Impact of active placebo controls on estimated drug effects in randomised trials: a systematic review of trials with both active placebo and standard placebo

BACKGROUND

An estimated 60% of pharmacological randomised trials use placebo control interventions to blind (i.e. mask) participants. However, standard placebos do not control for perceptible non-therapeutic effects (i.e. side effects) of the experimental drug, which may unblind participants. Trials rarely use active placebo controls, which contain pharmacological compounds designed to mimic the non-therapeutic experimental drug effects in order to reduce the risk of unblinding. A relevant improvement in the estimated effects of active placebo compared with standard placebo would imply that trials with standard placebo may overestimate experimental drug effects.

OBJECTIVES

We aimed to estimate the difference in drug effects when an experimental drug is compared with an active placebo versus a standard placebo control intervention, and to explore causes for heterogeneity. In the context of a randomised trial, this difference in drug effects can be estimated by directly comparing the effect difference between the active placebo and standard placebo intervention.

SEARCH METHODS

We searched PubMed, CENTRAL, Embase, two other databases, and two trial registries up to October 2020. We also searched reference lists and citations and contacted trial authors.

SELECTION CRITERIA

We included randomised trials that compared an active placebo versus a standard placebo intervention. We considered trials both with and without a matching experimental drug arm.

DATA COLLECTION AND ANALYSIS

We extracted data, assessed risk of bias, scored active placebos for adequacy and risk of unintended therapeutic effect, and categorised active placebos as unpleasant, neutral, or pleasant. We requested individual participant data from the authors of four cross-over trials published after 1990 and one unpublished trial registered after 1990. Our primary inverse-variance, random-effects meta-analysis used standardised mean differences (SMDs) of active versus standard placebo for participant-reported outcomes at earliest post-treatment assessment. A negative SMD favoured the active placebo. We stratified analyses by trial type (clinical or preclinical) and supplemented with sensitivity and subgroup analyses and meta-regression. In secondary analyses, we investigated observer-reported outcomes, harms, attrition, and co-intervention outcomes.

MAIN RESULTS

We included 21 trials (1462 participants). We obtained individual participant data from four trials. Our primary analysis of participant-reported outcomes at earliest post-treatment assessment resulted in a pooled SMD of -0.08 (95% confidence interval (CI) -0.20 to 0.04; I2 = 31%; 14 trials), with no clear difference between clinical and preclinical trials. Individual participant data contributed 43% of the weight of this analysis. Two of seven sensitivity analyses found more pronounced and statistically significant differences; for example, in the five trials with low overall risk of bias, the pooled SMD was -0.24 (95% CI -0.34 to -0.13). The pooled SMD of observer-reported outcomes was similar to the primary analysis. The pooled odds ratio (OR) for harms was 3.08 (95% CI 1.56 to 6.07), and for attrition, 1.22 (95% CI 0.74 to 2.03). Co-intervention data were limited. Meta-regression found no statistically significant association with adequacy of the active placebo or risk of unintended therapeutic effect.

AUTHORS' CONCLUSIONS

We did not find a statistically significant difference between active and standard placebo control interventions in our primary analysis, but the result was imprecise and the CI compatible with a difference ranging from important to irrelevant. Furthermore, the result was not robust, because two sensitivity analyses produced a more pronounced and statistically significant difference. We suggest that trialists and users of information from trials carefully consider the type of placebo control intervention in trials with high risk of unblinding, such as those with pronounced non-therapeutic effects and participant-reported outcomes.

Are investigators' access to trial data and rights to publish restricted and are potential trial participants informed about this? A comparison of trial protocols and informed consent materials

OBJECTIVES

To determine to which degree industry partners in randomised clinical trials own the data and can constrain publication rights of academic investigators.

METHODS

Cohort study of trial protocols, publication agreements and other documents obtained through Freedom of Information requests, for a sample of 42 trials with industry involvement approved by ethics committees in Denmark. The main outcome measures used were: proportion of trials where data was owned by the industry partner, where the investigators right to publish were constrained and if this was mentioned in informed consent documents, and where the industry partner could review data while the trial was ongoing and stop the trial early.

RESULTS

The industry partner owned all data in 20 trials (48%) and in 16 trials (38%) it was unclear. Publication constraints were described for 30 trials (71%) and this was not communicated to trial participants in informed consent documents in any of the trials. In eight trials (19%) the industry partner could review data during the trial, for 20 trials (48%) it was unclear. The industry partner could stop the trial early without any specific reason in 23 trials (55%).

CONCLUSIONS

Publication constraints are common, and data is often owned by industry partners. This is rarely communicated to trial participants. Such constraints might contribute to problems with selective outcome reporting. Patients should be fully informed about these aspects of trial conduct.

Reporting of harms in oncological clinical study reports submitted to the European Medicines Agency compared to trial registries and publications-a methodological review

BACKGROUND

An accurate and comprehensive assessment of harms is a fundamental part of an accurate weighing of benefits and harms of an intervention when making treatment decisions; however, harms are known to be underreported in journal publications. Therefore, we sought to compare the completeness of reporting of harm data, discrepancies in harm data reported, and the delay to access results of oncological clinical trials between three sources: clinical study reports (CSRs), clinical trial registries and journal publications.

METHODS

We used the EMA clinical data website to identify all trials submitted to the EMA between 2015 and 2018. We retrieved all CSRs and included all phase II, II/III or III randomised controlled trials (RCTs) assessing targeted therapy and immunotherapy for cancer. We then identified related records in clinical trial registries and journals. We extracted harms data for eight pre-specified variables and determined the completeness of reporting of harm data in each of the three sources.

RESULTS

We identified 42 RCTs evaluating 13 different drugs. Results were available on the EMA website in CSRs for 37 (88%) RCTs, ClinicalTrials.gov for 36 (86%), the European Clinical Trials Register (EUCTR) for 20 (48%) and in journal publications for 32 (76%). Harms reporting was more complete in CSRs than other sources. We identified marked discrepancies in harms data between sources, e.g. the number of patients discontinuing due to adverse events differed in CSRs and clinical trial registers for 88% of trials with data in both sources. For CSRs and publications, the corresponding number was 90%. The median (interquartile range) delay between the primary trial completion date and access to results was 4.34 (3.09-7.22) years for CSRs, 2.94 (1.16-4.52) years for ClinicalTrials.gov, 5.39 (4.18-7.33) years for EUCTR and 2.15 (0.64-5.04) years for publications.

CONCLUSIONS

Harms of recently approved oncological drugs were reported more frequently and in more detail in CSRs than in trial registries and journal publications. Systematic reviews seeking to address harms of oncological treatments should ideally use CSRs as the primary source of data; however, due to problems with access, this is currently not feasible.

Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials: overview of published comments and analysis of user practice in Cochrane and non-Cochrane reviews

BACKGROUND

The Cochrane risk of bias tool for randomized clinical trials was introduced in 2008 and has frequently been commented on and used in systematic reviews. We wanted to evaluate the tool by reviewing published comments on its strengths and challenges and by describing and analysing how the tool is applied to both Cochrane and non-Cochrane systematic reviews.

METHODS

A review of published comments (searches in PubMed, The Cochrane Methodology Register and Google Scholar) and an observational study (100 Cochrane and 100 non-Cochrane reviews from 2014).

RESULTS

Our review included 68 comments, 15 of which were categorised as major. The main strengths of the tool were considered to be its aim (to assess trial conduct and not reporting), its developmental basis (wide consultation, empirical and theoretical evidence) and its transparent procedures. The challenges of the tool were mainly considered to be its choice of core bias domains (e.g. not involving funding/conflicts of interest) and issues to do with implementation (i.e. modest inter-rater agreement) and terminology. Our observational study found that the tool was used in all Cochrane reviews (100/100) and was the preferred tool in non-Cochrane reviews (31/100). Both types of reviews frequently implemented the tool in non-recommended ways. Most Cochrane reviews planned to use risk of bias assessments as basis for sensitivity analyses (70 %), but only a minority conducted such analyses (19 %) because, in many cases, few trials were assessed as having "low" risk of bias for all standard domains (6 %). The judgement of at least one risk of bias domain as "unclear" was found in 89 % of included randomized clinical trials (1103/1242).

CONCLUSIONS

The Cochrane tool has become the standard approach to assess risk of bias in randomized clinical trials but is frequently implemented in a non-recommended way. Based on published comments and how it is applied in practice in systematic reviews, the tool may be further improved by a revised structure and more focused guidance.