Dataset Information

Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study.

ABSTRACT: OBJECTIVE: To examine whether deviation from the standard intention to treat analysis has an influence on treatment effect estimates of randomised trials. DESIGN: Meta-epidemiological study. DATA SOURCES: Medline, via PubMed, searched between 2006 and 2010; 43 systematic reviews of interventions and 310 randomised trials were included. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: From each year searched, random selection of 5% of intervention reviews with a meta-analysis that included at least one trial that deviated from the standard intention to treat approach. Basic characteristics of the systematic reviews and randomised trials were extracted. Information on the reporting of intention to treat analysis, outcome data, risk of bias items, post-randomisation exclusions, and funding were extracted from each trial. Trials were classified as: ITT (reporting the standard intention to treat approach), mITT (reporting a deviation from the standard approach), and no ITT (reporting no approach). Within each meta-analysis, treatment effects were compared between mITT and ITT trials, and between mITT and no ITT trials. The ratio of odds ratios was calculated (value <1 indicated larger treatment effects in mITT trials than in other trial categories). RESULTS: 50 meta-analyses and 322 comparisons of randomised trials (from 84 ITT trials, 118 mITT trials, and 108 no ITT trials; 12 trials contributed twice to the analysis) were examined. Compared with ITT trials, mITT trials showed a larger intervention effect (pooled ratio of odds ratios 0.83 (95% confidence interval 0.71 to 0.96), P=0.01; between meta-analyses variance ?(2)=0.13). Adjustments for sample size, type of centre, funding, items of risk of bias, post-randomisation exclusions, and variance of log odds ratio yielded consistent results (0.80 (0.69 to 0.94), P=0.005; ?(2)=0.08). After exclusion of five influential studies, results remained consistent (0.85 (0.75 to 0.98); ?(2)=0.08). The comparison between mITT trials and no ITT trials showed no statistical difference between the two groups (adjusted ratio of odds ratios 0.92 (0.70 to 1.23); ?(2)=0.57). CONCLUSIONS: Trials that deviated from the intention to treat analysis showed larger intervention effects than trials that reported the standard approach. Where an intention to treat analysis is impossible to perform, authors should clearly report who is included in the analysis and attempt to perform multiple imputations.

SUBMITTER: Abraha I

PROVIDER: S-EPMC4445790 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study.

Abraha Iosief I Cherubini Antonio A Cozzolino Francesco F De Florio Rita R Luchetta Maria Laura ML Rimland Joseph M JM Folletti Ilenia I Marchesi Mauro M Germani Antonella A Orso Massimiliano M Eusebi Paolo P Montedori Alessandro A

BMJ (Clinical research ed.) 20150527

<h4>Objective</h4>To examine whether deviation from the standard intention to treat analysis has an influence on treatment effect estimates of randomised trials.<h4>Design</h4>Meta-epidemiological study.<h4>Data sources</h4>Medline, via PubMed, searched between 2006 and 2010; 43 systematic reviews of interventions and 310 randomised trials were included.<h4>Eligibility criteria for selecting studies</h4>From each year searched, random selection of 5% of intervention reviews with a meta-analysis ...[more]

PMID: 26016488

Similar Datasets

Project description:ObjectivesTo determine the incidence and characteristics of randomised controlled trials that report using the modified intention to treat approach, and how the approach is described.DesignSystematic review.Data sourcesPubMed, Embase, Cochrane central register of controlled trials, ISI Web of Knowledge, Ovid, HighWire Press, Science-Direct, Ingenta, Medscape, BioMed Central, Springer, and Wiley, from inception to December 2006.Main outcome measuresIncidence of trials in which use of modified intention to treat was reported, and how the approach was described (classified according to the type and number of deviations from the intention to treat approach).Results475 randomised controlled trials reported use of a modified intention to treat analysis. Of these, 76 (16%) were published in five highly cited general medical journals. The incidence of all trials that reported use of modified intention to treat published in journals indexed in Medline increased from 0.006% in 1982-6 to 0.5% in 2002-6 (P<0.001 for linear trend). When the description of the modified intention to treat was examined in each trial, 192 (40%) reported one type of deviation from the intention to treat approach, 261 (55%) reported two or more types, and 22 (5%) did not describe any type. In 266 (56%) of the trials the deviation was related to the treatment received, in 196 (41%) to a post baseline assessment, in 118 (25%) to a baseline assessment, in 108 (23%) to a target condition, and in 23 (5%) to follow-up. Post-randomisation exclusions occurred in 380 (80%) trials. The results reported by 270 of the 352 (77%) superiority trials favoured the drug under investigation. All of the 123 trials using equivalence or non-inferiority methods to investigate interventions reported results that favoured their assumptions.ConclusionsRandomised controlled trials that report using a modified intention to treat are increasingly being published in the medical literature. The descriptions of such an approach were ambiguous, and may cover any type of descriptions for exclusion, such as missing data and deviation from protocol. Explicit statements about post-randomisation exclusions should replace the ambiguous terminology of modified intention to treat.

Project description:IntroductionMeta-epidemiological studies examining the influence of methodological characteristics, such as allocation concealment and intention-to-treat analysis have been performed in a large number of healthcare areas. However, there are no studies investigating these characteristics in physical therapy interventions for patients with low back pain. The aim of this study is to investigate the influence of allocation concealment and the use of intention-to-treat analysis on estimates of treatment effects of physical therapy interventions in low back pain clinical trials.Methods and analysisSearches on PubMed, Embase, Cochrane Database of Systematic Reviews, Physiotherapy Evidence Database (PEDro) and CINAHL databases will be performed. We will search for systematic reviews that include a meta-analysis of randomised controlled trials that compared physical therapy interventions in patients with low back pain with placebo or no intervention, and have pain intensity or disability as the primary outcomes. Information about selection (allocation concealment) and attrition bias (intention-to-treat analysis) will be extracted from the PEDro database for each included trial. Information about bibliographic data, study characteristics, participants' characteristics and study results will be extracted. A random-effects model will be used to provide separate estimates of treatment effects for trials with and without allocation concealment and with and without intention-to-treat analysis (eg, four estimates). A meta-regression will be performed to measure the association between methodological features and treatment effects from each trial. The dependent variable will be the treatment effect (the mean between-group differences) for the primary outcomes (pain or disability), while the independent variables will be the methodological features of interest (allocation concealment and intention-to-treat analysis). Other covariates will include sample size and sequence generation.Ethics and disseminationNo ethical approval will be required for this study. The study findings will be published in a peer-reviewed journal and presented at international conferences.Registration numberInternational Prospective Register of Systematic Reviews (CRD42016052347).

Project description:ObjectiveTo assess the influence of trial sample size on treatment effect estimates within meta-analyses.DesignMeta-epidemiological study.Data sources93 meta-analyses (735 randomised controlled trials) assessing therapeutic interventions with binary outcomes, published in the 10 leading journals of each medical subject category of the Journal Citation Reports or in the Cochrane Database of Systematic Reviews.Data extractionSample size, outcome data, and risk of bias extracted from each trial.Data synthesisTrials within each meta-analysis were sorted by their sample size: using quarters within each meta-analysis (from quarter 1 with 25% of the smallest trials, to quarter 4 with 25% of the largest trials), and using size groups across meta-analyses (ranging from <50 to ≥ 1000 patients). Treatment effects were compared within each meta-analysis between quarters or between size groups by average ratios of odds ratios (where a ratio of odds ratios less than 1 indicates larger effects in smaller trials).ResultsTreatment effect estimates were significantly larger in smaller trials, regardless of sample size. Compared with quarter 4 (which included the largest trials), treatment effects were, on average, 32% larger in trials in quarter 1 (which included the smallest trials; ratio of odds ratios 0.68, 95% confidence interval 0.57 to 0.82), 17% larger in trials in quarter 2 (0.83, 0.75 to 0.91), and 12% larger in trials in quarter 3 (0.88, 0.82 to 0.95). Similar results were obtained when comparing treatment effect estimates between different size groups. Compared with trials of 1000 patients or more, treatment effects were, on average, 48% larger in trials with fewer than 50 patients (0.52, 0.41 to 0.66) and 10% larger in trials with 500-999 patients (0.90, 0.82 to 1.00).ConclusionsTreatment effect estimates differed within meta-analyses solely based on trial sample size, with stronger effect estimates seen in small to moderately sized trials than in the largest trials.

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:ObjectiveTo quantify and compare the treatment effect and risk of bias of trials reporting biomarkers or intermediate outcomes (surrogate outcomes) versus trials using final patient relevant primary outcomes.DesignMeta-epidemiological study.Data sourcesAll randomised clinical trials published in 2005 and 2006 in six high impact medical journals: Annals of Internal Medicine, BMJ, Journal of the American Medical Association, Lancet, New England Journal of Medicine, and PLoS Medicine.Study selectionTwo independent reviewers selected trials.Data extractionTrial characteristics, risk of bias, and outcomes were recorded according to a predefined form. Two reviewers independently checked data extraction. The ratio of odds ratios was used to quantify the degree of difference in treatment effects between the trials using surrogate outcomes and those using patient relevant outcomes, also adjusted for trial characteristics. A ratio of odds ratios >1.0 implies that trials with surrogate outcomes report larger intervention effects than trials with patient relevant outcomes.Results84 trials using surrogate outcomes and 101 using patient relevant outcomes were considered for analyses. Study characteristics of trials using surrogate outcomes and those using patient relevant outcomes were well balanced, except for median sample size (371 v 741) and single centre status (23% v 9%). Their risk of bias did not differ. Primary analysis showed trials reporting surrogate endpoints to have larger treatment effects (odds ratio 0.51, 95% confidence interval 0.42 to 0.60) than trials reporting patient relevant outcomes (0.76, 0.70 to 0.82), with an unadjusted ratio of odds ratios of 1.47 (1.07 to 2.01) and adjusted ratio of odds ratios of 1.46 (1.05 to 2.04). This result was consistent across sensitivity and secondary analyses.ConclusionsTrials reporting surrogate primary outcomes are more likely to report larger treatment effects than trials reporting final patient relevant primary outcomes. This finding was not explained by differences in the risk of bias or characteristics of the two groups of trials.

Project description:ObjectiveTo compare treatment effects from randomised trials conducted in more developed versus less developed countries.DesignMeta-epidemiological study.Data sourcesCochrane Database of Systematic Reviews (August 2012).Data extractionMeta-analyses with mortality outcomes including data from at least one randomised trial conducted in a less developed country and one in a more developed country. Relative risk estimates of more versus less developed countries were compared by calculating the relative relative risks for each topic and the summary relative relative risks across all topics. Similar analyses were performed for the primary binary outcome of each topic.Results139 meta-analyses with mortality outcomes were eligible. No nominally significant differences between more developed and less developed countries were found for 128 (92%) meta-analyses. However, differences were beyond chance in 11 (8%) cases, always showing more favourable treatment effects in trials from less developed countries. The summary relative relative risk was 1.12 (95% confidence interval 1.06 to 1.18; P<0.001; I(2)=0%), suggesting significantly more favourable mortality effects in trials from less developed countries. Results were similar for meta-analyses with nominally significant treatment effects for mortality (1.15), meta-analyses with recent trials (1.14), and when excluding trials from less developed countries that subsequently became more developed (1.12). For the primary binary outcomes (127 meta-analyses), 20 topics had differences in treatment effects beyond chance (more favourable in less developed countries in 15/20 cases).ConclusionsTrials from less developed countries in a few cases show significantly more favourable treatment effects than trials in more developed countries and, on average, treatment effects are more favourable in less developed countries. These discrepancies may reflect biases in reporting or study design as well as genuine differences in baseline risk or treatment implementation and should be considers when generalising evidence across different settings.

Project description:IntroductionIt is fundamental that randomised controlled trials (RCTs) are properly conducted in order to reach well-supported conclusions. However, there is emerging evidence that RCTs are subject to biases which can overestimate or underestimate the true treatment effect, due to flaws in the study design characteristics of such trials. The extent to which this holds true in oral health RCTs, which have some unique design characteristics compared to RCTs in other health fields, is unclear. As such, we aim to examine the empirical evidence quantifying the extent of bias associated with methodological and non-methodological characteristics in oral health RCTs.Methods and analysisWe plan to perform a meta-epidemiological study, where a sample size of 60 meta-analyses (MAs) including approximately 600 RCTs will be selected. The MAs will be randomly obtained from the Oral Health Database of Systematic Reviews using a random number table; and will be considered for inclusion if they include a minimum of five RCTs, and examine a therapeutic intervention related to one of the recognised dental specialties. RCTs identified in selected MAs will be subsequently included if their study design includes a comparison between an intervention group and a placebo group or another intervention group. Data will be extracted from selected trials included in MAs based on a number of methodological and non-methodological characteristics. Moreover, the risk of bias will be assessed using the Cochrane Risk of Bias tool. Effect size estimates and measures of variability for the main outcome will be extracted from each RCT included in selected MAs, and a two-level analysis will be conducted using a meta-meta-analytic approach with a random effects model to allow for intra-MA and inter-MA heterogeneity.Ethics and disseminationThe intended audiences of the findings will include dental clinicians, oral health researchers, policymakers and graduate students. The aforementioned will be introduced to the findings through workshops, seminars, round table discussions and targeted individual meetings. Other opportunities for knowledge transfer will be pursued such as key dental conferences. Finally, the results will be published as a scientific report in a dental peer-reviewed journal.

Project description:Objective To examine whether a very large effect (VLE; defined as a relative risk of ?0.2 or ?5) in a randomised trial could be an empirical marker that subsequent trials are unnecessary.Design Meta-epidemiological assessment of existing published data on randomised trials.Data sources Cochrane Database of Systematic Reviews (2010, issue 7) with data on subsequent large trials updated to 2015, issue 12.Eligibility criteria All binary outcome forest plots were selected, which contained an index randomised trial with a VLE that was nominally statistically significant (P<0.05), included a subsequent large randomised trial (?200 events and ?200 non-events) for validation of the effect, assessed a primary outcome of the review, and was not a subgroup or sensitivity analysis.Results Of 3082 reviews yielding 85?002 forest plots, only 44 (0.05%) satisfied the inclusion criteria. Index trials were generally small, with a median sample of 99 (median 14 events). Few index trials were rated at low risk of bias (9 of 44; 20%). The relative risk was closer to the null in the subsequent large trials in 43 of 44 cases. Subsequent large trial data failed to find a statistically significant (P<0.05) effect in the same direction in 19 cases (43%, 95% confidence interval 29% to 58%). Even when the subsequent large trials did find a significant effect in the same direction, the additional primary outcomes in most of these trials would have to be considered before deciding in favour of using the intervention. Subsequent large trial data found a statistically significant effect in the same direction in 19 of 21 cases when the index trial also had a value of P<0.001.Conclusions The frequency of VLEs followed by a large trial is vanishingly small, and where they occur they do not appear to be a reliable marker for a benefit that is reproducible and directly actionable. An empirical rule using a VLE in a randomised controlled trial as a marker that further trials are unnecessary would be neither practical nor useful. Caution should be taken when interpreting small studies with very large treatment effects.

Dataset Information

Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study.

Publications

Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets