Potential impact of COVID-19 on ongoing clinical trials: a simulation study with the neurological Yale Global Tic Severity Scale based on the CANNA-TICS study

Abstract

The COVID-19 pandemic has manifold impacts on clinical trials. In response, drug regulatory agencies and public health bodies have issued guidance on how to assess potential impacts on ongoing clinical trials and stress the importance of a risk-assessment as a pre-requisite for modifications to the clinical trial conduct. This article presents a simulation study to assess the impact on the power of an ongoing clinical trial without the need to unblind trial data and compromise trial integrity. In the context of the CANNA-TICS trial, investigating the effect of nabiximols on reducing the total tic score of the Yale Global Tic Severity Scale (YGTSS-TTS) in patients with chronic tic disorders and Tourette syndrome, the impact of the two COVID-19 related intercurrent events handled by a treatment policy strategy is investigated using a multiplicative and additive data generating model. The empirical power is examined for the analysis of the YGTSS-TTS as a continuous and dichotomized endpoint using analysis techniques adjusted and unadjusted for the occurrence of the intercurrent event. In the investigated scenarios, the simulation studies showed that substantial power losses are possible, potentially making sample size increases necessary to retain sufficient power. However, we were also able to identify scenarios with only limited loss of power. By adjusting for the occurrence of the intercurrent event, the power loss could be diminished to different degrees in most scenarios. In summary, the presented risk assessment approach may support decisions on trial modifications like sample size increases, while maintaining trial integrity.

Keywords: COVID-19; Yale Global Tic Severity Scale; power; risk assessment; simulation study.

FIGURE 1

Potential impacts of the intercurrent event on the distribution of relative change in YGTSS‐TTS from 13 weeks. Panel (A) depicts the planning assumptions for the relative change in YGTSS‐TTS, corresponding expected response rates are 1% for the Placebo group and 29% for the Treatment group. Panel (B) exemplifies scenario (i) leading to an increase at the YGTSS‐TTS at the second visit, and a decrease in the expected response rates to 0% for the Placebo group and 14% for the Treatment group. Panel (C) exemplifies scenario (ii) introducing additional variability, but not changing the expected YGTSS‐TTS. Due to in increased variability, the expected response rates increase to 4% for the Placebo group and 30% for the Treatment group. Panel (D) exemplifies scenario (iii) leading to a decrease of the YGTSS‐TTS at the second visit, and an increase in the expected response rates to 41% for the Placebo group and 62% for the Treatment group