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Systematic Review and Patient-Level Meta-Analysis of SARS-CoV-2 Viral Dynamics to Model Response to Antiviral Therapies

期刊

CLINICAL PHARMACOLOGY & THERAPEUTICS
卷 110, 期 2, 页码 321-333

出版社

WILEY
DOI: 10.1002/cpt.2223

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资金

  1. National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London
  2. United Kingdom Medical Research Council (MRC) Fellowships [M008665, P014534]
  3. NIHR UCL/UCLH Biomedical Research Centre
  4. Rosetrees Trust PhD fellowship [M876]
  5. Wellcome Trust Collaborative Award [203268]
  6. MRC [MR/M008665/1] Funding Source: UKRI

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A meta-analysis was conducted to study the viral dynamics of SARS-CoV-2 in humans, revealing that older age, male gender, and more severe illness are associated with longer viral clearance times. Remdesivir and interferon combined with ribavirin were found to accelerate viral clearance, suggesting further investigation into combination therapy. The study has established a viral dynamic dataset and NLME model for designing and analyzing antiviral trials.
Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral loads change rapidly following symptom onset, so to assess antivirals it is important to understand the natural history and patient factors influencing this. We undertook an individual patient-level meta-analysis of SARS-CoV-2 viral dynamics in humans to describe viral dynamics and estimate the effects of antivirals used to date. This systematic review identified case reports, case series, and clinical trial data from publications between January 1, 2020, and May 31, 2020, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A multivariable Cox proportional hazards (Cox-PH) regression model of time to viral clearance was fitted to respiratory and stool samples. A simplified four parameter nonlinear mixed-effects (NLME) model was fitted to viral load trajectories in all sampling sites and covariate modeling of respiratory viral dynamics was performed to quantify time-dependent drug effects. Patient-level data from 645 individuals (age 1 month to 100 years) with 6,316 viral loads were extracted. Model-based simulations of viral load trajectories in samples from the upper and lower respiratory tract, stool, blood, urine, ocular secretions, and breast milk were generated. Cox-PH modeling showed longer time to viral clearance in older patients, men, and those with more severe disease. Remdesivir was associated with faster viral clearance (adjusted hazard ratio (AHR) = 9.19, P < 0.001), as well as interferon, particularly when combined with ribavirin (AHR = 2.2, P = 0.015; AHR = 6.04, P = 0.006). Combination therapy should be further investigated. A viral dynamic dataset and NLME model for designing and analyzing antiviral trials has been established.

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