scholarly journals Blinding, sham, and treatment effects in randomized controlled trials for back pain in 2000–2019: A review and meta-analytic approach

2021 ◽  
pp. 174077452098487
Author(s):  
Brian Freed ◽  
Brian Williams ◽  
Xiaolu Situ ◽  
Victoria Landsman ◽  
Jeehyoung Kim ◽  
...  
Keyword(s):  
Back Pain ◽  
Active Treatment ◽  
Treatment Effect ◽  
Effect Size ◽  
Treatment Effects ◽  
Effect Sizes ◽  
Controlled Trials ◽  
Sham Treatment ◽  
Randomized Controlled ◽  
Random Guess

Background: Blinding aims to minimize biases from what participants and investigators know or believe. Randomized controlled trials, despite being the gold standard to evaluate treatment effect, do not generally assess the success of blinding. We investigated the extent of blinding in back pain trials and the associations between participant guesses and treatment effects. Methods: We did a review with PubMed/OvidMedline, 2000–2019. Eligibility criteria were back pain trials with data available on treatment effect and participants’ guess of treatment. For blinding, blinding index was used as chance-corrected measure of excessive correct guess (0 for random guess). For treatment effects, within- or between-arm effect sizes were used. Analyses of investigators’ guess/blinding or by treatment modality were performed exploratorily. Results: Forty trials (3899 participants) were included. Active and sham treatment groups had mean blinding index of 0.26 (95% confidence interval: 0.12, 0.41) and 0.01 (−0.11, 0.14), respectively, meaning 26% of participants in active treatment believed they received active treatment, whereas only 1% in sham believed they received sham treatment, beyond chance, that is, random guess. A greater belief of receiving active treatment was associated with a larger within-arm effect size in both arms, and ideal blinding (namely, “random guess,” and “wishful thinking” that signifies both groups believing they received active treatment) showed smaller effect sizes, with correlation of effect size and summary blinding indexes of 0.35 ( p = 0.028) for between-arm comparison. We observed uniformly large sham treatment effects for all modalities, and larger correlation for investigator’s (un)blinding, 0.53 ( p = 0.046). Conclusion: Participants in active treatments in back pain trials guessed treatment identity more correctly, while those in sham treatments tended to display successful blinding. Excessive correct guesses (that could reflect weaker blinding and/or noticeable effects) by participants and investigators demonstrated larger effect sizes. Blinding and sham treatment effects on back pain need due consideration in individual trials and meta-analyses.

scholarly journals Guided Web-Based Cognitive Behavior Therapy for Perfectionism: Results From Two Different Randomized Controlled Trials (Preprint)

2018 ◽  
Author(s):  
Alexander Rozental ◽  
Roz Shafran ◽  
Tracey D Wade ◽  
Radha Kothari ◽  
Sarah J Egan ◽  
...  
Keyword(s):  
Cognitive Behavioral Therapy ◽  
Effect Size ◽  
Behavioral Therapy ◽  
Cognitive Behavioral ◽  
Effect Sizes ◽  
Controlled Trials ◽  
Intention To Treat ◽  
Randomized Controlled ◽  
The Uk

BACKGROUND Perfectionism can become a debilitating condition that may negatively affect functioning in multiple areas, including mental health. Prior research has indicated that internet-based cognitive behavioral therapy can be beneficial, but few studies have included follow-up data. OBJECTIVE The objective of this study was to explore the outcomes at follow-up of internet-based cognitive behavioral therapy with guided self-help, delivered as 2 separate randomized controlled trials conducted in Sweden and the United Kingdom. METHODS In total, 120 participants randomly assigned to internet-based cognitive behavioral therapy were included in both intention-to-treat and completer analyses: 78 in the Swedish trial and 62 in the UK trial. The primary outcome measure was the Frost Multidimensional Perfectionism Scale, Concern over Mistakes subscale (FMPS CM). Secondary outcome measures varied between the trials and consisted of the Clinical Perfectionism Questionnaire (CPQ; both trials), the 9-item Patient Health Questionnaire (PHQ-9; Swedish trial), the 7-item Generalized Anxiety Disorder scale (GAD-7; Swedish trial), and the 21-item Depression Anxiety Stress Scale (DASS-21; UK trial). Follow-up occurred after 6 months for the UK trial and after 12 months for the Swedish trial. RESULTS Analysis of covariance revealed a significant difference between pretreatment and follow-up in both studies. Intention-to-treat within-group Cohen d effect sizes were 1.21 (Swedish trial; 95% CI 0.86-1.54) and 1.24 (UK trial; 95% CI 0.85-1.62) for the FMPS CM. Furthermore, 29 (59%; Swedish trial) and 15 (43%; UK trial) of the participants met the criteria for recovery on the FMPS CM. Improvements were also significant for the CPQ, with effect sizes of 1.32 (Swedish trial; 95% CI 0.97-1.66) and 1.49 (UK trial; 95% CI 1.09-1.88); the PHQ-9, effect size 0.60 (95% CI 0.28-0.92); the GAD-7, effect size 0.67 (95% CI 0.34-0.99); and the DASS-21, effect size 0.50 (95% CI 0.13-0.85). CONCLUSIONS The results are promising for the use of internet-based cognitive behavioral therapy as a way of targeting perfectionism, but the findings need to be replicated and include a comparison condition.

scholarly journals Hierarchical Bayes Approach to Estimate the Treatment Effect for Randomized Controlled Trials

2020 ◽  
Vol 80 (6) ◽  
pp. 1090-1114
Author(s):  
Xinya Liang ◽  
Akihito Kamata ◽  
Ji Li
Keyword(s):  
Treatment Effect ◽  
Effect Size ◽  
Empirical Bayes ◽  
Hierarchical Bayes ◽  
Effect Sizes ◽  
Sample Treatment ◽  
Data Set ◽  
Randomized Controlled ◽  
Empirical Bayes Approach ◽  
Bayes Approach

One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance hyperparameters for estimating the treatment effect in a two-group randomized controlled trial. Assuming a random sample of treatment effect sizes is obtained from past studies, the hyper priors can be constructed based on the sampling distributions of the effect size mean and precision. The performance of the hierarchical Bayes approach was compared with the empirical Bayes approach (hyperparameters are fixed values or point estimates) and the ordinary least squares (OLS) method via simulation. The design factors for data generation included the sample treatment effect size, treatment/control group size ratio, and sample size. Each generated data set was analyzed using the hierarchical Bayes approach with three hyper priors, the empirical Bayes approach with twelve priors (including correct and inaccurate priors), and the OLS method. Results indicated that the proposed hierarchical Bayes approach generally outperformed the empirical Bayes approach and the OLS method, especially with small samples. When more sample effect sizes were available, the treatment effect was estimated more accurately regardless of the sample sizes. Practical implications and future research directions are discussed.

scholarly journals Empirical Evidence of an Association Between Internal Validity and Effect Size in Randomized Controlled Trials of Low-Back Pain

Spine ◽  
2009 ◽  
Vol 34 (16) ◽  
pp. 1685-1692 ◽  
Author(s):  
Maurits W. van Tulder ◽  
Marika Suttorp ◽  
Sally Morton ◽  
Lex M. Bouter ◽  
Paul Shekelle
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Randomized Controlled Trials ◽  
Empirical Evidence ◽  
Effect Size ◽  
Internal Validity ◽  
Controlled Trials ◽  
Low Back ◽  
Randomized Controlled

scholarly journals Yoga for Chronic Low Back Pain: A Meta-Analysis of Randomized Controlled Trials

2013 ◽  
Vol 18 (5) ◽  
pp. 267-272 ◽  
Author(s):  
Susan Holtzman ◽  
R Thomas Beggs
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Chronic Low Back Pain ◽  
Functional Disability ◽  
Post Treatment ◽  
Effect Sizes ◽  
Controlled Trials ◽  
Low Back ◽  
Randomized Controlled

OBJECTIVES: To evaluate the efficacy of yoga as an intervention for chronic low back pain (CLBP) using a meta-analytical approach. Randomized controlled trials (RCTs) that examined pain and/or functional disability as treatment outcomes were included. Post-treatment and follow-up outcomes were assessed.METHODS: A comprehensive search of relevant electronic databases, from the time of their inception until November 2011, was conducted. Cohen’s d effect sizes were calculated and entered in a random-effects model.RESULTS: Eight RCTs met the criteria for inclusion (eight assessing functional disability and five assessing pain) and involved a total of 743 patients. At post-treatment, yoga had a medium to large effect on functional disability (d=0.645) and pain (d=0.623). Despite a wide range of yoga styles and treatment durations, heterogeneity in post-treatment effect sizes was low. Follow-up effect sizes for functional disability and pain were smaller, but remained significant (d=0.397 and d=0.486, respectively); however, there was a moderate to high level of variability in these effect sizes.DISCUSSION: The results of the present study indicate that yoga may be an efficacious adjunctive treatment for CLBP. The strongest and most consistent evidence emerged for the short-term benefits of yoga on functional disability. However, before any definitive conclusions can be drawn, there are a number of methodological concerns that need to be addressed. In particular, it is recommended that future RCTs include an active control group to determine whether yoga has specific treatment effects and whether yoga offers any advantages over traditional exercise programs and other alternative therapies for CLBP.

Statistical Power of Negative Randomized Controlled Trials Presented at American Society for Clinical Oncology Annual Meetings

2007 ◽  
Vol 25 (23) ◽  
pp. 3482-3487 ◽  
Author(s):  
Philippe L. Bedard ◽  
Monika K. Krzyzanowska ◽  
Melania Pintilie ◽  
Ian F. Tannock
Keyword(s):  
Sample Size ◽  
Effect Size ◽  
Statistical Power ◽  
Effect Sizes ◽  
Controlled Trials ◽  
Time To Event ◽  
Randomized Controlled ◽  
American Society ◽  
Post Hoc ◽  
Adequate Sample Size

Purpose To investigate the prevalence of underpowered randomized controlled trials (RCTs) presented at American Society of Clinical Oncology (ASCO) annual meetings. Methods We surveyed all two-arm phase III RCTs presented at ASCO annual meetings from 1995 to 2003 for which negative results were obtained. Post hoc calculations were performed using a power of 80% and an α level of .05 (two sided) to determine sample sizes required to detect small, medium, and large effect sizes. For studies reporting a proportion or time-to-event as primary end point, effect size was expressed as an odds ratio (OR) or hazard ratio (HR), respectively, with a small effect size defined as OR/HR ≥ 1.3, medium effect size defined as OR/HR ≥ 1.5, and large effect size defined as OR/HR ≥ 2.0. Logistic regression was used to identify factors associated with lack of statistical power. Results Of 423 negative RCTs for which post hoc sample size calculations could be performed, 45 (10.6%), 138 (32.6%), and 233 (55.1%) had adequate sample size to detect small, medium, and large effect sizes, respectively. Only 35 negative RCTs (7.1%) reported a reason for inadequate sample size. In a multivariable model, studies that were presented at oral sessions (P = .0038), multicenter studies supported by a cooperative group (P < .0001), and studies with time to event as primary outcome (P < .0001) were more likely to have adequate sample size. Conclusion More than half of negative RCTs presented at ASCO annual meetings do not have an adequate sample to detect a medium-size treatment effect.

scholarly journals MO256THE TREATMENT EFFECT OF RAS BLOCKADE ON PROTEINURIA IN IGA NEPHROPATHY PATIENTS AS A SURROGATE FOR RENAL EVENTS AND DECLINE IN EGFR: AN ANALYSIS OF RANDOMIZED CONTROLLED TRIALS

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Alex Mercer ◽  
Kevin Carroll ◽  
Leah Conley ◽  
Jonathan Barratt
Keyword(s):  
Renal Failure ◽  
Treatment Effect ◽  
Treatment Effects ◽  
Regression Line ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Slope Estimate ◽  
Level Data ◽  
Meta Regression

Abstract Background and Aims Renin-Angiotensin System Blockade (RASB) is the cornerstone of standard-of-care in IgA nephropathy. Randomized controlled trials (RCTs) have shown the treatment benefit of RASB therapy on proteinuria and risk of renal failure. The objective of this study was to describe the relationships between the treatment effect of RASB on proteinuria and (i) risk of renal events, and (ii) decline in eGFR, as an endpoint proximal to renal failure. To this aim, trial level (TL) and simple weighted linear regression (SWR) analyses were conducted on RCTs identified through a systematic literature review, with RASB as the active intervention. Methods A systematic literature review of available peer-reviewed literature from 1990 to 2020 was performed applying the following inclusion criteria: RCT in patients with biopsy-proven IgAN, investigating the effects of RASB as an intervention, sample size &gt;25, measurement of proteinuria at baseline and at &gt;3 months. At least 1 renal event (defined as ≥50% decline in eGFR, CKD Stage 5, dialysis or transplantation) was required for the renal event analysis and similarly, at least 12 months follow-up was required for the decline in eGFR analysis. For the relationship between proteinuria and risk of renal events, 4 studies including 5 comparisons were identified, while 9 studies including 10 comparisons were identified for the analysis of proteinuria vs eGFR decline. Proteinuria change from baseline was calculated from the value closest to 6 months. If annualized change in eGFR was reported, these data were used, otherwise annualized change in eGFR was calculated per year of follow-up. Methods as described by Burzykoski & Buyse (2006) and Joffe & Greene (2008) were used for TL meta-regression analyses; the resulting meta-regression line was displayed with an 80% credible interval band (CB). Given the assumptions made in this analysis, a SWR analysis was also performed; to compensate for potential underestimation of error associated with the regression line, a 99.9% CB was applied in the SWR analysis. Results For RASB treatment effects on renal events, a statistical association was found with treatment effects on proteinuria with a TL slope estimate = 15.30 95% CI (0.57, 38.79), R2 = 0.88 95% CI (0.22, 1.00); using the lower CI of 0.75 for the estimated slope, a 30% treatment effect on proteinuria would be expected to result in at least a 25% reduction in the risk of renal events. As individual subject level data were not available, the correlation between errors on treatment effects for proteinuria and treatment effects for renal events were unknown, resulting in a wide CB on the meta-regression line and a wide CI for the slope estimate. The SWR approach is not hampered by lack of subject level data and gave a slope estimate of 3.5 95% CI (2.1, 5.0) with R2 = 0.97, such that a 30% treatment effect on proteinuria would be expected to result in at least a 64% reduction in the risk of renal events. For treatment effects on annualized eGFR versus effects on proteinuria, the TL slope estimate was -5.1 95% CI (-30.2, 35.0), R2 = 0.89 95% CI (0.15, 1.00); the corresponding SWR slope estimate was -7.6, 95% CI (-12.3, -2.8) with R2 = 0.71. A 30% treatment effect on proteinuria would be expected to result in a 2.6 mL/min (TL analysis) to 3.9 mL/min slower decline (SWR analysis) in annualized eGFR. Conclusion In patients with IgAN, associations were seen between treatment effects of RASB on proteinuria and on the clinically relevant endpoints of renal events and annualized change in eGFR. Consistent with TL analyses of RCTs across a variety of mechanisms of actions, these data, specific to RASB, contribute to the growing evidence base supporting the use of proteinuria as a valid surrogate endpoint in IgAN.

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