Blinding the statistician?

 Blinding randomised patients and doctors by masking treatment, where this is possible, is an established approach in clinical trials, aiming to prevent bias. It is not uncommon that published trial reports state that the statistician was also blinded, not only during the planning of the final analysis, which has been routine for a long time, but also during the analysis. Professional clinical trials units seem to have variable approaches to the blinding of trial statisticians (1).

You might argue that knowing which arm is which affects the outcome of the statistical analysis, and that blinding the statistician results in a more objective result. However, this misses the fact that statistical comparisons of treatment groups, masked or not, in itself are likely to unblind the data. For example, adverse-event profiles typically show side effect patterns that reveal the identity of treatment and placebo groups.

A reasonable explanation for the statisticians' influence on the analysis results could be that knowing which group is which impacts analytic choices for the final analysis. For example, covariate adjustment, outlier treatment, transformations, and handling of missing data can substantially impact the analysis's outcome. However, the argument misses that fact that these analytical choices, at least in confirmatory trials, must be specified in a detailed statistical analysis plan written prior to the final analysis when also the statistician usually is blinded.

A further argument is that knowing which group is which induces bias in the interpretation of the analysis results (2). While the interpretation of statistical results typically are problematic in exploratory studies, it is hardly an issue in well-defined confirmatory trials having pre-specified hypotheses and pre-specified statistical analyses that include strategies for addressing multiplicity issues.

In my opinion, there doesn't seem to be any good reason for blinding the statistician during the final analysis of a confirmatory trial. It is feasible that those who advocate for such blinding have more experience with exploratory studies than with confirmatory trials. But the two types of research differ profoundly, and the experiences of one might not be relevant to the other.

References

1. Iflaifel M, Partlett C, Bell J, Cook A, Gamble C, Julious S, Juszczak E, Linsell L, Montgomery A, Sprange K. Blinding of study statisticians in clinical trials: a qualitative study in UK clinical trials units. Trials. 2022 Jun 27;23(1):535. doi: 10.1186/s13063-022-06481-9. PMID: 35761345; PMCID: PMC9235168.

2. Järvinen TL, Sihvonen R, Bhandari M, Sprague S, Malmivaara A, Paavola M, Schünemann HJ, Guyatt GH. Blinded interpretation of study results can feasibly and effectively diminish interpretation bias. J Clin Epidemiol. 2014 Jul;67(7):769-72. doi: 10.1016/j.jclinepi.2013.11.011. Epub 2014 Feb 20. PMID: 24560088.

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