SARS-CoV-2 Neutralizing Antibodies: A Network Meta-Analysis across Vaccines

Background: There are no studies providing head-to-head comparison across SARS-CoV-2 vaccines. Therefore, we compared the efficacy of candidate vaccines in inducing neutralizing antibodies against SARS-CoV-2. Methods: A network meta-analysis was performed to compare the peak levels of SARS-CoV-2 neutralizing antibodies across candidate vaccines. Data were reported as standardized mean difference (SMD) since the outcome was assessed via different metrics and methods across the studies. Results: Data obtained from 836 healthy adult vaccine recipients were extracted from 11 studies. BBIBP-CorV, AZD1222, BNT162b2, New Crown COVID-19, and Sputnik V induced a very large effect on the level of neutralizing antibodies (SMD > 1.3); CoVLP, CoronaVac, NVX-CoV2373, and Ad5-nCoV induced a large effect (SMD > 0.8 to ≤1.3); and Ad26.COV2.S induced a medium effect (SMD > 0.5 to ≤0.8). BBIBP-CorV and AZD122 were more effective (p < 0.05) than Ad26.COV2.S, Ad5–nCoV, mRNA-1237, CoronaVac, NVX–CoV2373, CoVLP, and New Crown COVID-19; New Crown COVID-19 was more effective (p < 0.05) than Ad26.COV2.S, Ad5–nCoV, and mRNA-1237; CoronaVac was more effective (p < 0.05) than Ad26.COV2.S and Ad5–nCoV; and Sputnik V and BNT162b2 were more effective (p < 0.05) than Ad26.COV2.S. In recipients aged ≤60 years, AZD1222, BBIBP-CorV, and mRNA-1237 were the most effective candidate vaccines. Conclusion: All the candidate vaccines induced significant levels of SARS-CoV-2 neutralizing antibodies, but only AZD1222 and mRNA-1237 were certainly tested in patients aged ≥70 years. Compared with AZD1222, BNT162b and mRNA-1237 have the advantage that they can be quickly re-engineered to mimic new mutations of SARS-CoV-2.

Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis). 8 main MS Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. 9 main MS Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

11-12 main MS
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means).

main MS
Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis.

main MS
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

11-12 main MS
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

Study selection
17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
13 main MS; Figure  1 Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
13 main MS; Table 1 Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). 15-16 main MS; Figure  S4 Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
12 main MS; Figure  2 Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. 14 main MS; Figure  3, 4 Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). 15-16 main MS; Figure  S3, S5 Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). 14-15 main MS; Table  S3 DISCUSSION Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).