Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
PLoS Negl Trop Dis. 2020 Nov 16;14(11):e0008109. doi: 10.1371/journal.pntd.0008109. eCollection 2020 Nov.
For most antivenoms there is little information from clinical studies to infer the relationship between dose and efficacy or dose and toxicity. Antivenom dose-finding studies usually recruit too few patients (e.g. fewer than 20) relative to clinically significant event rates (e.g. 5%). Model based adaptive dose-finding studies make efficient use of accrued patient data by using information across dosing levels, and converge rapidly to the contextually defined 'optimal dose'. Adequate sample sizes for adaptive dose-finding trials can be determined by simulation. We propose a model based, Bayesian phase 2 type, adaptive clinical trial design for the characterisation of optimal initial antivenom doses in contexts where both efficacy and toxicity are measured as binary endpoints. This design is illustrated in the context of dose-finding for Daboia siamensis (Eastern Russell's viper) envenoming in Myanmar. The design formalises the optimal initial dose of antivenom as the dose closest to that giving a pre-specified desired efficacy, but resulting in less than a pre-specified maximum toxicity. For Daboia siamensis envenoming, efficacy is defined as the restoration of blood coagulability within six hours, and toxicity is defined as anaphylaxis. Comprehensive simulation studies compared the expected behaviour of the model based design to a simpler rule based design (a modified '3+3' design). The model based design can identify an optimal dose after fewer patients relative to the rule based design. Open source code for the simulations is made available in order to determine adequate sample sizes for future adaptive snakebite trials. Antivenom dose-finding trials would benefit from using standard model based adaptive designs. Dose-finding trials where rare events (e.g. 5% occurrence) are of clinical importance necessitate larger sample sizes than current practice. We will apply the model based design to determine a safe and efficacious dose for a novel lyophilised antivenom to treat Daboia siamensis envenoming in Myanmar.
对于大多数抗蛇毒血清，几乎没有临床研究信息可以推断剂量与疗效或剂量与毒性之间的关系。抗蛇毒血清剂量发现研究通常招募的患者相对临床显著事件发生率（例如 5%）较少（例如少于 20 例）。基于模型的适应性剂量发现研究通过使用各剂量水平的信息，高效利用累积的患者数据，并迅速收敛到上下文定义的“最佳剂量”。适应性剂量发现试验的足够样本量可以通过模拟确定。我们提出了一种基于模型的、贝叶斯二期型、适应性临床试验设计，用于在疗效和毒性均作为二分类终点进行测量的情况下，描述最佳初始抗蛇毒血清剂量。该设计在缅甸的圆斑蝰（东方罗素的毒蛇）蛇伤的剂量发现中进行了说明。该设计将抗蛇毒血清的最佳初始剂量形式化为最接近指定疗效所需剂量的剂量，但导致的最大毒性低于指定的最大毒性。对于圆斑蝰蛇伤，疗效定义为六小时内凝血功能恢复，毒性定义为过敏反应。综合模拟研究比较了基于模型的设计与更简单的基于规则的设计（改良的“3+3”设计）的预期行为。与基于规则的设计相比，基于模型的设计可以在更少的患者中确定最佳剂量。为了确定未来适应性蛇咬伤试验的足够样本量，我们提供了模拟的开源代码。抗蛇毒血清剂量发现试验将受益于使用标准的基于模型的自适应设计。对于具有临床重要意义的罕见事件（例如 5%的发生率），剂量发现试验需要比当前实践更大的样本量。我们将应用基于模型的设计来确定一种安全有效的新型冻干抗蛇毒血清剂量，用于治疗缅甸的圆斑蝰蛇伤。
