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Evaluating group-sequential non-inferiority clinical trials following interim stopping: The HIV Prevention Trials
Brett S Hanscom1, Deborah J Donnell1, Thomas R Fleming2
1Statistical Center for HIV Research and Prevention, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Background/Aims:
The HIV Prevention Trials Network 083 trial was a group-sequential non-inferiority trial designed to compare HIV incidence under a novel experimental regimen for HIV prevention, long-acting injectable cabotegravir, with an active-control regimen of daily oral tenofovir disoproxil fumarate/emtricitabine (brand name Truvada). In March of 2020, just as the trial had completed enrollment, the COVID-19 pandemic threatened to prevent trial participants from attending study visits and obtaining study medication, motivating the study team to update the interim monitoring plan. The Data and Safety Monitoring Board subsequently stopped the trial at the first interim review due to strong early evidence of efficacy.
Methods:
Here we describe some unique aspects of the trial's design, monitoring, analysis, and interpretation. We illustrate the importance of computing point estimates, confidence intervals, and p values based on the sampling distribution induced by sequential monitoring.
Results:
Accurate analysis, decision-making and interpretation of trial results rely on pre-specification of a stopping boundary, including the scale on which the stopping rule will be implemented, the specific test statistics to be calculated, and how the boundary will be adjusted if the available information fraction at interim review is different from planned. After appropriate adjustment for the sampling distribution and overrun, the HIV Prevention Trials Network 083 trial provided strong evidence that the experimental regimen was superior to the active control.
Conclusions:
For the HIV Prevention Trials Network 083 trial, the difference between corrected inferential statistics and naive results was quite small-as will often be the case-nevertheless, it is appropriate to report and publish the most accurate and unbiased statistical results.
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