Antiviral effect of Evusheld in COVID-19 hospitalized patients infected with pre-Omicron or Omicron variants: a modelling analysis of the randomized DisCoVeRy trial.

BACKGROUND: The antiviral efficacy of Evusheld (AZD7442) in patients hospitalized for SARS-CoV-2 is unknown. METHODS: We analysed the evolution of both the nasopharyngeal viral load and the serum neutralization activity against the variant of infection in 199 hospitalized patients (109 treated with Evusheld, 90 treated with placebo) infected with the SARS-CoV-2 virus and included in the randomized, double-blind, trial DisCoVeRy (NCT04315948). Using a mechanistic mathematical model, we reconstructed the trajectories of viral kinetics and how they are modulated by the increase in serum neutralization activity during Evusheld treatment. RESULTS: Our model identified that the neutralization activity was associated with viral kinetics. Reflecting the variant-dependent neutralization activity of Evusheld, the antiviral activity of Evusheld was larger in patients infected with pre-Omicron or Omicron BA.2 variants than in patients infected with Omicron BA.1 variant. More specifically, the model predicted that Evusheld reduced the median time to viral clearance compared with placebo-treated patients by more than 5 days in patients infected by pre-Omicron (median: 5.9; 80% PI: 2.1-13.6) or Omicron BA.2 (median: 5.4; 80% PI: 2.0-12.4), respectively. The effect was more modest in patients infected by the Omicron BA.1 variant, reducing the median time to viral clearance by 2 days (median: 2.2; 80% PI: 0.4-8.9). CONCLUSIONS: Hospitalized patients treated with Evusheld had a shorter median time to SARS-CoV-2 viral clearance. As Evusheld antiviral activity is mediated by the level of neutralization activity, its impact on viral clearance varies largely according to the variant of infection.

Nonlinear multilevel joint model for individual lesion kinetics and survival to characterize intra-individual heterogeneity in patients with advanced cancer.

In advanced cancer patients, tumor burden is calculated using the sum of the longest diameters (SLD) of the target lesions, a measure that lumps all lesions together and ignores intra-patient heterogeneity. Here, we used a rich dataset of 342 metastatic bladder cancer patients treated with a novel immunotherapy agent to develop a Bayesian multilevel joint model that can quantify heterogeneity in lesion dynamics and measure their impact on survival. Using a nonlinear model of tumor growth inhibition, we estimated that dynamics differed greatly among lesions, and inter-lesion variability accounted for 21% and 28% of the total variance in tumor shrinkage and treatment effect duration, respectively. Next, we investigated the impact of individual lesion dynamics on survival. Lesions located in the liver and in the bladder had twice as much impact on the instantaneous risk of death compared to those located in the lung or the lymph nodes. Finally, we evaluated the utility of individual lesion follow-up for dynamic predictions. Consistent with results at the population level, the individual lesion model outperformed a model relying only on SLD, especially at early landmark times and in patients with liver or bladder target lesions. Our results show that an individual lesion model can characterize the heterogeneity in tumor dynamics and its impact on survival in advanced cancer patients.