Fig 1.
Conceptual framework that underlies the Cochrane risk of bias tool for RCTs.
Letters A-E denote the sources of bias listed in Table 1.
Table 1.
Eligible sources of bias in randomized trials.
Fig 2.
Flow diagram of identification, screening, and inclusion of trials.
Table 2.
Summary of characteristics of included meta-epidemiological studies.
Table 3.
Heterogeneity associated with methodological characteristics.
Fig 3.
Random-effects meta-analysis of RORs associated with inadequate/unclear (versus adequate) sequence generation.
The boxed section displays the average bias estimates, where available, from the seven meta-epidemiological studies contributing to the BRANDO 2012a study (however only the BRANDO 2012a ROR was included in our meta-analysis). The BRANDO 2012a ROR is based on a multivariable analysis with adjustment for allocation concealment and double blinding [the corresponding univariable ROR is (95% CrI) 0.89 (0.82, 0.96)]. The BRANDO 2012b ROR is based on a multivariable analysis with adjustment for allocation concealment and double blinding [the corresponding univariable ROR (95% CrI) is 0.89 (0.75, 1.05)]. The Unverzagt 2013c ROR is based on a multivariable analysis with adjustment for allocation concealment, double blinding, attrition, selective outcome reporting, early stopping, pre-intervention, competing interests, baseline imbalance, switching interventions, sufficient follow-up, and single- versus multi-centre status [the corresponding univariable ROR (95% CI) is 0.98 (0.8, 1.21)]. The BRANDO 2012d ROR is based on a multivariable analysis with adjustment for allocation concealment and double blinding [the corresponding univariable ROR (95% CrI) is 0.99 (0.84, 1.16)]. The BRANDO 2012e ROR is based on a multivariable analysis with adjustment for allocation concealment and double blinding [the corresponding univariable ROR (95% CrI) is 0.83 (0.74, 0.94)].
Fig 4.
Random-effects meta-analysis of RORs associated with inadequate/unclear (versus adequate) allocation concealment.
The boxed section displays the average bias estimates, where available, from the seven meta-epidemiological studies contributing to the BRANDO 2012a study (however only the BRANDO 2012a ROR was included in our meta-analysis). The BRANDO 2012a ROR is based on a multivariable analysis with adjustment for sequence generation and double blinding [the corresponding univariable ROR (95% CrI) is 0.93 (0.87, 0.99)]. The BRANDO 2012b ROR is based on a multivariable analysis with adjustment for sequence generation and double blinding [the corresponding univariable ROR (95% CrI) is 0.98 (0.88, 1.10)]. The BRANDO 2012c ROR is based on a multivariable analysis with adjustment for sequence generation and double blinding [the corresponding univariable ROR (95% CrI) is 0.97 (0.85, 1.10)]. The BRANDO 2012d ROR is based on a multivariable analysis with adjustment for sequence generation and double blinding [the corresponding univariable ROR (95% CrI) is 0.85 (0.75, 0.95)].
Fig 5.
Random-effects meta-analysis of RORs and dSMDs associated with presence (versus absence) of baseline imbalance.
The Unverzagt 2013a ROR is based on a multivariable analysis with adjustment for sequence generation, allocation concealment, double blinding, attrition, selective outcome reporting, early stopping, pre-intervention, competing interests, switching interventions, sufficient follow-up, and single- versus multi-centre status [the corresponding univariable ROR (95% CI) is 0.92 (0.80, 1.06)].
Fig 6.
Random-effects meta-analysis of RORs and dSMDs associated with lack of/unclear blinding of participants (versus blinding of participants).
Fig 7.
Random-effects meta-analysis of RORs and dSMDs associated with lack of/unclear blinding of personnel or participants/personnel (versus blinding of either party).
Fig 8.
Estimated RORs and dSMDs associated with any (versus no or minimal) attrition.
The boxed section displays the average bias estimates, where available, from the four meta-epidemiological studies contributing to the BRANDO 2012 study. The Abraha 2015a ROR is based on a multivariable analysis with adjustment for use of placebo comparison, sample size, type of centre, items of risk of bias, post-randomisation exclusions, funding, and publication bias [the corresponding univariable ROR (95% CI) is 0.83 (0.71, 0.97)]. The Unverzagt 2013b ROR is based on a multivariable analysis with adjustment for sequence generation, allocation concealment, double blinding, selective outcome reporting, early stopping, pre-intervention, competing interests, baseline imbalance, switching interventions, sufficient follow-up, and single- versus multi-centre status [the corresponding univariable ROR (95% CI) is 1.19 (0.98, 1.45)]. The Nuesch 2009bc dSMD is based on a multivariable analysis with adjustment for allocation concealment [the corresponding multivariable dSMD (95% CI) with adjustment for blinding of participants is -0.15 (-0.30, 0.00), and the corresponding univariable dSMD (95% CI) is -0.13 (-0.29, 0.04)].
Fig 9.
Random-effects meta-analysis of RORs and dSMDs associated with lack of/unclear blinding of outcome assessors (versus blinding of outcome assessors).
RHR = Ratio of hazard ratios. Hróbjartsson 2014aa “standard trials” comprise those comparing experimental interventions with standard control interventions, such as placebo, no-treatment, usual care or active control. Hróbjartsson 2014ab “atypical trials” comprise those comparing an oral experimental administration of a drug with the intravenous control administration of the same drug for cytomegalovirus retinitis.
Fig 10.
Random-effects meta-analysis of RORs associated with lack of/unclear double blinding (versus double blinding).
The boxed section displays the average bias estimates, where available, from the seven meta-epidemiological studies contributing to the BRANDO 2012a study (however only the BRANDO 2012a ROR was included in our meta-analysis). The BRANDO 2012a ROR is based on a multivariable analysis with adjustment for sequence generation and allocation concealment [the corresponding univariable ROR (95% CrI) is 0.87 (0.79, 0.96)]. The BRANDO 2012b ROR is based on a multivariable analysis with adjustment for sequence generation and allocation concealment [the corresponding univariable ROR (95% CrI) is 0.92 (0.80, 1.04)]. The Unverzagt 2013c ROR is based on a multivariable analysis with adjustment for sequence generation, allocation concealment, attrition, selective outcome reporting, early stopping, pre-intervention, competing interests, baseline imbalance, switching interventions, sufficient follow-up, and single- versus multi-centre status [the corresponding univariable ROR (95% CI) is 0.84 (0.69, 1.02)]. The BRANDO 2012d ROR is based on a multivariable analysis with adjustment for sequence generation and allocation concealment [the corresponding univariable ROR (95% CrI) is 0.93 (0.74, 1.18)]. The BRANDO 2012e ROR is based on a multivariable analysis with adjustment for sequence generation and allocation concealment [the corresponding univariable ROR (95% CrI) is 0.78 (0.65, 0.92)].
Fig 11.
Random-effects meta-analysis of RORs and dSMDs associated with high/unclear (versus low) risk of bias due to selective reporting.
The Unverzagt 2013a ROR is based on a multivariable analysis with adjustment for sequence generation, allocation concealment, double blinding, attrition, early stopping, pre-intervention, competing interests, baseline imbalance, switching interventions, sufficient follow-up, and single- versus multi-centre status [the corresponding univariable ROR (95% CI) is 0.73 (0.54, 0.98)].