Early-Phase Dose-Finding Trials in Virology

Viruses have taken central place in public health due to the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Antiviral treatments, and combination of antivirals, can be effective at reducing viral load shortly after infection, improving long-term outcomes. While it is obvious that choosing the right dose of treatment is a fundamental consideration, little has been published in terms of methodology for dose-finding trials in virology. The considerable progress in dose-finding methodology of the last few decades has focused almost entirely on oncology. However, the framework developed in oncology does not apply 1:1 to virology. While adverse reactions to cytotoxic drugs may be life threatening, for anti-viral agents, we anticipate something different: side effects that provoke the cessation of treatment. This would correspond to treatment failure. On the contrary, success would not be yes/no but would correspond to a range of responses, from small, no more than say 20% reduction in viral load to the complete elimination of the virus. Less than total success matters since this may allow the patient to achieve immunemediated clearance. In this presentation, we will introduce a novel methodology whose goal is twofold: first, to identify the dose that provides the most favorable distribution of treatment outcomes, and, second, to do this in a way that maximizes the treatment benefit for the patients included in the study. We will compare two modeling approaches in the talk. The first approach relies on the Bayesian Dirichlet-Categorical model to describe the toxicity/efficacy profile of each of the dose levels. The second approach relies on the principles of the continual reassessment model (CRM). We separately model the dose-toxicity curve and the dose-efficacy curve. By representing efficacy with three categories (low, medium, high viral load reduction), we can use the following assumptions: dose-efficacy curve is decreasing for the low-response category, and dose-efficacy curve in increasing for the high-response category. By combining the modeled toxicity and efficacy curves, we obtain the center of mass curve over the dose levels of interest. We will compare both approaches via simulations. The first approach described above has been recently published in Statistics in Medicine (doi: 10.1002/ sim.8771). The second approach is being currently developed and tested and will be the topic of a future publication.

Gestational Diabetes during the Pandemic: Screening Methods and Outcomes in First-time GDM

Objective: To study the impact of national recommendations on the method of screening used for GDM during the COVID-19 pandemic, and evaluate differences in maternal and fetal outcomes among women with first-time GDM (ftGDM). Design: A retrospective observational study in a single Tertiary London Hospital. During the pandemic, the RCOG recommended an amended GDM screening protocol to reduce hospital attendance and risk of virus transmission (fasting blood glucose level ≥5.3 and/or HbA1c ≥39 at 28 weeks of gestation). Our Trust did not adopt this due to concerns regarding its sensitivity. We adopt a 2-step approach to universal GDM screening using a 50g glucose challenge test, and refer those screening positive for a full oral glucose tolerance test. Method: Outcomes were reviewed for women with ftGDM delivering a singleton at ≥24 weeks gestation between 01/04/20 -28/ 5/21. Our primary aim was to determine the impact of the change in COVID-19 GDM screening policy, had it been implemented. Our secondary outcomes included GDM management method, maternal and perinatal complications. We excluded women with a booking HbA1c ≥42 (indicative of pre-diabetes) and those who had bariatric surgery. Demographic and outcome data were obtained from electronic databases. Results: 247 women were diagnosed with ftGDM using local screening methods. Only 23 of these women had a HbA1c ≥39 at time of diagnosis and a further 12 had FBG ≥5.3. There was no significant difference in age or ethnicity between the two groups. The locally diagnosed group had a statistically significantly lower booking BMI (P<0.001) and were less likely to require pharmacological management of GDM (P<0.001). There were no significant differences in rates of induction of labour, gestation at delivery, birth weight or any perinatal adverse outcome. However, the women in the Covid-19 GDM screening group were significantly more likely to be delivered by Emergency Caesarean Section (p = 0.03) and have gestational hypertensive disease (p = 0.025). Conclusions: If we had implemented RCOG HbA1c screening, we would have not diagnosed 207 women with GDM, 41% of whom required pharmacological treatment. It is not surprising that women with higher HbA1c values had higher rates of maternal complications, due to the well-established association between maternal hyperglycaemia and adverse obstetric outcomes. As such, it is imperative that more sensitive screening protocols such as the 50g screen are considered in any future pandemics, such that women with GDM can be identified and maternal hyperglycaemia treated to benefit in-utero fetal programming.