Mis-Randomization and Analysis Populations

Introduction

There is a  common question when  the subject is randomized to a wrong treatment arm , what will  the analysis population during the statistical analysis. This part  tries to give an answer for this query based on the papers published wide over .

“Intention to treat” is a strategy for the analysis of randomized controlled trials that compares patients in the groups to which they were originally randomly assigned. This is generally interpreted as including all patients, regardless of whether they actually satisfied the entry criteria, the treatment actually received, and subsequent withdrawal or deviation from the protocol.

For example, in a trial comparing active and placebo vaccination there is the potential for placebo vaccine to be incorrectly administered in place of active, but this could not occur outside the trial and so need not be accounted for in estimates of potential efficacy. However, most types of deviations from protocol would continue to occur in routine practice and so should be included in the estimated benefit of a change in treatment policy. Exclusion of subjects and events from the analysis can introduce bias, for example, subjects who do not receive the assigned treatment, receive the wrong treatment assignment, die before treatment is given, do not adhere to or comply with the study protocol, or dropout of the study.

As per ICH E9 the statistical section of the protocol should address anticipated problems prospectively in terms of how these affect the subjects and data to be analyzed. The protocol should also specify procedures aimed at minimizing any anticipated irregularities in study conduct that might impair a satisfactory analysis, including various types of protocol violations, withdrawals and missing values. The protocol should consider ways both to reduce the frequency of such problems and to handle the problems that do occur in the analysis of data. Possible amendments to the way in which the analysis will deal with protocol violations should be identified during the blind review.


The problem of treatment deviation is not an anticipated error in a clinical trial.. The frequency and type of protocol violations, missing values, and other problems should be documented in the clinical study report and their potential influence on the trial results should be described (see ICH E3).
However, this ITT analysis has been criticized because it does not provide a true test of treatment efficacy (effect of treatment in those who follow the study protocol) but rather of treatment effectiveness (effect of treatment given to everyone). Thus, other methods have been proposed and used that exclude some subjects and events. For example, the analysis “per protocol” excludes subjects who did not adhere to the protocol. As per ICH E9 the treatment deviation is one of the relevant protocol deviations in a trial
Intention to treat analysis is therefore most suitable for pragmatic trials of effectiveness rather than for explanatory investigations of efficacy.
No method of analysis can completely account for large numbers of study subjects who deviate from the study protocol, thereby resulting in high rates of non-adherence, dropout, or missing data. If non-adherences anticipated being a problem in advance of the trial, the study design and the objectives of the study must be reconsidered.

Additional Notes

Pragmatic research asks whether an intervention works under real-life conditions and whether it works in terms that matter to the patient. It is simply concerned with whether the intervention works, not how or why. Pragmatic studies are most useful for deciding what services should be provided but give only limited insight into why interventions do or do not work.

Patient selection for a pragmatic study should reflect routine practice. All patients who might receive the intervention should be studied. Selection criteria should be broad, with exclusions limited to patient groups for whom either the intervention or control are contraindicated. Thus we will know whether the intervention works for patients in general.

 Explanatory research asks whether an intervention works under ideal or selected conditions. It is more concerned with how and why an intervention works. Explanatory studies are valuable for understanding questions of efficacy but are of limited value for telling us whether we should provide a service to a wide variety of patients in a wide variety of circumstances  

For an explanatory study recruitment may be more selective. By excluding patients with co-morbidity or patients with a doubtful diagnosis we can establish whether the intervention works under ideal conditions. However, we will not know how the intervention works in the rather more complex “real-life” setting.