The antidepressant debate and the balanced placebo trial design: an ethical analysis

Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research

It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response heterogeneity in nutrition and obesity research. Our goal is to educate nutrition and obesity researchers in how to correctly identify and consider treatment response heterogeneity when analyzing data and interpreting results, leading to rigorous and accurate advancements in the field of personalized medicine.

Placebo and Active Treatment Additivity in Placebo Analgesia: Research to Date and Future Directions

Placebo analgesia is a robust experimental and clinical phenomenon. While our understanding of the mechanisms of placebo analgesia has developed rapidly, some central questions remain unanswered. Among the important questions is how placebo analgesia interacts with active analgesic effects. It is an assumption underlying double-blind randomized placebo-controlled trials (RCTs) that the true effect of a treatment can be determined by examining the effect of the active treatment arm and subtracting the response in the placebo group ("the assumption of additivity"). However, despite the importance of this assumption for the interpretation of RCTs, it has rarely been formally examined. This article reviews the assumption of additivity in placebo analgesia by examining studies employing factorial designs manipulating both the receipt of an active analgesic and instructions about the treatment being delivered. In reviewing the literature, we identified seven studies that allowed a test of additivity. Of these, four found evidence against additivity, while the remaining three studies found results consistent with additivity. While the limited available data are somewhat mixed, the evidence suggests that at least under some conditions the assumption of additivity does not hold in placebo analgesia. The concordance between mechanisms of the active analgesic and placebo analgesia may influence whether additivity occurs or not. However, more research using factorial designs is needed to disentangle the relationship between placebo analgesia and the active effect of analgesic treatments.

Randomization to randomization probability: Estimating treatment effects under actual conditions of use

Blinded randomized controlled trials (RCT) require participants to be uncertain if they are receiving a treatment or placebo. Although uncertainty is ideal for isolating the treatment effect from all other potential effects, it is poorly suited for estimating the treatment effect under actual conditions of intended use-when individuals are certain that they are receiving a treatment. We propose an experimental design, randomization to randomization probabilities (R2R), which significantly improves estimates of treatment effects under actual conditions of use by manipulating participant expectations about receiving treatment. In the R2R design, participants are first randomized to a value, π, denoting their probability of receiving treatment (vs. placebo). Subjects are then told their value of π and randomized to either treatment or placebo with probabilities π and 1-π, respectively. Analysis of the treatment effect includes statistical controls for π (necessary for causal inference) and typically a π-by-treatment interaction. Random assignment of subjects to π and disclosure of its value to subjects manipulates subject expectations about receiving the treatment without deception. This method offers a better treatment effect estimate under actual conditions of use than does a conventional RCT. Design properties, guidelines for power analyses, and limitations of the approach are discussed. We illustrate the design by implementing an RCT of caffeine effects on mood and vigilance and show that some of the actual effects of caffeine differ by the expectation that one is receiving the active drug. (PsycINFO Database Record

On the Maintenance of Expectations in Major Depression - Investigating a Neglected Phenomenon

In this perspective paper, we suggest that among patients suffering from major depressive disorder (MDD), dysfunctional expectations are maintained despite experiences that are contrary to these expectations. Surprisingly, this persistence of expectations in MDD has not yet been addressed by empirical studies. We argue that it is worthwhile to investigate this phenomenon with the aim of improving the treatment of MDD, and we provide a theoretical framework for understanding it. It is hypothesized that the persistence of expectations is primarily due to a process called immunization. That is, people experiencing depressive symptoms may cognitively reappraise the contradictory experience such that expectations do not need to be changed. There may be two mechanisms underlying this immunization: (1) the experience in the expectation-violating situation is considered to be an exception; or (2) the credibility of the information gained from the experience is called into question. Moreover, the maintenance of expectations may be particularly persistent if a person’s expectations reflect his or her self-concept, as self-concept has been shown to be associated with future expectations. To empirically examine the hypothesized maintenance of expectations in MDD, we propose an experimental approach which could provide important implications for the treatment of MDD within cognitive behavioral therapy. We suggest that psychological interventions such as behavioral experiments should more rigorously focus on patients’ appraisal of expectation-violating experiences in order to prevent immunization processes. Therapists should continuously examine whether patients’ expectations were modified and should address the reasons for the maintenance of expectations.

Drug*placebo interaction effect may bias clinical trials interpretation: hybrid balanced placebo and randomized placebo-controlled design

Background

Conventional randomized placebo-controlled study design assumes the absence of drug*placebo interaction. We hypothesized the presence of such an interaction and that conventionally estimated drug effect might be biased. The objectives of the study were to determine the drug*placebo interaction effect (main) and compare conventionally estimated and interaction model-estimated drug effects (secondary).

Methods

We used a hybrid of balanced placebo and randomized placebo-controlled designs. Four hundred eighty healthy volunteers were randomized to three groups. The first received hydroxyzine (25 mg) described as hydroxyzine or placebo, the second received placebo described as hydroxyzine or placebo, and the third received hydroxyzine and placebo described as unknown; each in a randomized crossover design. Seven participants failed to crossover. Group assignment was concealed from participants and study coordinators. Coordinators were blinded to group and intervention assignment. Participants and coordinators were deceived as to study objectives. Main outcomes were mean area-under-the-curve of drowsiness (therapeutic outcome) and mouth-dryness (adverse outcome), self-reported on 100 mm visual analog scale over 7 h. Drug, placebo, placebo + interaction, and total effects were estimated using analysis of covariance by comparing received hydroxyzine/told placebo to received placebo/told placebo, received placebo/told hydroxyzine to received placebo/told placebo, received hydroxyzine/told hydroxyzine to received hydroxyzine/told placebo, and received hydroxyzine/told hydroxyzine to received placebo/told placebo, respectively. Drug effect was also conventionally estimated in the third group.

Results

Mean (SD) age was 31.4 (6.6) years, 65% were males. There was significant difference between placebo + interaction effect and placebo effect for both drowsiness and mouth-dryness with a mean difference (95% confidence interval) of 35.1 (5.6 to 64.6) and 23.8 (2.4 to 45.2) mm*hr, respectively. Total effect was larger than the sum of drug and placebo effects for drowsiness (139.7 (109.8 to 169.6) vs. 99.1 (68.2 to 130.0) mm*hr) and mouth-dryness (63.6 (41.1 to 86.1) vs. 34.7 (11.1 to 58.4) mm*hr). Conventionally estimated drug effect was larger than interaction model-estimated drug effect for drowsiness (69.2 (45.5 to 92.8) vs. (58.3 (31.6 to 85.0) mm*hr) and mouth-dryness (19.9 (5.3 to 34.5) vs. 9.5 (−9.2 to 28.1) mm*hr).

Conclusions

There is significant and important drug*placebo interaction effect that may bias conventionally estimated drug effect.

Trial registration

ClinicalTrial.gov identifier: NCT01501591 (registered December 25, 2011).

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.

Randomised controlled trials may underestimate drug effects: balanced placebo trial design

Background

It is an inherent assumption in randomised controlled trials that the drug effect can be estimated by subtracting the response during placebo from the response during active drug treatment.

Objective

To test the assumption of additivity. The primary hypothesis was that the total treatment effect is smaller than the sum of the drug effect and the placebo effect. The secondary hypothesis was that non-additivity was most pronounced in participants with large placebo effects.

Methods

We used a within-subject randomised blinded balanced placebo design and included 48 healthy volunteers (50% males), mean (SD) age 23.4 (6.2) years. Experimental pain was induced by injections of hypertonic saline into the masseter muscle. Participants received four injections with hypertonic saline along with lidocaine or matching placebo in randomised order: A: received hypertonic saline/told hypertonic saline; B: received hypertonic saline+lidocaine/told hypertonic saline; C: received hypertonic saline+placebo/told hypertonic saline+pain killer; D: received hypertonic saline+lidocaine/told hypertonic saline+pain killer. The primary outcome measure was the area under the curve (AUC, mm²) of pain intensity during injections.

Results

There was a significant difference between the sum of the drug effect and the placebo effect (mean AUC 6279 mm² (95% CI, 4936–7622)) and the total treatment effect (mean AUC 5455 mm² (95% CI, 4585–6324)) (P = 0.049). This difference was larger for participants with large versus small placebo effects (P = 0.015), and the difference correlated significantly with the size of the placebo effect (r = 0.65, P = 0.006).

Conclusion

Although this study examined placebo effects and not the whole placebo response as in randomised controlled trials, it does suggest that the additivity assumption may be incorrect, and that the estimated drug effects in randomised controlled trials may be underestimated, particularly in studies reporting large placebo responses. The implications for randomised controlled trials and systematic reviews need to be discussed.

Improving study design for antidepressant effectiveness assessment

Antidepressants effectiveness in major depressive disorder (MDD) is still questioned because the extrapolation of randomized controlled trial (RCT) results to "real life" settings is problematic. The application of the RCT paradigm in a disorder of this type, where global care plays a central role, raises questions regarding the internal and external validity of this type of study. Outcome measurement, attrition rates, the ability of the double-blind design to control for expectations, placebo response, the representativeness of trial participants and publication bias are major methodological pitfalls. This review discusses these issues. It is illustrated using original data and proposes some alternatives for assessing antidepressant effectiveness via different approaches. Some are easy to implement, such as ecological measures, qualitative approaches, improvement of analytical strategy and improvement of blinding procedures. Some are sophisticated, involving temporary deception to deal with the confounding effect of expectations, and they raise ethical issues. Others resort to external validity, this being the case in observational studies. But all are necessary to explore antidepressant effectiveness.

Antidepressant drugs and the response in the placebo group: the real problem lies in our understanding of the issue

In a recent paper, Horder and colleagues (Horder et al., 2010, J Psychopharmacol 25: 1277-1288) have suggested that the mainproblem in the Kirsch analysis is methodological. We argue that the results are similar irrespective of the method used. In our opinion the data suggest that placebo and drug effects are non-additive: antidepressants act independently of depression severity, while the placebo effect is present only in milder cases. While the response in the placebo group is due to unstable 'noise' and 'artefacts', the medication effect is reliable, valid and stable.

General and comparative efficacy and effectiveness of antidepressants in the acute treatment of depressive disorders: a report by the WPA section of pharmacopsychiatry

Current gold standard approaches to the treatment of depression include pharmacotherapeutic and psychotherapeutic interventions with social support. Due to current controversies concerning the efficacy of antidepressants in randomized controlled trials, the generalizability of study findings to wider clinical practice and the increasing importance of socioeconomic considerations, it seems timely to address the uncertainty of concerned patients and relatives, and their treating psychiatrists and general practitioners. We therefore discuss both the efficacy and clinical effectiveness of antidepressants in the treatment of depressive disorders. We explain and clarify useful measures for assessing clinically meaningful antidepressant treatment effects and the types of studies that are useful for addressing uncertainties. This includes considerations of methodological issues in randomized controlled studies, meta-analyses, and effectiveness studies. Furthermore, we summarize the differential efficacy and effectiveness of antidepressants with distinct pharmacodynamic properties, and differences between studies using antidepressants and/or psychotherapy. We also address the differential effectiveness of antidepressant drugs with differing modes of action and in varying subtypes of depressive disorder. After highlighting the clinical usefulness of treatment algorithms and the divergent biological, psychological, and clinical efforts to predict the effectiveness of antidepressant treatments, we conclude that the spectrum of different antidepressant treatments has broadened over the last few decades. The efficacy and clinical effectiveness of antidepressants is statistically significant, clinically relevant, and proven repeatedly. Further optimization of treatment can be helped by clearly structured treatment algorithms and the implementation of psychotherapeutic interventions. Modern individualized antidepressant treatment is in most cases a well-tolerated and efficacious approach to minimize the negative impact of otherwise potentially devastating and life-threatening outcomes in depressive disorders.

Efficacy of antidepressants: a re-analysis and re-interpretation of the Kirsch data

Recently there has been much debate on the true usefulness of antidepressant therapy especially after the publication of a meta-analysis by Kirsch et al. (PLoS Medicine 2008, 5, e45). The aim of the current paper was to recalculate and re-interpret the data of that study. Effect-size and mean-score changes were calculated for each agent separately as well as pooled effect sizes and mean changes on the basis of the data reported by Kirsch et al. The weighted mean improvement was (depending on the method of calculation) 10.04 or 10.16 points on the Hamilton Depression Rating Scale (HAMD) in the drug groups, instead of 9.60, and thus the correct drug-placebo difference is 2.18 or 2.68 instead of 1.80. Kirsch et al. failed to report that that the change in HAMD score was 3.15 or 3.47 points for venlafaxine and 3.12 or 3.22 for paroxetine, which are above the NICE threshold. Still the figures for fluoxetine and nefazodone are low. Thus it seems that the Kirsch et al.'s meta-analysis suffered from important flaws in the calculations; reporting of the results was selective and conclusions unjustified and overemphasized. Overall the results suggest that although a large percentage of the placebo response is due to expectancy this is not true for the active drug and effects are not additive. The drug effect is always present and is unrelated to depression severity, while this is not true for placebo.

Interaction between drug and placebo effects: a cross-over balanced placebo design trial

Background

The total effect of a medication is the sum of its drug effect, placebo effect (meaning response), and their possible interaction. Current interpretation of clinical trials' results assumes no interaction. Demonstrating such an interaction has been difficult due to lack of an appropriate study design.

Methods

180 adults were randomized to caffeine (300 mg) or placebo groups. Each group received the assigned intervention described by the investigators as caffeine or placebo, in a randomized crossover design. 4-hour-area-under-the-curve of energy, sleepiness, nausea (on 100 mm visual analog scales), and systolic blood pressure levels as well as caffeine pharmacokinetics (in 22 volunteers nested in the caffeine group) were determined. Caffeine drug, placebo, placebo-plus-interaction, and total effects were estimated by comparing outcomes after, receiving caffeine described as placebo to receiving placebo described as placebo, receiving placebo described as caffeine or placebo, receiving caffeine described as caffeine or placebo, and receiving caffeine described as caffeine to receiving placebo described as placebo, respectively.

Results

The placebo effect on area-under-the-curve of energy (mean difference) and sleepiness (geometric mean ratio) was larger than placebo-plus-interaction effect (16.6 [95% CI, 4.1 to 29.0] vs. 8.4 [-4.2 to 21.0] mm*hr and 0.58 [0.39 to 0.86] vs. 0.69 [0.49 to 0.97], respectively), similar in size to drug effect (20.8 [3.8 to 37.8] mm*hr and 0.49 [0.30 to 0.91], respectively), and its combination with the later was larger than total caffeine effect (29.5 [11.9 to 47.1] mm*hr and 0.37 [0.22 to 0.64]). Placebo-plus-interaction effect increased caffeine terminal half-life by 0.40 [0.12 to 0.68] hr (P = 0.007).

Conclusions

Drug and placebo effects of a medication may be less than additive, which influences the interpretation of clinical trials. The placebo effect may increase active drug terminal half-life, a novel mechanism of placebo action.

Trial Registration

ClinicalTrials.gov identification number - NCT00426010.

Participant expectancies in double-blind randomized placebo-controlled trials: potential limitations to trial validity

BACKGROUND

Randomized controlled trials (RCTs) that use placebo controls to achieve double-blinding intend to establish the efficacy of a treatment over and above expectancy and other forms of bias. Despite this, a growing body of research suggests that participant expectancies can influence the outcomes of these trials.

PURPOSE

and

METHODS

This nonsystematic review examines research assessing the role of participant expectancies in double-blind placebo-controlled RCTs in order to determine if and how they can limit these types of trials.

RESULTS

There appear to be at least three ways in which participant expectancies can limit the validity of double-blind placebo-controlled RCTs. First, when blinding fails researches cannot determine whether any observed improvement in the group receiving active treatment resulted because of the treatment's effect or because of participants' expectancies. Second, participant expectancies could create ceiling effects if there are strong placebo effects in each treatment arm and this may falsely suggest that the active treatment is ineffective without expectancy. Third, the knowledge that a participant will be allocated active treatment or placebo in double-blind placebo-controlled RCTs is likely to lead to weaker treatment responses than would be expected in standard clinical practice, in which patients are unlikely to doubt that they have been given an active treatment.

CONCLUSIONS

Participants' expectancies can undermine the validity of double-blind placebo-controlled RCTs. Researchers conducting these trials should assess participants' beliefs about their treatment allocation and actively investigate if and how these beliefs may have influenced the trial's outcome. Clinical Trials 2010; 7: 246-255. http://ctj.sagepub.com.

Importance of placebo effect in cough clinical trials

Cough is a unique symptom because, unlike sneeze and other symptoms, it can be under voluntary control and this complicates clinical trials on cough medicines. All over-the-counter cough medicines (OTC) are very effective treatments because of their placebo effect. The placebo effect is enhanced by expectancy related to advertising, brand, packaging, and formulation. This placebo effect creates a problem for the conduct of clinical trials on OTC cough medicines that attempt to demonstrate the efficacy of a pharmacological agent above that of any placebo effect. Up to 85% of the efficacy of some cough medicines can be attributed to a placebo effect. The placebo effect apparent in clinical trials consists of several components: natural recovery, regression of cough response toward mean, demulcent effect, effect of sweetness, voluntary control, and effects related to expectancy and meaning of the treatment. The placebo effect has been studied most in the pain model, and placebo analgesia is reported to depend on the activation of endogenous opioid systems in the brain; this model may be applicable to cough. A balanced placebo design may help to control for the placebo effect, but this trial design may not be acceptable due to deception of patients. The placebo effect in clinical trials may be controlled by use of a crossover design, where feasible, and the changes in the magnitude of the placebo effect in this study design are discussed.