Abstract
Preventing type 1 diabetes remains a significant challenge but ongoing efforts are bringing us closer to this goal. This article discusses some implications of heterogeneity and chance in relation to prevention of type 1 diabetes, particularly regarding interpretation of evidence and planning of future trials. Using simulations, I illustrate uncertainties in efficacy estimates in prevention trials with time-to-event endpoints, using the TN10 teplizumab trial as an example. I emphasise that risk heterogeneity does not equate to treatment effect heterogeneity. When factors modifying efficacy are taken into account, robust identification of treatment effect heterogeneity may require sample sizes approximately four times larger than those needed to determine overall efficacy in certain scenarios. Efficiency of prevention trials can be increased using 2 × 2 factorial designs investigating two treatment options. I also simulate statistical power in exploratory studies involving multiple testing with different strategies for handling potential type 1 diabetes endotypes. If endotypes are defined as subtypes of type 1 diabetes-related phenotypes with at least partially unique risk factors, it becomes clear that we should aim to discover actionable aetiological factors that are not endotype-specific. Subjective judgements and pragmatism will influence whether and how a prevention trial is planned. Current approaches target high-risk individuals, which reduces the required number of trial participants but increases the cost of identifying trial participants. A prevention trial targeting infants in the general population with a multivalent antiviral vaccine will likely need over 50,000 participants, depending on circumstances and assumptions. While such a trial is conceivable, it would demand robust safety data before initiation.