Planning robust clinical trials for Shigella vaccines: A simulation-based evaluation of the impact of naturally-acquired immunity on vaccine performance

BackgroundSeveral Shigella vaccine candidates are in late stages of development, and the design of large Phase 3 trials in target populations is underway. Immunologic catch up by unvaccinated infants to vaccinated infants, which is determined by the trial site-specific force of infection, may modify the vaccine efficacy (VE) estimates observed in such trials. To set expectations and support optimal planning of future Shigella vaccine trials, we aimed to quantify the potential bias of VE estimates from the force of infection under different surveillance strategies and assumptions about Shigella immunity. MethodsWe simulated Shigella vaccine trials in low-, medium-, and high-burden settings under different assumptions about vaccine- and infection-conferred immunity. We evaluated six trial designs: active surveillance for Shigella infection or symptom-based reporting paired with single-outcome, stratified recurrent outcome, or crude recurrent-outcome Cox proportional hazards models. In each scenario, we evaluated bias, 95% confidence interval coverage, and the false negative rate. FindingsOnly the trial design using active surveillance for infection and single outcome models was consistently unbiased across all examined scenarios. The other five designs underestimated VE by up to an absolute 20%, with a single outcome model paired with symptom-based reporting performing least poorly. Bias generally was worse at higher-burden sites. For realistically sized trials, the 95% CI coverage and false negative rate were also worse at higher-burden sites. InterpretationThe observed VE in Shigella vaccine trials is likely to underestimate true VE. Careful trial design is needed to minimize this underestimation.