Are we drawing the right conclusions from randomised placebo-controlled trials? A post-hoc analysis of data from a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Assumptions underlying placebo controlled trials include that the placebo effect impacts on all study arms equally, and that treatment effects are additional to the placebo effect. However, these assumptions have recently been challenged, and different mechanisms may potentially be operating in the placebo and treatment arms. The objective of the current study was to explore the nature of placebo versus pharmacological effects by comparing predictors of the placebo response with predictors of the treatment response in a randomised, placebo-controlled trial of a phytotherapeutic combination for the treatment of menopausal symptoms. A substantial placebo response was observed but no significant difference in efficacy between the two arms.</p> <p>Methods</p> <p>A <it>post hoc </it>analysis was conducted on data from 93 participants who completed this previously published study. Variables at baseline were investigated as potential predictors of the response on any of the endpoints of flushing, overall menopausal symptoms and depression. Focused tests were conducted using hierarchical linear regression analyses. Based on these findings, analyses were conducted for both groups separately. These findings are discussed in relation to existing literature on placebo effects.</p> <p>Results</p> <p>Distinct differences in predictors were observed between the placebo and active groups. A significant difference was found for study entry anxiety, and Greene Climacteric Scale (GCS) scores, on all three endpoints. Attitude to menopause was found to differ significantly between the two groups for GCS scores. Examination of the individual arms found anxiety at study entry to predict placebo response on all three outcome measures individually. In contrast, <it>low </it>anxiety was significantly associated with improvement in the active treatment group. None of the variables found to predict the placebo response was relevant to the treatment arm.</p> <p>Conclusion</p> <p>This study was a <it>post hoc </it>analysis of predictors of the placebo versus treatment response. Whilst this study does not explore neurobiological mechanisms, these observations are consistent with the hypotheses that 'drug' effects and placebo effects are not necessarily additive, and that mutually exclusive mechanisms may be operating in the two arms. The need for more research in the area of mechanisms and mediators of placebo versus active responses is supported.</p> <p>Trial Registration</p> <p>International Clinical Trials Registry ISRCTN98972974.</p

Reactions to treatment debriefing among the participants of a placebo controlled trial

BACKGROUND: A significant proportion of trial participants respond to placebos for a variety of conditions. Despite the common conduct of these trials and the strong emphasis placed on informed consent, very little is known about informing participants about their individual treatment allocation at trial closure. This study aims to address this gap in the literature by exploring treatment beliefs and reactions to feedback about treatment allocation in the participants of a placebo-controlled randomized clinical trial (RCT). METHODS: Survey of trial participants using a semi-structured questionnaire including close and open-ended questions administered as telephone interviews and postal questionnaires. Trial participants were enrolled in a double-blind placebo-controlled RCT evaluating the effectiveness of corticosteroid for heel pain (ISRCTN36539116). The trial had closed and participants remained blind to treatment allocation. We assessed treatment expectations, the percentage of participants who wanted to be informed about their treatment allocation, their ability to guess and reactions to debriefing. RESULTS: Forty-six (73%) contactable participants responded to our survey. Forty-two were eligible (four participants with bilateral disease were excluded as they had received both treatments). Most (79%) participants did not have any expectations prior to receiving treatment, but many 'hoped' that something would help. Reasons for not having high expectations included the experimental nature of their care and possibility that they may get a placebo. Participants were hopeful because their pain was so severe and because they trusted the staff and services. Most (83%) wanted to be informed about their treatment allocation and study results. Over half (55%) said they could not guess which treatment they had been randomized to, and many of those who attempted a guess were incorrect. Reactions to treatment debriefing were generally positive, including in placebo responders. CONCLUSION: Our study suggests that most trial participants want to be informed about their treatment allocation and trial results. Further research is required to develop measure of hope and expectancy and to rigorously evaluate the effects of debriefing prospectively

The therapeutic effect of clinical trials: understanding placebo response rates in clinical trials – A secondary analysis

BACKGROUND AND PURPOSE: Placebo response rates in clinical trials vary considerably and are observed frequently. For new drugs it can be difficult to prove effectiveness superior to placebo. It is unclear what contributes to improvement in the placebo groups. We wanted to clarify, what elements of clinical trials determine placebo variability. METHODS: We analysed a representative sample of 141 published long-term trials (randomized, double-blind, placebo-controlled; duration > 12 weeks) to find out what study characteristics predict placebo response rates in various diseases. Correlational and regression analyses with study characteristics and placebo response rates were carried out. RESULTS: We found a high and significant correlation between placebo and treatment response rate across diseases (r = .78; p < .001). A multiple regression model explained 79% of the variance in placebo variability (F = 59.7; p < 0.0001). Significant predictors are, among others, the duration of the study (beta = .31), the quality of the study (beta = .18), the fact whether a study is a prevention trial (beta = .44), whether dropouts have been documented (beta = -.20), or whether additional treatments have been documented (beta = -.17). Healing rates with placebo are lower in the following diagnoses; neoplasms (beta = -.21), nervous diseases (beta = -.10), substance abuse (beta = -.14). Without prevention trials the amount of variance explained is 42%. CONCLUSION: Medication response rates and placebo response rates in clinical trials are highly correlated. Trial characteristics can explain some portion of the variance in placebo healing rates in RCTs. Placebo response in trials is only partially due to methodological artefacts and only partially dependent on the diagnoses treated

Competitive Tendering In The Netherlands: Central Planning Or Functional Specifications?

Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne

Novel study designs to investigate the placebo response

<p>Abstract</p> <p>Background</p> <p>Investigating the size and mechanisms of the placebo response in clinical trials have relied on experimental procedures that simulate the double-blind randomized placebo-controlled design. However, as the conventional design is thought to elucidate drug rather than placebo actions, different methodological procedures are needed for the placebo response.</p> <p>Methods</p> <p>We reviewed the respective literature for trials designs that may be used to elucidate the size of the placebo response and the mechanisms associated with it.</p> <p>Results</p> <p>In general, this can be done by either manipulation the information provided to the subjects, or by manipulation the timing of the drug applied. Two examples of each strategy are discussed: the "balanced placebo design" (BDP) and the "balanced cross-over design" (BCD) and their variants are based on false information, while the "hidden treatment" (HT) and the ""delayed response test" (DRT) are based on manipulating the time of drug action. Since most such approaches include deception or incomplete information of the subjects they are suitable for patient only with authorized deception.</p> <p>Conclusion</p> <p>Both manipulating the information provided to subjects (BDP, DCD) or manipulating the timing of drug application (HT, DRT) allows overcoming some of the restrictions of conventional drug trials in the assessment of the placebo response, but they are feasible mostly in healthy subjects for ethical reasons.</p

Resting-State Quantitative Electroencephalography Reveals Increased Neurophysiologic Connectivity in Depression

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–20 Hz) frequency bands. The frontopolar region contained the greatest number of “hub nodes” (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD

Has Behavioral Science Tumbled Through the Biological Looking Glass? Will Brief, Evidence-Based Training Return It From the Rabbit Hole?

Time constraints and professional demands leave practicing professionals unlikely to enroll in extended training such as a semester-long graduate course. Thus, the three-hour continuing education format has become a standard for those in practice. One may ask what sorts of training strategies optimize that format. To explore that, a three hour training program for seventy-six practicing mental health professionals, most of whom self-identified as psychologists, was devised. It made use of primarily antecedent techniques that have been shown to bring about changed perceptions on a number of topics. Content focused on two areas of importance to behavior analysts, the culture’s increasing acceptance of the biological causation model of disorders such as attentiondeficit hyperactivity disorder (ADHD), unipolar depression, anxiety disorders, and schizophrenia, and the field’s increasing reliance on medications, often to the exclusion of behavioral methods. Pre-post assessment showed that participants had changed their thinking regarding the two content areas. The authors caution that participants’ changed opinions may serve as setting events to changes in practice, but those changes are verbal. One must not assume changes in practice techniques will automatically occur

Functional impairment related to painful physical symptoms in patients with generalized anxiety disorder with or without comorbid major depressive disorder: post hoc analysis of a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Generalized anxiety disorder (GAD) is the most frequent anxiety disorder in primary care patients. It is known that painful physical symptoms (PPS) are associated with GAD, regardless the presence of comorbid major depressive disorder (MDD). However the specific role of such symptoms in patients' functional impairment is not well understood. The objective of the present study is to assess functional impairment related to the presence of PPS in patients with GAD.</p> <p>Methods</p> <p>This is a post hoc analysis of a cross-sectional study. Functioning, in the presence (overall pain score >30; Visual Analog Scale) or absence of PPS, was assessed using the Sheehan Disability Scale (SDS) in three groups of patients; 1) GAD and comorbid MDD (GAD+MDD+), 2) GAD without comorbid MDD (GAD+MDD-), 3) controls (GAD-MDD-). ANCOVA models were used.</p> <p>Results</p> <p>Of those patients with GAD+MDD+ (n = 559), 436 (78.0%) had PPS, compared with GAD+MDD- (249 of 422, 59%) and controls (95 of 336, 28.3%). Functioning worsened in both GAD groups in presence of PPS (SDS least squares mean total score: 16.1 vs. 9.8, p < 0.0001, GAD+MDD+; 14.3 vs. 8.2, p < 0.0001, GAD+MDD-). The presence of PPS was significantly associated with less productivity.</p> <p>Conclusions</p> <p>Functional impairment related to the presence of PPS was relevant. Clinical implications should be considered.</p

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

RationaleIdentification of biomarkers that establish diagnosis or treatment response is critical to the advancement of research and management of patients with depression.ObjectiveOur goal was to identify biomarkers that can potentially assess fluoxetine response and risk to poor treatment outcome.MethodsWe measured behavior, gene expression, and the levels of 36 neurobiochemical analytes across a panel of genetically diverse mouse inbred lines after chronic treatment with water or fluoxetine.ResultsGlyoxylase 1 (GLO1) and guanine nucleotide-binding protein 1 (GNB1) mostly account for baseline anxiety-like and depressive-like behavior, indicating a common biological link between depression and anxiety. Fluoxetine-induced biochemical alterations discriminated positive responders, while baseline neurobiochemical differences differentiated negative responders (p < 0.006). Results show that glial fibrillary acidic protein, S100 beta protein, GLO1, and histone deacetylase 5 contributed most to fluoxetine response. These proteins are linked within a cellular growth/proliferation pathway, suggesting the involvement of cellular genesis in fluoxetine response. Furthermore, a candidate genetic locus that associates with baseline depressive-like behavior contains a gene that encodes for cellular proliferation/adhesion molecule (Cadm1), supporting a genetic basis for the role of neuro/gliogenesis in depression.ConclusionWe provided a comprehensive analysis of behavioral, neurobiochemical, and transcriptome data across 30 mouse inbred strains that has not been accomplished before. We identified biomarkers that influence fluoxetine response, which, altogether, implicate the importance of cellular genesis in fluoxetine treatment. More broadly, this approach can be used to assess a wide range of drug response phenotypes that are challenging to address in human samples.Electronic supplementary materialThe online version of this article (doi:10.1007/s00213-011-2574-z) contains supplementary material, which is available to authorized users