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To study the impact of lack of blinding of outcome assessors on estimated treatment effects of randomized clinical trials. Meta-epidemiological study. We included randomized trials with binary or measurement scale outcomes that (1) allocated patients to subtrials with and without blinded outcome assessment, or (2) had both blinded and non-blinded assessments of the same outcome. We identified trials from previous meta-epidemiological studies and searched six databases from 2013 to 2024. We calculated a ratio of odds ratios (ROR) for each trial. A ROR < 1 indicated a more favorable effect estimate by the non-blinded assessor. We pooled RORs using random effects meta-analysis and conducted meta-regression, subgroup, and sensitivity analyses. We included 66 trials (9451 patients) across 18 clinical specialties. The pooled RORs in 43 trials (7055 patients) was 0.71 (0.55–0.92). Thirty of the 43 trials assessed highly subjective outcomes. Meta-regression showed no statistically significant association between ROR and scores for outcome subjectivity (P = .53), vulnerability (P = .91), and involvement (P = .99). Heterogeneity was partly explained by a larger impact in non-drug trials, ROR 0.62 (0.46–0.84), and industry-funded trials, ROR 0.57 (0.37–0.88). Sensitivity analyses, including imputed data for 23 trials (2396 patients randomized), did not modify the observed impact importantly. We provide empirical evidence of considerable bias in effect estimates of randomized trials with non-blinded assessors of subjective binary and measurement scale outcomes. Non-blinded assessors exaggerated effect estimates, expressed as odds ratios, by 29% (8%–45%) on average. This strongly supports blinding outcome assessors of subjective outcomes. In a randomized clinical trial, the person evaluating the results (assessor) may be either unaware of the intervention received by participants (blinded assessor) or aware of it (non-blinded assessor). Knowing which treatment a patient received can influence the assessor's evaluation of the effect; for example, if an assessor has high expectations for a new experimental intervention, they may rate a patient's improvement more favorably in the group that received the intervention compared to the group that did not. We call this observer bias. In this study, we compared the results obtained from blinded assessors to those from non-blinded assessors within the same trials to estimate the impact of observer bias in randomized trials. We found that non-blinded assessors exaggerated the experimental intervention effect by approximately 29%, on average, compared to blinded assessors. Our results indicate that when an evaluation of a patient in a randomized trial requires judgment, there is potential for substantial bias if assessors are not blinded. To ensure more reliable results, randomized clinical trials should blind assessors whenever possible. •Substantial bias in the effect estimates of randomized trials with nonblinded assessors of subjective outcomes.•Nonblinded assessors exaggerate effect estimates, expressed as odds ratios, by 29% (8%-45%), on average.•Outcome assessors of randomized trials with subjective outcomes should be blinded whenever possible.

AbstractObjectivesTo 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.

Randomized clinical trials often involve blinding as a methodological procedure to avoid bias. Unfortunately, blinding procedures may be unsuccessful, but the risk of unblinding is rarely reported in trial publications. Our primary aim was to assess the occurrence of unreported assessment of the risk of unblinding in randomized clinical trials and to describe the assessment procedures involved. Our secondary aim was to assess the occurrence of unreported suspected or overt unblinding and the mechanisms of unblinding. A Web-based questionnaire survey of authors to trial publications which did not report risk of unblinding. Respondents were corresponding authors to a random sample of PubMed indexed articles on blinded randomized clinical trials published in 2010. We initially sampled 300 publications of which 24 reported on risk of unblinding. Of the 276 contacted trial authors, 129 (47%) responded. Assessment of the risk of unblinding was conducted in 56 trials (43%), often based on a pretrial evaluation involving a group of healthy assessors trying to identify differences between experimental and control interventions. When we included informal assessments of the risk of unblinding, the number of trials assessing the risk of unblinding increased to 75 (58%). Suspected or overt unblinding occurred in 14 trials (11%), mostly based on perceptible differences between experimental and control interventions. Approximately 4 of 10 trials assessed risk of unblinding without reporting such assessments in the trial publication, and approximately 1 in 10 trials identified cases of overt or suspected unblinding, also without reporting them. Unblinding is not an exceptional event in randomized clinical trials; it occurs regularly but is rarely reported.

To assess the proportion of clinical trials explicitly reporting the risk of unblinding, to evaluate the completeness of reporting on unblinding risk, and to describe the reported procedures involved in assessing unblinding. We sampled at random 300 blinded randomized clinical trials indexed in PubMed in 2010. Two authors read the trial publications and extracted data independently. Twenty-four trial publications, or 8% (95% confidence interval [CI], 5, 12%), explicitly reported the risk of unblinding, of which 16 publications, or 5% (95% CI, 3, 8%), reported compromised blinding; and 8 publications, or 3% (95% CI, 1, 5%), intact blinding. The reporting on risk of unblinding in the 24 trial publications was generally incomplete. The median proportion of assessments per trial affected by unblinding was 3% (range 1–30%). The most common mechanism for unblinding was perceptible physical properties of the treatments, for example, a difference in the taste and odor of a typhoid vaccine compared with its placebo. Published articles on randomized clinical trials infrequently reported risk of unblinding. This may reflect a tendency for avoiding reporting actual or suspected unblinding or a genuine low risk of unblinding.

The degree of bias in randomized clinical trials varies depending on whether the outcome is subjective or objective. Assessment of the risk of bias in a clinical trial will therefore often involve categorization of the type of outcome. Our primary aim was to examine how the concepts “subjective outcome” and “objective outcome” are defined in methodological publications and clinical trial reports. To put this examination into perspective, we also provide an overview of how outcomes are classified more broadly. A systematic review of methodological publications providing a classification of clinical trial outcomes and a descriptive study of how outcomes were classified in 200 PubMed indexed clinical trial reports published in 2012. We identified 90 methodological publications with some form of a classification of outcomes. Three distinct definitions were provided for subjective outcome: (1) dependent on assessor judgment, (2) patient-reported outcome, or (3) private phenomena (ie, phenomena only assessable by the patient). Of the 200 clinical trial reports, 12 used the term “subjective” and/or “objective” about outcomes, but no clinical trial reports explicitly defined the terms. The terms “subjective” and “objective” are ambiguous when used to describe outcomes in randomized clinical trials. We suggest that the terms should be defined explicitly when used in connection with the assessment of risk of bias in a clinical trial, in metaepidemiological research, and generally in the reporting of clinical trials. We also suggest that adding an explicit clarification of the terms in future versions of the Cochrane Handbook might further strengthen its important role in guiding review authors.

Background: The Inuit have gone through an accelerated process of modernization especially since 1950. Primarily because of the dietary transition, westernisation is expected to influence the Inuit's metabolic risk in a negative way with respect to cardiovascular risk. The aim was to analyze metabolic risk factors among Inuit in Greenland and Denmark and their relation to westernization. Methods: 1173 adult Inuit participated in a health survey in Greenland and Denmark. The examination included a 75 g OGTT. BMI, waist-to-hip ratio, and blood pressure were measured. P-glucose, s-insulin, lipids and urine-albumin/creatinine ratio were analysed. Westernization was estimated by place of residence and language. Results: The prevalence of the metabolic syndrome was 20.3% among men and 19.5% among women (p = 0.73). The association between the metabolic syndrome and westernization was different for men and women. For men there was an increase in prevalence of the metabolic syndrome with westernization within Greenland, but the variation was less pronounced than the difference between the migrants and the Inuit in Greenland. Age, family history of diabetes, and non-smoking were directly associated with the metabolic syndrome, whereas high physical activity was negatively associated with the metabolic syndrome. For women there was a significant negative association between westernization and the metabolic syndrome among the three population groups in Greenland, whereas the prevalence was not significantly lower among female migrants compared with Inuit women in Greenland. Age, family history of diabetes, non-smoking, and low education were associated with the metabolic syndrome. Conclusions: The effect of westernization on metabolic risk was different for men and women. For men physical inactivity due to a decrease in subsistence hunting and fishing seems to increase the metabolic risk; for women higher education is associated with a more favorable risk profile.