Effectiveness and Safety of Nirmatrelvir/Ritonavir (Paxlovid) Versus Remdesivir in COVID‐19: A Systematic Review and Meta‐Analysis of Retrospective Studies
Arash Akbarzadeh, Masoud Razeghian, Foruzan Hajiabadi, Parvaneh Dehghan, Sadegh Ahmadi‐Mazhin, Maliheh Eshaghzadeh, Mohsen Poursadeqiyan, Rouhollah ShabestanABSTRACT
Background and Aim
Nirmatrelvir/ritonavir (Paxlovid) and remdesivir are antiviral agents that have been widely used in the management of patients with Coronavirus disease 2019 (COVID‐19). This systematic review and meta‐analysis were conducted to compare the clinical effectiveness and safety outcomes of Paxlovid and remdesivir among patients with COVID‐19.
Methods
A systematic search was performed across the Cochrane Library, Web of Science, PubMed, and medRxiv from inception to July 2024. Data from the identified studies were analyzed using Comprehensive Meta‐Analysis (CMA) software.
Results
Thirteen studies involving 4583 patients were included in the final analysis. Compared with remdesivir, Paxlovid was associated with a significant reduction in mortality (odds ratio [OR] = 0.36, 95% confidence interval [CI]: 0.18–0.73), time to SARS‐CoV‐2 negative conversion (standardized mean differences [SMD] = −1.44, 95% CI: −1.54 to −1.33), hospitalization (OR = 0.34, 95% CI: 0.16–0.74), intensive care unit admission (OR = 0.10, 95% CI: 0.01–0.53), and the need for oxygen therapy (OR = 0.06, 95% CI: 0.02–0.16). No statistically significant difference was observed between the two treatments regarding polymerase chain reaction negativity rate (OR = 1.45, 95% CI: 0.73–2.86). However, adverse events were higher among patients receiving Paxlovid (OR = 6.60, 95% CI: 3.24–13.42). The certainty of evidence for the evaluated outcomes ranged from low to moderate.
Conclusion
In patients with COVID‐19, Paxlovid may offer potential benefits over remdesivir for certain clinical outcomes, though it may also be accompanied by a higher rate of adverse events. These findings are based on retrospective studies, which carry risks of selection bias, confounding, and heterogeneity.