Comparing evidence of selection bias between cluster-randomised and individually randomised controlled trials: a systematic review and meta-analysis

Bolzern, Jaime; Mnyama, Nandi; Bosanquet, Kate; Torgerson, David

doi:10.1016/s0140-6736(18)32871-x

Cited by 2 publications

(3 citation statements)

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“…We observed here that chance imbalances between key risk variables decreased over time (i.e. as sample size increased); this has been previously observed in meta-analyses of cRCTs [ 21 ] which suggests that patient-level imbalance is expected in cRCTs.…”

Section: Discussionsupporting

confidence: 82%

Strategies to minimise and monitor biases and imbalances by arm in surgical cluster randomised trials: evidence from ChEETAh, a trial in seven low- and middle-income countries

Ahogni¹,

Ahounou²,

Boukari³

et al. 2023

Trials

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Background Cluster randomised controlled trials (cRCT) present challenges regarding risks of bias and chance imbalances by arm. This paper reports strategies to minimise and monitor biases and imbalances in the ChEETAh cRCT. Methods ChEETAh was an international cRCT (hospitals as clusters) evaluating whether changing sterile gloves and instruments prior to abdominal wound closure reduces surgical site infection at 30 days postoperative. ChEETAh planned to recruit 12,800 consecutive patients from 64 hospitals in seven low-middle income countries. Eight strategies to minimise and monitor bias were pre-specified: (1) minimum of 4 hospitals per country; (2) pre-randomisation identification of units of exposure (operating theatres, lists, teams or sessions) within clusters; (3) minimisation of randomisation by country and hospital type; (4) site training delivered after randomisation; (5) dedicated ‘warm-up week’ to train teams; (6) trial specific sticker and patient register to monitor consecutive patient identification; (7) monitoring characteristics of patients and units of exposure; and (8) low-burden outcome-assessment. Results This analysis includes 10,686 patients from 70 clusters. The results aligned to the eight strategies were (1) 6 out of 7 countries included ≥ 4 hospitals; (2) 87.1% (61/70) of hospitals maintained their planned operating theatres (82% [27/33] and 92% [34/37] in the intervention and control arms); (3) minimisation maintained balance of key factors in both arms; (4) post-randomisation training was conducted for all hospitals; (5) the ‘warm-up week’ was conducted at all sites, and feedback used to refine processes; (6) the sticker and trial register were maintained, with an overall inclusion of 98.1% (10,686/10,894) of eligible patients; (7) monitoring allowed swift identification of problems in patient inclusion and key patient characteristics were reported: malignancy (20.3% intervention vs 12.6% control), midline incisions (68.4% vs 58.9%) and elective surgery (52.4% vs 42.6%); and (8) 0.4% (41/9187) of patients refused consent for outcome assessment. Conclusion cRCTs in surgery have several potential sources of bias that include varying units of exposure and the need for consecutive inclusion of all eligible patients across complex settings. We report a system that monitored and minimised the risks of bias and imbalances by arm, with important lessons for future cRCTs within hospitals.

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Section: Discussionsupporting

confidence: 82%

Strategies to minimise and monitor biases and imbalances by arm in surgical cluster randomised trials: evidence from ChEETAh, a trial in seven low- and middle-income countries

Ahogni¹,

Ahounou²,

Boukari³

et al. 2023

Trials

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“…error" overestimating treatment effect size, 24 risk of imbalanced participant characteristics at baseline 25 and risk of unequal cluster size leading to reduced statistical power. 10 Although these issues were listed and discussed by experts, they were not considered as being the most impactful; moreover, these issues are specific to CRTs.…”

Section: Key Resultsmentioning

confidence: 99%

“…In the present study, the experts also considered post‐randomization recruitment in CRTs as being critical. Previous studies reported other issues specific to CRTs: intra‐cluster correlation, 11 “unit‐of‐analysis error” overestimating treatment effect size, 24 risk of imbalanced participant characteristics at baseline 25 and risk of unequal cluster size leading to reduced statistical power 10 . Although these issues were listed and discussed by experts, they were not considered as being the most impactful; moreover, these issues are specific to CRTs.…”

Section: Discussionmentioning

confidence: 99%

A first step towards best practice recommendations for the design and statistical analyses of pragmatic clinical trials: A modified Delphi approach

Palin

Staa

Steels

et al. 2022

Brit J Clinical Pharma

Self Cite

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Aim Pragmatic clinical trials (PCTs) are randomized trials implemented through routine clinical practice, where design parameters of traditional randomized controlled trials are modified to increase generalizability. However, this may introduce statistical challenges. We aimed to identify these challenges and discuss possible solutions leading to best practice recommendations for the design and analysis of PCTs. Methods A modified Delphi method was used to reach consensus among a panel of 11 experts in clinical trials and statistics. Statistical issues were identified in a focused literature review and aggregated with insights and possible solutions from experts collected through a series of survey iterations. Issues were ranked according to their importance. Results Twenty‐seven articles were included and combined with experts' insight to generate a list of issues categorized into participants, recruiting sites, randomization, blinding and intervention, outcome (selection and measurement) and data analysis. Consensus was reached about the most important issues: risk of participants' attrition, heterogeneity of “usual care” across sites, absence of blinding, use of a subjective endpoint and data analysis aligned with the trial estimand. Potential issues should be anticipated and preferably be addressed in the trial protocol. The experts provided solutions regarding data collection and data analysis, which were considered of equal importance. Discussion A set of important statistical issues in PCTs was identified and approaches were suggested to anticipate and/or minimize these through data analysis. Any impact of choosing a pragmatic design feature should be gauged in the light of the trial estimand.

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Comparing evidence of selection bias between cluster-randomised and individually randomised controlled trials: a systematic review and meta-analysis

Cited by 2 publications

References 0 publications

Strategies to minimise and monitor biases and imbalances by arm in surgical cluster randomised trials: evidence from ChEETAh, a trial in seven low- and middle-income countries

Strategies to minimise and monitor biases and imbalances by arm in surgical cluster randomised trials: evidence from ChEETAh, a trial in seven low- and middle-income countries

A first step towards best practice recommendations for the design and statistical analyses of pragmatic clinical trials: A modified Delphi approach

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