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Joint Estimation of Treatment and Placebo Effects in Clinical Trials with Longitudinal Blinding Assessments.

ABSTRACT: In some therapeutic areas, treatment evaluation is frequently complicated by a possible placebo effect (i.e., the psychobiological effect of a patient's knowledge or belief of being treated). When a substantial placebo effect is likely to exist, it is important to distinguish the treatment and placebo effects in quantifying the clinical benefit of a new treatment. These causal effects can be formally defined in a joint causal model that includes treatment (e.g., new versus placebo) and treatmentality (i.e., a patient's belief or mentality about which treatment she or he has received) as separate exposures. Information about the treatmentality exposure can be obtained from blinding assessments, which are increasingly common in clinical trials where blinding success is in question. Assuming that treatmentality has a lagged effect and is measured at multiple time points, this article is concerned with joint evaluation of treatment and placebo effects in clinical trials with longitudinal follow-up, possibly with monotone missing data. We describe and discuss several methods adapted from the longitudinal causal inference literature, apply them to a weight loss study, and compare them in simulation experiments that mimic the weight loss study.

SUBMITTER: Liu W

PROVIDER: S-EPMC4838817 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Joint Estimation of Treatment and Placebo Effects in Clinical Trials with Longitudinal Blinding Assessments.

Liu Wei W Zhang Zhiwei Z Schroeder R Jason RJ Ho Martin M Zhang Bo B Long Cynthia C Zhang Hui H Irony Telba Z TZ

Journal of the American Statistical Association 20160818 514

In some therapeutic areas, treatment evaluation is frequently complicated by a possible placebo effect (i.e., the psychobiological effect of a patient's knowledge or belief of being treated). When a substantial placebo effect is likely to exist, it is important to distinguish the treatment and placebo effects in quantifying the clinical benefit of a new treatment. These causal effects can be formally defined in a joint causal model that includes treatment (e.g., new versus placebo) and treatment ...[more]

PMID: 27110045

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Project description:ObjectivesTo study the impact of blinding on estimated treatment effects, and their variation between trials; differentiating between blinding of patients, healthcare providers, and observers; detection bias and performance bias; and types of outcome (the MetaBLIND study).DesignMeta-epidemiological study.Data sourceCochrane Database of Systematic Reviews (2013-14).Eligibility criteria for selecting studiesMeta-analyses with both blinded and non-blinded trials on any topic.Review methodsBlinding status was retrieved from trial publications and authors, and results retrieved automatically from the Cochrane Database of Systematic Reviews. Bayesian hierarchical models estimated the average ratio of odds ratios (ROR), and estimated the increases in heterogeneity between trials, for non-blinded trials (or of unclear status) versus blinded trials. Secondary analyses adjusted for adequacy of concealment of allocation, attrition, and trial size, and explored the association between outcome subjectivity (high, moderate, low) and average bias. An ROR lower than 1 indicated exaggerated effect estimates in trials without blinding.ResultsThe study included 142 meta-analyses (1153 trials). The ROR for lack of blinding of patients was 0.91 (95% credible interval 0.61 to 1.34) in 18 meta-analyses with patient reported outcomes, and 0.98 (0.69 to 1.39) in 14 meta-analyses with outcomes reported by blinded observers. The ROR for lack of blinding of healthcare providers was 1.01 (0.84 to 1.19) in 29 meta-analyses with healthcare provider decision outcomes (eg, readmissions), and 0.97 (0.64 to 1.45) in 13 meta-analyses with outcomes reported by blinded patients or observers. The ROR for lack of blinding of observers was 1.01 (0.86 to 1.18) in 46 meta-analyses with subjective observer reported outcomes, with no clear impact of degree of subjectivity. Information was insufficient to determine whether lack of blinding was associated with increased heterogeneity between trials. The ROR for trials not reported as double blind versus those that were double blind was 1.02 (0.90 to 1.13) in 74 meta-analyses.ConclusionNo evidence was found for an average difference in estimated treatment effect between trials with and without blinded patients, healthcare providers, or outcome assessors. These results could reflect that blinding is less important than often believed or meta-epidemiological study limitations, such as residual confounding or imprecision. At this stage, replication of this study is suggested and blinding should remain a methodological safeguard in trials.

Project description:BackgroundBlinding is an established approach in clinical trials which aims to minimise the risk of performance and detection bias. There is little empirical evidence to guide UK clinical trials units (CTUs) about the practice of blinding statisticians. Guidelines recommend that statisticians remain blinded to allocation prior to the final analysis. As these guidelines are not based on empirical evidence, this study undertook a qualitative investigation relating to when and how statisticians should be blinded in clinical trials.MethodsData were collected through online focus groups with various stakeholders who work in the delivery and oversight of clinical trials. Recordings of the focus groups were transcribed verbatim and thematic analysis was used to analyse the transcripts.ResultsThirty-seven participants from 19 CTUs participated in one of six focus groups. Four main themes were identified, namely statistical models of work, factors affecting the decision to blind statisticians, benefits of blinding/not blinding statisticians and practicalities. Factors influencing the decision to blind the statistician included available resources, study design and types of intervention and outcomes and analysis. Although blinding of the statistician is perceived as a desirable mitigation against bias, there was uncertainty about the extent to which an unblinded statistician might impart bias. Instead, in most cases, the insight that the statistician offers was deemed more important to delivery of a trial than the risk of bias they may introduce if unblinded. Blinding of statisticians was only considered achievable with the appropriate resource and staffing, which were not always available. In many cases, a standard approach to blinding was therefore considered unrealistic and impractical; hence the need for a proportionate risk assessment approach identifying possible mitigations.ConclusionsThere was wide variation in practice between UK CTUs regarding the blinding of trial statisticians. A risk assessment approach would enable CTUs to identify risks associated with unblinded statisticians conducting the final analysis and alternative mitigation strategies. The findings of this study will be used to design guidance and a tool to support this risk assessment process.

Project description:BackgroundPatient expectancy of therapeutic improvement is a primary mediator of placebo effects in antidepressant clinical trials, but its mechanisms are poorly understood. This study employed a novel antidepressant trial design, with integrated functional magnetic resonance imaging (fMRI), to manipulate patient outcome expectancy and examine its neural mediators.MethodTwenty-three depressed outpatients, in a randomized controlled trial were assigned to either Open (high outcome expectancy) or Placebo-controlled (low outcome expectancy) treatment with citalopram for eight weeks. fMRI scans were acquired before and after the expectancy manipulation (before medication treatment), while participants performed a masked emotional face task. Focusing on an amygdala region-of-interest (ROI), we tested a model where reduction in amygdala activation mediated outcome expectancy effects on the slope of change in depressive symptoms.ResultsFollowing the manipulation, significant differences between conditions were found in neural activation changes in the amygdala, as well as in superior temporal gyrus, insula, and thalamus. Findings support the proposed mediation model according to which activation in the left amygdala ROI decreased significantly in the Open as opposed to the Placebo-controlled group following randomization (p = 0.009) for sad vs. neutral face contrast. The reduced left amygdala activation, in turn, was a significant predictor of decreased depressive symptoms during the trial (p = 0.007), and the mediation model was significant.ConclusionsResults from this study, the first designed to identify the neural mechanisms of expectancy augmentation in an antidepressant randomized control trial, suggest that therapeutic modulation of amygdala activity may be an important pathway by which patient outcome expectancy influences depressive symptoms. CLINICALTRIALS.Gov identifierNCT01919216; Trial name: Placebo Effects in the Treatment of Depression: Cognitive and Neural Mechanisms, URL: https://clinicaltrials.gov/ct2/show/NCT01919216.

Dataset Information

Joint Estimation of Treatment and Placebo Effects in Clinical Trials with Longitudinal Blinding Assessments.

Publications

Joint Estimation of Treatment and Placebo Effects in Clinical Trials with Longitudinal Blinding Assessments.

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