction accuracy was 72%. This is the first application of ML to identify moderators of placebo response in BED. The results of this analysis confirm previous findings of lesser baseline disease severity and adds that patients with no anxiety are more susceptible to placebo response.

Effect of a Run-In Period on Estimated Treatment Effects in Cardiovascular Randomized Clinical Trials: A Meta-Analytic Review

Background A run-in period may increase adherence to intervention and reduce loss to follow-up. Whether use of a run-in period affects the magnitude of treatment effects is unknown. Methods and Results We conducted a meta-analysis comparing treatment effects from 11 systematic reviews of cardiovascular prevention trials using a run-in period with matched trials not using a run-in period. We matched run-in with non-run-in trials by population, intervention, control, and outcome. We calculated a ratio of relative risks (RRRs) using a random-effects meta-analysis. Our primary outcome was a composite of cardiovascular events, and the primary analysis was a matched comparison of clinical trials using a run-in period versus without a run-in period. We identified 66 run-in trials and 111 non-run-in trials (n=668 901). On meta-analysis there was no statistically significant difference in the magnitude of treatment effect between run-in trials (relative risk [RR], 0.83 [95% CI, 0.80-0.87]) compared with non-run-in trials (RR, 0.88 [95% CI, 0.84-0.91]; RRR, 0.95 [95% CI, 0.90-1.01]). There was no significant difference in the RRR for secondary outcomes of all-cause mortality (RRR, 0.97 [95% CI, 0.91-1.03]) or medication discontinuation because of adverse events (RRR, 1.05 [95% CI, 0.85-1.21]). Post hoc exploratory univariate meta-regression showed that on average a run-in period is associated with a statistically significant difference in treatment effect (RRR, 0.94 [95% CI, 0.90-0.99]) for cardiovascular composite outcome, but this was not statistically significant on multivariable meta-regression analysis (RRR, 0.95 [95% CI, 0.90-1.0]). Conclusions The use of a run-in period was not associated with a difference in the magnitude of treatment effect among cardiovascular prevention trials.

Association of Single-blind Placebo Run-in Periods With the Placebo Response in Randomized Clinical Trials of Antidepressants: A Systematic Review and Meta-analysis

Importance

Single-blind placebo run-in (PRI) periods are common in randomized clinical trials (RCTs) of treatment for depression. They aim to increase sensitivity to detect drug effects; however, the association of PRI periods with study outcomes remains unclear. This is concerning given the costs of PRI periods to patients and investigators.

Objective

To examine the association of the use of PRI periods with the placebo response, drug response, and drug-placebo difference among RCTs of antidepressants.

Data Sources

MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and PsycINFO, as well as repositories of unpublished studies, were systematically searched up to July 2021.

Study Selection

Included studies were double-blind, placebo-controlled RCTs of antidepressant medication among adults with depressive disorders.

Data Extraction and Synthesis

Data were extracted into a coding sheet, including the characteristics of studies, the characteristics of PRI periods, and the outcomes of studies.

Main Outcomes and Measures

Study outcomes were the primary depression symptom measure reported by the RCT. These outcomes were used to calculate effect sizes (Hedges g) of the within-group drug response and placebo response as well as the drug-placebo difference. Random-effects meta-analysis was used to calculate effect sizes, and subgroup analyses were used to compare outcomes depending on use of PRI periods.

Results

A total of 347 trials (representing 89 183 participants) were included; 174 studies (50%) reported using a single-blind PRI period. Response outcome data were available for 189 studies. Studies using PRI periods reported a smaller placebo response (g = 1.05 [95% CI, 0.98-1.11]; I2 = 82%) than studies that did not use a PRI period (g = 1.15 [95% CI, 1.09-1.21]; I2 = 81%; P = .02). Subgroup analysis showed a larger drug response size among studies that did not use a PRI period (g = 1.55 [95% CI, 1.49-1.61]; I2 = 85%) than those that did use a PRI period (g = 1.42 [95% CI, 1.36-1.48]; I2 = 81%; P = .001). The drug-placebo difference did not differ by use of PRI periods (g = 0.33 [95% CI, 0.29-0.38]; I2 = 47% for use of a PRI period vs g = 0.34 [95% CI, 0.30-0.38]; I2 = 54% for no use of PRI periods; P = .92). The likelihood of response to drug vs placebo also did not differ between studies that used a PRI period (odds ratio, 1.89 [95% CI, 1.76-2.03]) and those that did not use a PRI period (odds ratio, 1.77 [95% CI, 1.65-1.89]; P = .18).

Conclusions and Relevance

This study suggests that RCTs using PRI periods yield smaller within-group changes across both placebo and drug groups compared with RCTs without PRI periods. The reduction in effect size across groups was equivalent in magnitude. Consequently, PRI studies do not observe larger drug-placebo differences, suggesting that they do not increase trial sensitivity. As such, given the resources and probable deception required and risk to external validity, the practice of using PRI periods in RCTs of antidepressants should be ended.

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.

Meta-Analysis: Pediatric Placebo Response in Depression Trials Does Not Replicate in Anxiety and Obsessive-Compulsive Disorder Trials

Background: Placebo response has been identified as an important factor influencing the success of adult antidepressant trials, yet little research of placebo response has been conducted in pediatric populations. Understanding disorder-specific and transdiagnostic predictors of pediatric placebo response is important in designing successful child psychopharmacological trials. Methods: A PubMed search was conducted for all pediatric antidepressant randomized controlled trials treating depression, anxiety, or obsessive-compulsive disorder (OCD). A random-effects model was utilized to examine the magnitude of placebo symptom improvement using standardized mean difference (SMD) and placebo response rates. Stratified subgroup analysis was performed by diagnostic indication. Meta-regression was utilized to search possible correlates of placebo symptom improvement and placebo response rate. Results: Thirty antidepressant trials involving 2911 participants receiving placebo were included in this meta-analysis. Magnitude of placebo improvement and placebo response rates varied significantly across disorders; being greater in depression (SMD = 1.44, 95% confidence interval [CI]: 1.18 to 1.71) than anxiety disorders (SMD = 1.09, 95% CI: 0.77 to 1.41) and the lowest in OCD (SMD = 0.71, 95% CI: 0.32 to 1.12). Different predictors were associated with placebo response in different indications. Conclusions: Both the magnitude and predictors of placebo response in pediatric depression trials do not replicate across anxiety and OCD. Based on our results, across disorders, minimizing the number of sites might significantly reduce placebo improvement. In addition to these, we could potentially decrease the placebo response in depression trials by increasing the number of subjects enrolled per study site, minimizing the number of study visits and conducting the studies in the United States. Further research is needed into the predictors of placebo response in pediatric anxiety and OCD.

The association between placebo arm inclusion and adverse event rates in antidepressant randomized controlled trials: An examination of the Nocebo Effect

BACKGROUND

Antidepressant efficacy is influenced by patient expectations and, in randomized controlled trials (RCTs), the probability of receiving a placebo. It is unclear whether tolerability demonstrates a similar pattern. This study aimed to determine whether study design influences adverse event (AE) rates in antidepressant trials for subjects receiving active treatment or placebo.

METHODS

RCTs comparing one antidepressant to another antidepressant, placebo, or both in major depressive disorder (MDD) (1996-2018) were retrieved from Medline and PsycINFO. Clinicaltrials.gov was searched for unpublished trials. Of 1,997 studies screened, 77 trials were included. Studies were classified as drug-drug, drug-drug-placebo, or drug-placebo based on design and overall number of subjects experiencing any AE was recorded. Subgroup meta-analysis of proportions and meta-regression techniques were used to compare AE rates across study designs in patients receiving active antidepressant treatment and placebo.

RESULTS

Among the actively treated, AE rates were lower in drug-drug trials (58.5%) compared to drug-drug-placebo (75.7%) and drug-placebo (76.4%) (the model reported coefficients for percent differences between AE rates of different study designs were B=17.0, p<0.001 and B=17.8, p<0.001, respectively). AE rates in patients receiving placebo were not different between study designs.

LIMITATIONS

The present study is limited by the diverse range of study populations, variability in reporting of AEs, and specific antidepressants employed in the included trials.

CONCLUSIONS

The inclusion of a placebo arm in the study design was unexpectedly associated with higher rates of AEs among patients receiving active medication in antidepressant trials. This observation has important implications for interpretation of trial tolerability findings.

Prerandomization run-in periods in randomized controlled trials of chronic diseases: a methodological study

OBJECTIVE

To systematically review the epidemiology of prerandomized run-in periods in randomized controlled trials (RCTs) of chronic diseases.

STUDY DESIGN AND SETTING

Meta-epidemiologic study of all RCTs from the four highest impact medical journals from 2011 to 2016. Eligible trials included parallel RCTs that evaluated pharmacologic therapies in adults with chronic diseases with a minimum follow-up of 24 weeks.

RESULTS

Of 262 eligible manuscripts, 48 (18.3%), representing 42 unique RCTs, included run-in periods. Run-in periods were most common in cardiovascular disease and diabetes trials. Of the 42 RCTs, in 22 patients received the experimental therapy, 15 placebo, 4 both (either sequentially or in combination), and one did not report the run-in period drug. The median run-in period duration was 28 days (Q1: Q3 14: 66 days). Reasons for including a run-in period included ensuring eligibility criteria were met (18, 42.9%), excluding participants with nonadherence (18, 42.9%) and intolerances to therapy (15, 35.7%), and to standardize therapy prior to randomization (8, 19.0%). The median run-in completion rate was 77.4% (Q1: Q3 62.2:87.8%).

CONCLUSIONS

Run-in periods are uncommon in RCTs of chronic drug treatments and when used, their reporting is heterogeneous. Further research to improve the design, use, and reporting of run-in periods is necessary.

Placebo run-in periods in anticholinergic trials are not associated with treatment effect size or risk of attrition: an empirical evaluation

OBJECTIVES

We aimed to explore the impact of run-in periods on the magnitude of treatment effect and the risk of attrition in a sample of randomized trials.

STUDY DESIGN AND SETTING

We identified randomized trials from a published systematic review examining the effects of anticholinergics for the treatment of overactive bladders. We fitted meta-analytic mixed-effects models to assess whether the type of run-in (placebo run-in vs. no run-in) was associated with the magnitude of the effect estimates for the following outcomes: the number of voids per day, number of leakages per day, presence of dry mouth, cure/improvement, patient withdrawal from the trial, compliance with the trial protocol, and/or adherence to study drug. We adjusted for potential confounders.

RESULTS

A total of 96 trials met the eligibility criteria; 59 trials had no run-in (which included those with a screening or withdrawal period), 37 trials had a placebo run-in, and no trials had a drug run-in. The magnitude of the effect estimates for all outcomes did not importantly differ between trials with a placebo run-in and trials with no run-in. Adjustment for the confounding variables did not materially change the estimates.

CONCLUSION

The hypothesized benefits of placebo run-in periods were not observed in our sample of anticholinergic randomized trials for the treatment of overactive bladders. Designing future trials of anticholinergics with more pragmatic intentions is likely to result in evidence that more directly informs clinical decision-making.

Advancing the understanding of placebo effects in psychological outcomes of exercise: Lessons learned and future directions

Despite the apparent strength of scientific evidence suggesting that psychological benefits result from both acute and chronic exercise, concerns remain regarding the extent to which these benefits are explained by placebo effects. Addressing these concerns is methodologically and at times conceptually challenging. However, developments in the conceptualisation and study of placebo effects from the fields of psychology, neuroscience, pharmacology, and human performance offer guidance for advancing the understanding of placebo effects in psychological responses to exercise. In clinical trials, expectations can be measured and experimentally manipulated to better understand the influence of placebo effects on treatment responses. Further, compelling evidence has shown that the contribution of placebo effects and their underlying neurobiological mechanisms to treatment effects can be measured without administering a traditional placebo (e.g. inert substance) by leveraging psychological factors such as expectations and conditioning. Hence, the purpose of this focused review is to integrate lessons such as these with the current body of literature on placebo effects in psychological responses to exercise and provide recommendations for future research directions.

Early score fluctuation and placebo response in a study of major depressive disorder

Early score fluctuation in double-blind, placebo-controlled studies may affect the reliability of the baseline measurement and adversely affect the eventual study outcome. We examined the effect of early score fluctuation during a 2-week double-blind placebo lead-in period in a phase II, double-blind, placebo-controlled trial of adjunctive s-adenosyl methionine (MSI-195) in MDD subjects who had had an inadequate response to ongoing antidepressant treatment. The overall study failed to meet its specified endpoints. We examined the score trajectories of all placebo-assigned subjects during the double-blind placebo lead-in period and subsequent 6-week treatment period. Placebo-assigned subjects with ≥20% HamD₁₇ or MADRS score fluctuations (improvement or worsening) during the double-blind placebo lead-in period (prior to randomization) had significantly higher rates of placebo response and remission at week 8 compared to subjects with <20% response. A post-hoc analysis of evaluable subjects taken from the ITT population that excluded subjects with ≥20% early score response yielded higher effect sizes for both the HamD₁₇ and MADRS sub-groups and statistical significance for MSI-195 over placebo in the MADRS sub-group (p = 0.012) with an effect size of 0.404. A reliable baseline measure is an asset for signal detection. These post-hoc findings suggest that study designs that anticipate and attempt to manage early response prior to randomization may yield more meaningful outcome data for trials of MDD and possibly other disorders as well.

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.

Run-in periods and clinical outcomes of antipsychotics in dementia: A meta-epidemiological study of placebo-controlled trials

Purpose

Run‐in periods are used to identify placebo‐responders and washout. Our aim was to assess the association of run‐in periods with clinical outcomes of antipsychotics in dementia.

Methods

We searched randomized placebo‐controlled trials of conventional and atypical antipsychotics for neuropsychiatric symptoms (NPS) in dementia in electronic sources and references of selected articles. We extracted (a) the presence of a run‐in period, use of placebo/investigated drug during run‐in (versus washout only), and run‐in duration (1 week or more) and (b) the reduction in NPS, number of participants with somnolence, extrapyramidal symptoms (EPS), and deaths per treatment group. We pooled clinical outcomes comparing antipsychotic and placebo groups in trials with and without run‐in.

Results

We identified 35 trials. Twenty‐nine trials used run‐in. The pooled standardized mean difference in the reduction of NPS was −0.170 (95% CI, −0.227 to −0.112) in trials with run‐in and −0.142 (95% CI, −0.331 to 0.047) in trials without run‐in. The pooled odds ratio for somnolence was 2.8 (95% CI, 2.3‐3.5) in trials with run‐in and 3.5 (95% CI, 1.2‐10.7) in trials without run‐in; for EPS, these ORs were 1.8 (95% CI, 1.4‐2.2) and 2.0 (95% CI, 1.3‐3.1) respectively, and for mortality 1.4 (95% CI, 1.0‐2.0) and 1.6 (95% CI, 0.7‐3.4). The use of placebo/investigated drug during run‐in and run‐in duration did not affect the estimates in a consistent way.

Conclusions

The use of run‐in in trials might have led to overestimated efficacy and especially underestimated risks of side effects of antipsychotics compared with placebo for NPS in dementia.

Neuroimaging Studies of Antidepressant Placebo Effects: Challenges and Opportunities

Over the last two decades, neuroscientists have used antidepressant placebo probes to examine the biological mechanisms implicated in expectancies of mood improvement.However, findings from these studies have yet to elucidate a model-based theory that would explain the mechanisms through which antidepressant expectancies evolve to induce persistent mood changes. Compared to other fields, the development of experimental models of antidepressant placebo effects faces significant challenges, such as the delayed mechanism of action of conventional antidepressants and the complex internal dynamics of mood. Still, recent neuroimaging studies of antidepressant placebo effects have shown remarkable similarities to those observed in other disciplines (e.g., placebo analgesia), such as placebo-induced increased µ-opioid signaling and blood-oxygen-level dependent (BOLD) responses in areas involved in cognitive control, the representation of expected values and reward and emotional processing. This review will summarize these findings and the challenges and opportunities that arise from applying methodologies used in the field of placebo analgesia into the field of antidepressant placebo effects.

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.

Model-Informed Approach to Assess the Treatment Effect Conditional to the Level of Placebo Response

One of the most important reasons for failure of placebo-controlled randomized controlled clinical trials (RCTs) is the lack of appropriate methodologies for detecting treatment effect (TE; difference between placebo and active treatment response) in the presence of excessively low/high levels of placebo response. Although, the higher the level of placebo response in a trial, the lower the apparent detectable TE. TE is usually estimated in a conventional analysis of an RCT as an "apparent" TE value conditional to the level of placebo response in that RCT. A model-informed methodology is proposed to establish a relationship between level of placebo response and TE. This relationship is used to estimate the "typical" TE associated with a "typical" level of placebo response, irrespective of the level of placebo response observed. The approach can be valuable for providing a reliable estimate of TE, for conducting risk/benefit analysis, and for determining dosage recommendations.

Randomized clinical trials with run-in periods: frequency, characteristics and reporting

Background

Run-in periods are occasionally used in randomized clinical trials to exclude patients after inclusion, but before randomization. In theory, run-in periods increase the probability of detecting a potential treatment effect, at the cost of possibly affecting external and internal validity. Adequate reporting of exclusions during the run-in period is a prerequisite for judging the risk of compromised validity. Our study aims were to assess the proportion of randomized clinical trials with run-in periods, to characterize such trials and the types of run-in periods and to assess their reporting.

Materials and methods

This was an observational study of 470 PubMed-indexed randomized controlled trial publications from 2014. We compared trials with and without run-in periods, described the types of run-in periods and evaluated the completeness of their reporting by noting whether publications stated the number of excluded patients, reasons for exclusion and baseline characteristics of the excluded patients.

Results

Twenty-five trials reported a run-in period (5%). These were larger than other trials (median number of randomized patients 217 vs 90, P=0.01) and more commonly industry trials (11% vs 3%, P<0.01). The run-in procedures varied in design and purpose. In 23 out of 25 trials (88%), the run-in period was incompletely reported, mostly due to missing baseline characteristics.

Conclusion

Approximately 1 in 20 trials used run-in periods, though much more frequently in industry trials. Reporting of the run-in period was often incomplete, precluding a meaningful assessment of the impact of the run-in period on the validity of trial results. We suggest that current trials with run-in periods are interpreted with caution and that updates of reporting guidelines for randomized trials address the issue.

Buprenorphine/samidorphan combination for the adjunctive treatment of major depressive disorder: results of a phase III clinical trial (FORWARD-3)

BACKGROUND

The endogenous opioid system is a fundamental regulator of mood in humans. Previously reported clinical trials have demonstrated the efficacy of the investigational agent buprenorphine/samidorphan (BUP/SAM) combination, an opioid-system modulator, for the adjunctive treatment of major depressive disorder. We present here a third phase III study of different design.

METHODS

Adult patients with major depressive disorder and inadequate response to antidepressant therapy were enrolled in this double-blind, placebo-controlled, placebo run-in study to evaluate the efficacy, safety, and tolerability of adjunctive BUP/SAM 2 mg/2 mg. Patients with baseline Hamilton Depression Rating Scale score $20 received double-blind placebo in addition to background antidepressant therapy for 4 weeks. Nonresponders were randomized to receive adjunctive BUP/SAM 2 mg/2 mg or placebo for 6 weeks. The primary end point was change in Montgomery-Åsberg Depression Rating Scale (MADRS)-10 total score from randomization at baseline to the end of the 6-week treatment period.

RESULTS

Least-squares mean change in MADRS-10 score at end of treatment was -4.8 (SE 0.67) in the BUP/SAM 2 mg/2 mg group and -4.6 (SE 0.66) in the placebo group (mean difference -0.3 [SE 0.95], P=0.782). There were no differences in MADRS-based response or remission rates. Overall, 42.9% of the BUP/SAM 2 mg/2 mg group and 34.5% of the placebo group experienced at least one treatment-emergent adverse event during the 6-week treatment period, most of which were mild or moderate in severity. There were no clinically important changes in laboratory parameters, weight, or vital signs and no evidence of abuse potential during treatment or opiate-withdrawal symptoms post treatment.

CONCLUSION

Efficacy results in FORWARD-3 measured by change in MADRS-10 score did not meet the primary end point, but postbaseline improvement in MADRS-10 in the BUP/SAM 2 mg/2 mg group was consistent with that seen in previously reported trials. BUP/SAM 2 mg/2 mg was well tolerated.

An augmentation study of MSI-195 (S-adenosylmethionine) in Major Depressive Disorder

We conducted a 6-week double-blind, placebo-controlled, augmentation study comparing the efficacy and safety of MSI-195 800 mg (a proprietary formulation of S-adenosylmethionine) or placebo added to ongoing antidepressant medication (ADT) in acutely depressed subjects with Major Depressive Disorder (MDD) who had experienced an inadequate response to their ongoing ADT (The Horizon Study, ClinicalTrials.gov NCT01912196). There were 234 eligible subjects randomized to either MSI-195 (n = 118) or placebo (n = 116). There were no overall statistically significant differences found between MSI-195 added to ongoing ADT compared to placebo on any of 3 depression-rating instruments (HamD₁₇, MADRS, IDS-SR₃₀) in the ITT set. MSI-195 was generally safe and well tolerated with predominantly mild gastrointestinal side effects. Post-hoc analyses examined factors that might have affected study outcome. The ITT set was divided into subjects enrolled during the 1st half (first nine months) and 2nd half of the study. MSI-195 added to ongoing ADT was significantly better than placebo on both the HamD₁₇ and MADRS in the 1st half (p = 0.03 and 0.02 respectively), but not in the 2nd half of the study. Several demographic and clinical characteristics were significantly different between the two study segments including body mass index, pre-randomization symptom severity fluctuation, number of lifetime depressive episodes, and anxious depression sub-type. Thus, the characteristics of the enrolled subjects changed between the 1st and 2nd half of the study. These post-hoc findings highlight the inherent challenges encountered for subject selection in double-blind, placebo controlled trials and compel further investigation of enrollment criteria and moderating factors that affect treatment. The favorable safety profile and clinical benefit observed with MSI-195 in the 1st half of this study warrant further investigation in MDD.

Factors Associated With Response to Placebo in Patients With Irritable Bowel Syndrome and Constipation

BACKGROUND & AIMS

A high proportion of patients with irritable bowel syndrome (IBS) respond to placebo in clinical trials (estimated at about 40%). We aimed to identify factors that contribute to the high placebo response rate using data from a placebo-controlled trial of patients with IBS.

METHODS

We performed a retrospective analysis of 599 women with IBS with constipation who were in the placebo group of a 12-week, randomized, double-blind, phase 3 trial of the experimental medication renzapride. Primary analyses evaluated frequency of abdominal pain in patients who received placebo, defined as ≥30% pain improvement from baseline for ≥6 of the 12 study weeks. We performed backward elimination regression with bootstrapping to identify factors associated with response to placebo.

RESULTS

In the placebo group, 29.0% of the patients had an abdominal pain response. Factors associated with a response to placebo were baseline variation in abdominal pain (odds ratio [OR], 1.71), maximum baseline pain severity (OR, 1.34), and placebo response in study week 2 (OR, 2.23) or week 3 (OR, 3.69). Factors associated with lack of response to placebo were number of baseline complete spontaneous bowel movements (OR, 0.73; P = .019) and final baseline pain ratings (OR, 0.73; P < .001).

CONCLUSIONS

We identified factors associated with a response in abdominal pain to placebo using original data from an IBS clinical trial. Baseline factors associated with the placebo response in women with IBS and constipation included variation in baseline pain symptoms, severity of baseline symptoms, and early improvement of abdominal pain. These findings have significant implications for clinical trial design.

Placebo Effects Across Self-Report, Clinician Rating, and Objective Performance Tasks Among Women With Post-Traumatic Stress Disorder: Investigation of Placebo Response in a Pharmacological Treatment Study of Post-Traumatic Stress Disorder

PURPOSE/BACKGROUND

For a drug to acquire Food and Drug Administration approval, it must significantly outperform placebo treatment. In recent years, the placebo effect seems to be increasing in neuropsychiatric conditions. Here, we examine placebo effects across self-reported, clinically rated, and performance-based data from a trial using a corticotropin-releasing hormone receptor type 1 (CRHR1) antagonist for treatment of post-traumatic stress disorder (PTSD).

METHODS/PROCEDURES

Women with chronic PTSD were randomized to treatment with either GSK561679, a CRHR1 antagonist, or placebo. Before randomization, participants completed self-report scales, clinician-rated measures of PTSD and depression symptoms, and objective tests of cognition and functioning. Differences in change scores on measures were compared between GSK561679 and placebo-treated participants.

FINDINGS/RESULTS

GSK561679 failed to produce any significant improvement in the participants. A substantial placebo effect was observed in both self-report and clinical rating scales, with effect sizes up to 1.5 SD. No single variable predicted placebo-related changes. Notably, there was an improvement on objective performance measures of cognition that exceeded previous standards for practice effects.

IMPLICATIONS/CONCLUSIONS

Participants in this trial manifested retest effects on performance-based measures of cognition. Notably, they had minimal prior experience with performance-based assessments. Experiencing the structure and support of a clinical trial may have contributed to significant reductions in subject-reported and clinician-rated PTSD symptom levels. The improvement seen across all assessment domains was consistent with that seen in previous studies where the active treatments separated from placebo. Investigators conducting clinical trials treating PTSD patients should expect placebo effects and design studies accordingly.

Differences in the placebo response in duloxetine and venlafaxine trials

OBJECTIVE

Our analysis aimed at comparing the placebo effect sizes from randomized controlled trials (RCTs) of two widely prescribed antidepressants, namely duloxetine and venlafaxine, and at analysing a potential influence of the investigated drugs on the placebo response.

METHOD

We conducted a comprehensive systematic review and meta-analysis of placebo-controlled, double-blind RCTs, which examined the efficacy of duloxetine and venlafaxine in the acute treatment of major depressive disorder.

RESULTS

We included 71 studies (29 duloxetine trials and 43 venlafaxine trials; one study provided data for the duloxetine and the venlafaxine data set). The placebo effect sizes, defined as pre-postscore change divided by baseline standard deviation, differed significantly between venlafaxine and duloxetine studies (-2.51 vs. -2.09; test for subgroup differences P = 0.028; high heterogeneity). The analysis of effect modifiers and the metaregression analyses confirmed the drug, next to baseline depression severity and publication status, as the most influential independent predictor.

CONCLUSION

Our analyses show a significant difference in the placebo response between venlafaxine and duloxetine trials and suggest that the investigated drug has an influence on the placebo response that is not related to baseline severity, changes over the years or other variables we included.

Can knowledge of Placebo and Nocebo Mechanisms Help Improve Randomized Clinical Trials?

Over the last decade, there has been a substantial increase in negative results from randomized controlled trials (RCTs), which may be due to an increasing placebo response among other factors. Currently, identification and exclusion of placebo responders from trials are attempted to overcome this problem, but so far the success of these approaches has been limited. At the same time, the placebo-mechanism literature has highlighted how contextual factors, such as patients' expectations, interfere with the effect of drug administration, leading to a certain degree of uncertainty in RCTs. In this chapter, we review the current challenges of RCTs including the uncertainties of the active arm, the placebo arm, the additivity assumption, and the double-blind procedure. We use the placebo-mechanism literature to debate the strengths and weaknesses of attempts to identify and exclude placebo responders from trials. Finally, we illustrate how insights from the placebo-mechanism literature may point to new ways of improving RCTs.

Impact of demographic factors on the antidepressant effect: A patient-level data analysis from depression trials submitted to the Pharmaceuticals and Medical Devices Agency in Japan

A substantial and variable placebo response can cause unreliable findings in clinical trials designed to demonstrate the efficacy of antidepressants, and the high rate of failed trials represents a major obstacle in the development of new drugs for major depressive disorder (MDD). However, the influence of demographic and symptom factors on the antidepressant effect remains to be established. The purpose of this study was to estimate the magnitude of this influence. A patient-level meta-analysis of data from double-blind, randomized, placebo-controlled trials involving the use of antidepressants for adults with MDD was performed. Data from five confirmatory trials evaluating the efficacy of four antidepressants that were submitted to the Pharmaceuticals and Medical Devices Agency (PMDA) to support new drug applications were pooled (n = 1898). The change in the total score of 17-item Hamilton Depression Rating Scale (HDRS₁₇) was the primary outcome of interest in our analysis. The changes in the total HDRS₁₇ score in both the antidepressant medication group (ADM) and the placebo group (PBO) increased in relation to baseline symptom severity. Among older patients and those with a history of prior treatment with antidepressants, the changes in the total HDRS₁₇ score decreased in ADM and remained static in PBO. There were no notable clinical symptoms that influenced the change in the total HDRS₁₇ score. Baseline symptom severity, participant age and a history of previous treatment with antidepressants were suggested as moderators of the antidepressant effect. The drug-placebo difference in the estimated changes as a function of baseline symptom severity varied depending on the regression models used, and further studies are required to investigate appropriate models.

Early symptomatic improvement affects treatment outcome in a study of major depressive disorder

Early symptomatic improvement immediately following randomization can affect signal detection in clinical trials. The impact of early improvement of the Montgomery-Asberg depression rating scale (MADRS) on eventual treatment outcome was examined in a 6-week, double-blind, placebo-controlled trial of a putative antidepressant (CX157) versus placebo in depressed subjects with major depressive disorder (MDD) who had had an inadequate response to ongoing antidepressant treatment (NCT00739908). MADRS score changes within one week after randomization directly affected treatment outcome at the study endpoint (week 6). The response and remission rates at week 6 increased significantly as the percent of MADRS score improvement increased between baseline and week 1 regardless of treatment assignment. Less MADRS improvement or actual worsening within the first week after randomization was associated with minimal overall MADRS score changes by week 6 in either treatment assignment. Alternatively, CX157 assigned subjects who had ≥30% improvement by week 1 achieved a significantly greater treatment response rate than the matched placebo group at the study endpoint (p = 0.025) that converted the lack of signal detection in the mITT population. This post-hoc analysis highlights the potent effect that early symptomatic improvement immediately following randomization can have on treatment outcome, and is particularly relevant for antidepressant drugs with rapid onset of action. The findings compel further exploration of possible moderating and mediating factors, including the experimental condition itself that can influence early response, and the need to identify "bio-types" within the population of MDD subjects.

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.

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.

Placebo Washout is not a Meaningful Part of Antidepressant Drug Trials

Most trials testing the effectiveness of psychotropic drugs begin with a placebo washout phase. Hypothetically this technique rids studies of placebo re-spenders before randomization of subjects to drug and placebo groups. In theory, this lowers the level of response to placebo in the study and magnifies the superiority of the response to medication. An analysis of 10 years of research literature demonstrates that the washout technique does not do what it was designed to do in antidepressant studies. Within placebo or drug groups neither measures of depression nor dropouts were affected by including a preliminary washout in the design. The findings are consistent with the two other studies that have addressed this issue.

Maintenance of Blinding in Clinical Trials and the Implications for Studying Analgesia Using Cannabinoids

The design of analgesic clinical trials invariably involves a comparison between placebo and active study medication. An assumption is made that treatment effects can be approximated by subtracting the response to placebo from that attained with the use of active study medication. However, the psychoactivity of cannabinoids may unmask their presence and lead to an expectation and/or conditioning of pain relief. For example, study participants biased toward the belief that cannabis is beneficial for their condition might be more inclined to report positive effects if they were to accurately identify the active treatment because of its psychoactivity. This may lead to incorrect assumptions regarding the efficacy of a cannabinoid. Methodologies designed to counteract unmasking need to be implemented in the design phase of a study. During the clinical trial, it is also important to query participants as to which treatment they believe they have received. Blinding can be considered to be preserved when the accuracy of treatment guesses is not considerably different than random guessing, which is estimated to be correct 50% of the time. After a study has been completed, the use of statistical methodologies such as regression and mediation analysis are worthy of consideration to see whether psychoactive effects biased the results.

Predicting Therapeutic Effects of Psychodiagnostic Assessment Among Children and Adolescents Participating in Randomized Controlled Trials

This study explored predictors of improvement after completing a psychodiagnostic screening assessment but before randomization among youth who participated in two pilot randomized controlled trials of omega-3 supplementation and Individual-Family Psychoeducational Psychotherapy (PEP). Ninety-five youth (56.8% male, 61.1% White) ages 7-14 with mood disorders completed screening and baseline assessments (including Clinical Global Impressions-Improvement [CGI-I], Children's Depression Rating Scale-Revised, Young Mania Rating Scale), then were randomized into a 12-week trial of omega-3, PEP, their combination, or placebo. Between screening and randomization, 35.8% minimally improved (CGI-I = 3), 12.6% much improved (CGI-I < 3), totaling 48.4% improved. Caregiver postsecondary education (p = .018), absence of attention-deficit/hyperactivity disorder (p = .027), and lower screen depression severity (p = .034) were associated with CGI-I. Caregiver postsecondary education (p = .020) and absence of a disruptive behavior diagnosis (p = .038) were associated with depression severity improvement. Prerandomization improvement moderated treatment outcomes: Among youth who improved prerandomization, those who received PEP (alone or with omega-3) had more favorable placebo-controlled depression trajectories due to a lack of placebo response. This open-label trial of psychodiagnostic assessment provides suggestive evidence that psychodiagnostic assessment is beneficial, especially for those with depression and without externalizing disorders. Prerandomization improvement is associated with better placebo-controlled treatment response. Future research should test alternative hypotheses for change and determine if less intensive (shorter and/or automated) assessments would provide comparable results.

Mechanisms of the placebo effect in pain and psychiatric disorders

Placebo effect research over the past 15 years has improved our understanding of how placebo treatments reduce patient symptoms. The expectation of symptom improvement is the primary factor underlying the placebo effect. Such expectations are shaped by past experiences, contextual cues and biological traits, which ultimately modulate one's degree of response to a placebo. The body of evidence that describes the physiology of the placebo effect has been derived from mechanistic studies primarily restricted to the setting of pain. Imaging findings support the role of endogenous opioid and dopaminergic networks in placebo analgesia in both healthy patients as well as patients with painful medical conditions. In patients with psychiatric illnesses such as anxiety disorders or depression, a vast overlap in neurological changes is observed in drug responders and placebo responders supporting the role of serotonergic networks in placebo response. Molecular techniques have been relatively underutilized in understanding the placebo effect until recently. We present an overview of the placebo responder phenotypes and genetic markers that have been associated with the placebo effect in pain, schizophrenia, anxiety disorders and depression.

Mitigating the Effects of Nonadherence in Clinical Trials

Accounting for subject nonadherence and eliminating inappropriate subjects in clinical trials are critical elements of a successful study. Nonadherence can increase variance, lower study power, and reduce the magnitude of treatment effects. Inappropriate subjects (including those who do not have the illness under study, fail to report exclusionary conditions, falsely report medication adherence, or participate in concurrent trials) confound safety and efficacy signals. This paper, a product of the International Society for CNS Clinical Trial Methodology (ISCTM) Working Group on Nonadherence in Clinical Trials, explores and models nonadherence in clinical trials and puts forth specific recommendations to identify and mitigate its negative effects. These include statistical analyses of nonadherence data, novel protocol design, and the use of biomarkers, subject registries, and/or medication adherence technologies.

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.

INFLUENCE OF STUDY DESIGN ON TREATMENT RESPONSE IN ANXIETY DISORDER CLINICAL TRIALS

OBJECTIVE

The influence of study design variables and publication year on response to medication and placebo was investigated in clinical trials for social anxiety disorder (SAD), generalized anxiety disorder (GAD), and panic disorder (PD).

METHOD

Hierarchical linear modeling determined whether publication year, treatment assignment (medication vs. placebo), study type (placebo-controlled or active comparator), study duration, and the number of study visits affected the mean change associated with medication and placebo.

RESULTS

In the 66 trials examined, the change associated with both medication and placebo increased over time (t = 4.23, df = 39, P < .001), but average drug-placebo differences decreased over time (t = -2.04, df = 46, P = .047). More severe baseline illness was associated with greater drug-placebo differences for serotonin norepinephrine reuptake inhibitors (SNRIs, t = 3.46, df = 106, P = .001) and selective serotonin reuptake inhibitors (SSRI, t = 10.37, df = 106, P < .001). Improvement with medication was significantly greater in active-comparator studies compared to placebo-controlled trials (t = 3.41, df = 39, P = .002). A greater number of study visits was associated with greater symptom improvement in PD trials relative to SAD (t = 2.83, df = 39, P = .008) and GAD (t = 2.16, df = 39, P = .037).

CONCLUSIONS

Placebo response is substantial in SAD, GAD, and PD trials, and its rise over time has been associated with diminished drug-placebo differences. Study design features that influence treatment response in anxiety disorder trials include patient expectancy, frequency of follow-up visits, and baseline illness severity.

The VA augmentation and switching treatments for improving depression outcomes (VAST-D) study: Rationale and design considerations

Because two-thirds of patients with Major Depressive Disorder do not achieve remission with their first antidepressant, we designed a trial of three "next-step" strategies: switching to another antidepressant (bupropion-SR) or augmenting the current antidepressant with either another antidepressant (bupropion-SR) or with an atypical antipsychotic (aripiprazole). The study will compare 12-week remission rates and, among those who have at least a partial response, relapse rates for up to 6 months of additional treatment. We review seven key efficacy/effectiveness design decisions in this mixed "efficacy-effectiveness" trial.

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.

Predicting placebo response in adolescents with major depressive disorder: The Adolescent Placebo Impact Composite Score (APICS)

OBJECTIVE

The aim of this study was to construct a composite scoring system to predict the probability of placebo response in adolescents with Major Depressive Disorder (MDD).

METHOD

Participants of the current study were 151 adolescents (aged 12-17 years) who were randomized to the placebo arm (placebo transdermal patches) of a randomized controlled trial (RCT) comparing the selegiline transdermal patch with placebo (DelBello et al., 2014). The primary outcome of response was defined as a CGI-I score of 1 or 2 (very much or much improved) at week 12 (study-end) or exit. As a first step, a multiple logistic mixed model was used to estimate the odds of placebo response from each predictor in the model, including age, CDRS-R total at baseline (depressive symptom severity), history of recurrent depression (yes vs. no), sex (female vs. male), and race (non-Caucasian vs. Caucasian). On the basis of the initial logistic mixed model analysis, we then constructed an Adolescent Placebo Impact Composite Score (APICS) that became the sole predictor in a re-specified Bayesian logistic regression model to estimate the probability of placebo response. Finally, the AUC for the APICS was tested against a nominal area of 0.50 to evaluate how well the APICS discriminated placebo response status.

RESULTS

Among the 151 adolescents, with a mean age of 14.6 years (SD = 1.6) and a mean baseline CDRS-R total of 60.6 (SD = 12.1), 68.2% were females, 50.3% was Caucasian, and 39.7% had a history of recurrent depression. Placebo response rate was 58.3%. Based on the logistic mixed model, the re-specified equation with the highest discriminatory ability to estimate the probability of placebo response was APICS = age + (0.32 × CDRS-R Total at baseline) + (-2.85 × if female) + (-5.50 × if history of recurrent depression) + (-5.85 × if non-Caucasian). The AUC for this model was 0.59 (p = .049). Within a Bayesian decision-theoretic framework, in 95.5% of the time, the 10,000 posterior Monte Carlo samples suggested that as APICS decreased the probability of placebo response increased. The observed APICS and related probability of responding to placebo in this adolescent sample ranged from 14.1 = 74.1% (in placebo responders) to 39.1 = 41.8% (in placebo non-responders).

CONCLUSION

The APICS model estimates the probability of placebo response in adolescents with MDD with a modest degree of accuracy (AUC = 0.59) and with a reasonable degree of positive predictive value (74.5%), and is based on five previously identified patient characteristics of placebo response from prior meta-analytic studies (Bridge et al., 2009; Cohen et al., 2010) of randomized placebo-controlled trials of antidepressants in youth with MDD. Calculation of the APICS should be restricted to the range of the adolescent ages (12-17 years) and CDRS-R total scores (17-113); thus, the APICS can assume possible calculated values and related probability of responding to placebo ranging from about 3 (84%) to 53 (25%). The APICS Bayesian logistic model, based on a given aggregate patient profile, has a range of predicted probabilities of placebo response that is fairly wide, albeit truncated, but potentially meaningful for predicting the probability of placebo response among adolescent youth with MDD. The ability of the APICS to objectify the probability of placebo response in adolescents with MDD could be accounted for in the clinical research design of the trial itself and perhaps aid clinicians in treatment strategy for youth who are more likely to experience placebo response.

A sequential enriched design for target patient population in psychiatric clinical trials

High placebo response is widely believed to be one major reason why many psychiatric clinical trials fail to demonstrate drug efficacy. In order to alleviate this problem, research has developed several enrichment designs, including the parallel design with a placebo lead-in phase, the sequential parallel design, and a recently proposed two-way enriched design. While these designs have been evaluated and discussed individually, their effectiveness against each other has not been rigorously compared. The current study examines the various enrichment designs simultaneously. Building on their strengths, we introduce a new improved design named' sequential enriched design' (SED) aimed at removing not only patients with high placebo response but also patients who do not respond to any treatment from the study. The SED begins with a double-blind placebo lead-in phase followed by a traditional parallel design in the first stage. Only patients who respond to the drug in the first stage are re-randomized to the drug or placebo at the second stage. We simulate data for a mixed population composed of four subgroups of patients who are predetermined as to whether they respond to drug or not as well as to placebo or not. By focusing on the target patients whose responses reflect the drug's efficacy,we evaluate the bias, mean squared error, and power for different designs. We demonstrate that the SED produces a less biased estimate for the target treatment effect and yields reasonably high power in general compared with the other designs.

Nocebo vs. placebo: the challenges of trial design in analgesia research

The placebo effect in randomized clinical trials appears to have increased thereby contributing to problems of demonstrating statistically reliable effects of treatments that directly target biological mechanisms. The shortcomings of randomized clinical trials are currently discussed along with potential improvements of trial designs. In this review we explain how utilizing knowledge from the placebo and nocebo mechanisms literature could improve the information that can be obtained from randomized clinical trials. We present three major challenges in randomized clinical trials: (i) increasing placebo effects, (ii) variability of the placebo effect, and (iii) risk of un-blinding. We then explain how recent placebo and nocebo studies of effects of verbal suggestion, expectancy, and emotions may improve understanding and discussion of increasing placebo effects, account/control for large parts of the variability of placebo effects, and suggest ways to improve blinding in future trials.

From Randomized Controlled Trials of Antidepressant Drugs to the Meta-Analytic Synthesis of Evidence: Methodological Aspects Lead to Discrepant Findings

During the last decade, several meta-analytic studies employing different methodological approaches have had inconsistent conclusions regarding antidepressant efficacy. Herein, we aim to comment on methodological aspects that may have contributed to disparate findings. We initially discuss methodological inconsistencies and limitations related to the conduct of individual antidepressant randomized controlled trials (RCTs), including differences in allocated samples, limitations of psychometric scales, possible explanations for the heightened placebo response rates in antidepressant RCTs across the past two decades as well as the reporting of conflicts of interest. In the second part of this article, we briefly describe the various meta-analyses techniques (e.g., simple random effects meta-analysis and network meta-analysis) and the application of these methods to synthesize evidence related to antidepressant efficacy. Recently published antidepressant metaanalyses often provide discrepant results and similar results often lead to different interpretations. Finally, we propose strategies to improve methodology considering real-world clinical scenarios.

The role of patient expectancy in placebo and nocebo effects in antidepressant trials

OBJECTIVE

To determine whether patient expectancy plays a role in observed placebo and nocebo effects in 2 clinical trials.

METHOD

Data were reanalyzed from 2 fluoxetine-discontinuation studies conducted from March 1990 to September 1992 and from May 1997 to December 2002. The 673 outpatients included were aged 18-65 years with DSM-III-R major depressive disorder (MDD), responded to 12-week duration open treatment, and were randomized to continued fluoxetine or placebo for an additional year. Participants in 1 of the included studies received a fixed dose of fluoxetine 20 mg daily, while the second study utilized flexible fluoxetine doses up to 60 mg daily. Mixed effects longitudinal models determined whether the possible randomization to placebo at 12 weeks resulted in significant depressive symptom worsening across treatments. Correlations were computed between early symptom change (weeks 1-3 of open treatment) and postrandomization symptom change (weeks 13-16 following randomization).

RESULTS

Participants continuing to receive fluoxetine and those switched to placebo had significantly higher mean Hamilton Depression Rating Scale (HDRS) scores immediately postrandomization compared to the final weeks of open treatment (P < .001 for both fluoxetine- and placebo-treated patients). In both studies, early HDRS change was significantly correlated with postrandomization HDRS change for patients receiving fluoxetine (r = -0.46, P < .001) as well as placebo (r = -0.48, P < .001).

CONCLUSIONS

The possibility of receiving placebo following 12 weeks of open fluoxetine was associated with significant symptom worsening in 2 large fluoxetine discontinuation studies. Worsening depression scores following randomization were significantly associated with the degree of improvement participants experienced during weeks 1-3 of open treatment. These results suggest that treatment changes influence patients' expectations of improvement, which, in turn, affect their depressive symptoms.