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Partially randomised patient preference trials as an alternative design to randomised controlled trials: systematic review and meta-analyses.

ABSTRACT: OBJECTIVE:Randomised controlled trials (RCT) are the gold standard to provide unbiased data. However, when patients have a treatment preference, randomisation may influence participation and outcomes (eg, external and internal validity). The aim of this study was to assess the influence of patients' preference in RCTs by analysing partially randomised patient preference trials (RPPT); an RCT and preference cohort combined. DESIGN:Systematic review and meta-analyses. DATA SOURCES:MEDLINE, Embase, PsycINFO and the Cochrane Library. ELIGIBILITY CRITERIA FOR SELECTING STUDIES:RPPTs published between January 2005 and October 2018 reporting on allocation of patients to randomised and preference cohorts were included. DATA EXTRACTION AND SYNTHESIS:Two independent reviewers extracted data. The main outcomes were the difference in external validity (participation and baseline characteristics) and internal validity (lost to follow-up, crossover and the primary outcome) between the randomised and the preference cohort within each RPPT, compared in a meta-regression using a Wald test. Risk of bias was not assessed, as no quality assessment for RPPTs has yet been developed. RESULTS:In total, 117 of 3734 identified articles met screening criteria and 44 were eligible (24 873 patients). The participation rate in RPPTs was >95% in 14 trials (range: 48%-100%) and the randomisation refusal rate was >50% in 26 trials (range: 19%-99%). Higher education, female, older age, race and prior experience with one treatment arm were characteristics of patients declining randomisation. The lost to follow-up and cross-over rate were significantly higher in the randomised cohort compared with the preference cohort. Following the meta-analysis, the reported primary outcomes were comparable between both cohorts of the RPPTs, mean difference 0.093 (95% CI -0.178 to 0.364, p=0.502). CONCLUSIONS:Patients' preference led to a substantial proportion of a specific patient group refusing randomisation, while it did not influence the primary outcome within an RPPT. Therefore, RPPTs could increase external validity without compromising the internal validity compared with RCTs. PROSPERO REGISTRATION NUMBER:CRD42019094438.

SUBMITTER: Wasmann KA

PROVIDER: S-EPMC6797441 | biostudies-other | 2019 Oct

REPOSITORIES: biostudies-other

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Partially randomised patient preference trials as an alternative design to randomised controlled trials: systematic review and meta-analyses.

Wasmann Karin A KA Wijsman Pieta P van Dieren Susan S Bemelman Willem W Buskens Christianne C

BMJ open 20191016 10

<h4>Objective</h4>Randomised controlled trials (RCT) are the gold standard to provide unbiased data. However, when patients have a treatment preference, randomisation may influence participation and outcomes (eg, external and internal validity). The aim of this study was to assess the influence of patients' preference in RCTs by analysing partially randomised patient preference trials (RPPT); an RCT and preference cohort combined.<h4>Design</h4>Systematic review and meta-analyses.<h4>Data source ...[more]

PMID: 31619428

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Project description:To compare the characteristics, quality and treatment effects of randomised clinical trials (RCTs) by individual patient data (IPD) availability, in trials eligible for 18 IPD meta-analyses (MA).Trial characteristics, risk of bias (RoB) and hazard ratio (HR) for overall survival were extracted from IPD-MA publications and/or RCTs publications. Data for the RoB assessment were extracted for a subset of 73 RCTs. Two investigators blinded to whether IPD was available or not evaluated the RoB for these trials. Treatment effects were compared using ratios of global HRs (RHRs) of IPD-unavailable trials and IPD-available trials. RHR were pooled using a fixed-effect model.We examined the IPD availability for each trial eligible for each IPD-MA; when the IPD was not available for a trial, we used information from published sources.We selected all published IPD-MAs conducted at Gustave Roussy and the RCTs eligible for each.349 RCTs (73?018 patients) from 18 MAs were eligible: 60 RCTs (5890 patients) had unavailable IPD and 289 RCTs (67?128 patients) had available IPD. The main reason for IPD unavailability was data loss by investigators. IPD-unavailable trials were smaller (p<0.001), more often monocentric (p<0.001) and non-international (p=0.0004) than IPD-available trials. Geographical areas differed (p=0.054) between IPD-unavailable IPD-available trials. RoB was higher in IPD-unavailable RCTs for random sequence generation (p=0.007) and allocation concealment (p=0.006). The HR and 95% confidence interval (CI) for overall survival were extractable from publications in 23/60 IPD-unavailable trials included in 10 different MAs. Treatment effects were significantly greater for IPD-unavailable trials compared with IPD-available trials (RHR=0.86 (95% CI 0.75 to 0.98)).IPD-unavailable RCTs were significantly different from IPD-available RCTs in terms of trial characteristics and were at greater RoB. IPD-unavailable RCTs had a significantly greater treatment effect.

Project description:OBJECTIVE:To assess the association between intake of non-sugar sweeteners (NSS) and important health outcomes in generally healthy or overweight/obese adults and children. DESIGN:Systematic review following standard Cochrane review methodology. DATA SOURCES:Medline (Ovid), Embase, Cochrane CENTRAL, WHO International Clinical Trials Registry Platform, Clinicaltrials.gov, and reference lists of relevant publications. ELIGIBILITY CRITERIA FOR SELECTING STUDIES:Studies including generally healthy adults or children with or without overweight or obesity were eligible. Included study designs allowed for a direct comparison of no intake or lower intake of NSS with higher NSS intake. NSSs had to be clearly named, the dose had to be within the acceptable daily intake, and the intervention duration had to be at least seven days. MAIN OUTCOME MEASURES:Body weight or body mass index, glycaemic control, oral health, eating behaviour, preference for sweet taste, cancer, cardiovascular disease, kidney disease, mood, behaviour, neurocognition, and adverse effects. RESULTS:The search resulted in 13?941 unique records. Of 56 individual studies that provided data for this review, 35 were observational studies. In adults, evidence of very low and low certainty from a limited number of small studies indicated a small beneficial effect of NSSs on body mass index (mean difference -0.6, 95% confidence interval -1.19 to -0.01; two studies, n=174) and fasting blood glucose (-0.16 mmol/L, -0.26 to -0.06; two, n=52). Lower doses of NSSs were associated with lower weight gain (-0.09 kg, -0.13 to -0.05; one, n=17?934) compared with higher doses of NSSs (very low certainty of evidence). For all other outcomes, no differences were detected between the use and non-use of NSSs, or between different doses of NSSs. No evidence of any effect of NSSs was seen on overweight or obese adults or children actively trying to lose weight (very low to moderate certainty). In children, a smaller increase in body mass index z score was observed with NSS intake compared with sugar intake (-0.15, -0.17 to -0.12; two, n=528, moderate certainty of evidence), but no significant differences were observed in body weight (-0.60 kg, -1.33 to 0.14; two, n=467, low certainty of evidence), or between different doses of NSSs (very low to moderate certainty). CONCLUSIONS:Most health outcomes did not seem to have differences between the NSS exposed and unexposed groups. Of the few studies identified for each outcome, most had few participants, were of short duration, and their methodological and reporting quality was limited; therefore, confidence in the reported results is limited. Future studies should assess the effects of NSSs with an appropriate intervention duration. Detailed descriptions of interventions, comparators, and outcomes should be included in all reports. SYSTEMATIC REVIEW REGISTRATION:Prospero CRD42017047668.

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Project description:BACKGROUND:In individually randomised trials we might expect interventions delivered in groups or by care providers to result in clustering of outcomes for participants treated in the same group or by the same care provider. In partially nested randomised controlled trials (pnRCTs) this clustering only occurs in one trial arm, commonly the intervention arm. It is important to measure and account for between-cluster variability in trial design and analysis. We compare analysis approaches for pnRCTs with continuous outcomes, investigating the impact on statistical inference of cluster sizes, coding of the non-clustered arm, intracluster correlation coefficient (ICCs), and differential variance between intervention and control arm, and provide recommendations for analysis. METHODS:We performed a simulation study assessing the performance of six analysis approaches for a two-arm pnRCT with a continuous outcome. These include: linear regression model; fully clustered mixed-effects model with singleton clusters in control arm; fully clustered mixed-effects model with one large cluster in control arm; fully clustered mixed-effects model with pseudo clusters in control arm; partially nested homoscedastic mixed effects model, and partially nested heteroscedastic mixed effects model. We varied the cluster size, number of clusters, ICC, and individual variance between the two trial arms. RESULTS:All models provided unbiased intervention effect estimates. In the partially nested mixed-effects models, methods for classifying the non-clustered control arm had negligible impact. Failure to account for even small ICCs resulted in inflated Type I error rates and over-coverage of confidence intervals. Fully clustered mixed effects models provided poor control of the Type I error rates and biased ICC estimates. The heteroscedastic partially nested mixed-effects model maintained relatively good control of Type I error rates, unbiased ICC estimation, and did not noticeably reduce power even with homoscedastic individual variances across arms. CONCLUSIONS:In general, we recommend the use of a heteroscedastic partially nested mixed-effects model, which models the clustering in only one arm, for continuous outcomes similar to those generated under the scenarios of our simulations study. However, with few clusters (3-6), small cluster sizes (5-10), and small ICC (?0.05) this model underestimates Type I error rates and there is no optimal model.

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Partially randomised patient preference trials as an alternative design to randomised controlled trials: systematic review and meta-analyses.

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Partially randomised patient preference trials as an alternative design to randomised controlled trials: systematic review and meta-analyses.

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