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. 2020 Jun 3;21(1):457.
doi: 10.1186/s13063-020-04374-3.

Changes to aspects of ongoing randomised controlled trials with fixed designs

Xanthi Coskinas  1 , John Simes  1 , Manjula Schou  2   3 , Andrew James Martin  4
Affiliations

Changes to aspects of ongoing randomised controlled trials with fixed designs

Xanthi Coskinas et al. Trials. .

Abstract

Background: Despite careful planning, changes to some aspects of an ongoing randomised clinical trial (RCT), with a fixed design, may be warranted. We sought to elucidate the distinction between legitimate versus illegitimate changes to serve as a guide for less experienced clinical trialists and other stakeholders.

Methods: Using data from a large trial of statin therapy for secondary prevention, we generated a set of simulated trial datasets under the null hypothesis (H0) and a set under an alternative hypothesis (H1). Through analysis of these simulated trials, we assessed the performance of the strategy of changing aspects of the design/analysis with knowledge of treatment allocation (illegitimate) versus the strategy of making changes without knowledge of treatment allocation (legitimate). Performance was assessed using the type 1 error, as well as measures of absolute and relative bias in the treatment effect.

Results: Illegitimate changes led to a relative bias of 61% under H1, and a type 1 error rate under H0 of 23%-well in excess of the 5% significance level targeted. Legitimate changes produced unbiased estimates under H1 and did not inflate the type 1 error rate under H0.

Conclusions: Changes to pre-specified aspects of the design and analysis of an ongoing RCT may be a necessary response to unforeseen circumstances. Such changes risk introducing a bias if undertaken with knowledge of treatment allocation. Legitimate changes need to be adequately documented to provide assurance to all stakeholders of their validity.

Keywords: Bias; Design changes; Randomised control trials; Type 1 error.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Distribution of p-values and θ^ under H0 (null hypothesis) (Scenario 1)
Fig. 2
Fig. 2
Distribution of p-values and θ^ under H0 (null hypothesis) and flexibility in only one analysis decision category (Scenario 2)
Fig. 3
Fig. 3
Distribution of θ^ under H1 (alternative hypothesis) (Scenario 3)
See this image and copyright information in PMC

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