If deviations are present, it is still possible to use data from a randomised trial to derive an unbiased estimate of the effect of adhering to intervention (Hernán and Robins 2017). Jensen JS, Bielefeldt AO, Hróbjartsson A. Neurological Sciences. Schulz KF, Grimes DA. Furthermore, outcome measures and analyses should be compared across different papers describing the trial. Allocation concealment in randomised controlled trials: are we getting better? Handling missing data in RCTs; a review of the top medical journals. trialists only state in the trial registry record that they will measure ‘pain’, without specifying the measurement scale, time point or metric that will be used). This domain addresses risk of bias due to missing outcome data, including biases introduced by procedures used to impute, or otherwise account for, the missing outcome data. Systematic differences in the care provided to members of different study groups other than the intervention under investigationPerformance bias is specific to differences that occur due to knowledge of interventions allocation, in either the researcher or the participant. Errors in measurement of outcomes can bias intervention effect estimates. Risk of bias in this domain may differ between outcomes, even if the same people were aware of intervention assignments during the trial. Cochrane Reviews include an assessment of the risk of bias in each included study (see Hernán MA, Scharfstein D. Cautions as Regulators Move to End Exclusive Reliance on Intention to Treat. Knowledge of the next assignment (e.g. Banerjee A, Pluddemann A, O’Sullivan J, Nunan D. Catalogue of Bias Collaboration. Assessments for one of the RoB 2 domains, ‘Bias due to deviations from intended interventions’, differ according to whether review authors are interested in quantifying: Trusted evidence.
The ITT principle of measuring outcome data on all participants (see Section In contrast, other trialists may selectively report harm estimates that are statistically significant and unfavourable to the experimental intervention if they believe that publicizing the existence of a harm will increase their chances of publishing in a high impact journal. Mansournia MA, Higgins JPT, Sterne JAC, Hernán MA. It is important not to select results to assess based on the likely judgements arising from the assessment. Higgins JPT, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, Savović J, Schulz KF, Weeks L, Sterne JAC. An approach that focuses on the main outcomes of the review (the results contributing to the review’s ‘Summary of findings’ table) may be the most appropriate approach (see also Participants who would have been assigned to an intervention deemed to be ‘inappropriate’ may be rejected. An ITT analysis maintains the benefit of randomization: that, on average, the intervention groups do not differ at baseline with respect to measured or unmeasured prognostic factors.
For example, participants in the control group might seek other treatments, or researchers/clinicians might treat participants differently depending on which group they are in. Informed decisions. Although not required, if review authors wish to calculate measures of agreement (e.g. Similarly, for trials in which the comparator intervention is ‘usual care’, the protocol may not specify interventions consistent with usual care or whether they are expected to be used alongside the experimental intervention. For some trials, the analysis intentions will not be readily available. If blinding is not feasible, the effect of performance bias can be mitigated by using objective outcomes. Unfortunately, trial protocols may not fully specify the circumstances in which deviations from the initial intervention should occur, or distinguish changes to intervention that are consistent with the intentions of the investigators from those that should be considered as deviations from the intended intervention. Blinding during a trial can be difficult or impossible in some contexts, for example in a trial comparing a surgical with a non-surgical intervention.
All-cause mortality or the result of an automated test. In particular, a naïve ‘per-protocol’ analysis is restricted to participants who received the intended intervention. The situation most likely to lead to bias is when reasons for missing outcome data differ between the intervention groups: for example if participants who became seriously unwell withdrew from the comparator group while participants who recovered withdrew from the experimental intervention group. Attempts to achieve allocation sequence concealment may be undermined in practice. An attempt to blind participants, carers and people delivering the interventions to intervention group does not ensure successful blinding in practice. Who is blinded in randomized clinical trials? ‘lack of efficacy’ and ‘positive response’) are related to the true values of the missing outcome data.
It may therefore be necessary for review authors to document changes that are and are not considered to be deviations from intended intervention. If possible, review authors should specify potential non-protocol interventions in advance (at review protocol writing stage). For example, unsealed allocation envelopes may be opened, while translucent envelopes may be held against a bright light to reveal the contents (Schulz et al 1995, Schulz 1995, Jüni et al 2001). Personal accounts suggest that many allocation schemes have been deduced by investigators because the methods of concealment were inadequate (Schulz 1995). Before starting an assessment of risk of bias, authors will need to select which specific results from the included trials to assess. For example, in trials comparing an experimental intervention with placebo, trialists who have a preconception or vested interest in showing that the experimental intervention is beneficial and safe may be inclined to be selective in reporting efficacy estimates that are statistically significant and favourable to the experimental intervention, along with harm estimates that are not significantly different between groups. This domain relates primarily to differential errors.