Comparative effectiveness of Omicron XBB 1.5-adapted COVID-19 vaccines: a systematic literature review and network meta-analysis
Year: 2025
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: INTRODUCTION: Comparative effectiveness data of COVID-19 vaccines remain limited. We conducted a systematic review and network meta-analysis (NMA) feasibility assessment of effectiveness studies of Omicron-adapted COVID-19 vaccines. RESEARCH DESIGN AND METHODS: Searches in MEDLINE and Embase up to February 2025 identified studies comparing the effectiveness of Omicron-adapted COVID-19 vaccines, either directly or against no recent vaccine. Two investigators independently selected articles reporting adjusted vaccine effectiveness (VE). A feasibility assessment determined the appropriateness of a common comparator and evaluated effect modifiers (EMs). Data extraction and risk-of-bias assessment were performed by one investigator and validated by a second investigator. Bayesian NMAs using random-effects models were performed for base-case analyses, data permitting. RESULTS: The review identified 25 studies for Omicron-adapted COVID-19 vaccines: 16 for XBB formulations, eight of which were included in NMAs, all for mRNA formulations, representing 29.9 million participants. BNT162b2 had the largest evidence base. Comparisons between XBB.1.5-adapted BNT162b2 (Comirnaty) and mRNA-1273 (Spikevax) found that both vaccines are effective and comparable against XBB-related hospitalizations, infections, and medically attended visits in adults Among elderly, the estimated effectiveness against XBB-related hospitalizations favored BNT162b2. CONCLUSIONS: Findings of this NMA of observational studies support the effectiveness of XBB.1.5-adapted mRNA vaccines. Limitations included assumptions on EMs and sparse evidence networks.
Source: Expert Review of Vaccines
Institution: Pfizer (United States)
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funder: Pfizer
OpenAlex ID: W4410325829
