Evidence map›Paper›PMID 36868258›Full record

SynthesisThe Lancet. Microbe2023

Efficacy of SARS-CoV-2 vaccines and the dose-response relationship with three major antibodies: a systematic review and meta-analysis of randomised controlled trials.

Zhi-Rong Yang, Yi-Wen Jiang, Fu-Xiao Li, Di Liu, Teng-Fei Lin, Zi-Yi Zhao, Chang Wei, Qian-Yi Jin, Xi-Miao Li, Yuan-Xi Jia and 5 more

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in The Lancet. Microbe, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 4 pooled it
24.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 4 syntheses or guidelines pooled it, 128 citations in OpenAlex.

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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 6 institutions in 3 countries.

Zhi-Rong YangCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Yi-Wen JiangCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Fu-Xiao LiCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Di LiuCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Teng-Fei LinCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Zi-Yi ZhaoCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Chang WeiCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Qian-Yi JinSchool of Mathematics, Sun Yat-sen University, Guangzhou, China.
Xi-Miao LiSchool of Mathematics, Sun Yat-sen University, Guangzhou, China.
Yuan-Xi JiaCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Feng-Cai ZhuDepartment of Vaccine Clinical Evaluation, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Zu-Yao YangDivision of Epidemiology, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China. Electronic address: zyang@cuhk.edu.hk.
Feng ShaCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. Electronic address: feng.sha@siat.ac.cn.
Zi-Jian FengDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Jin-Ling TangCenter for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Clinical Data Center, Guangzhou Women and Children's Medical Center, Guangzhou, China.
Chinese University of Hong Kong · HKShenzhen Institutes of Advanced Technology · CNSun Yat-sen University · CNGuangzhou Women and Children Medical Center · CNChinese Center For Disease Control and Prevention · CNJiangsu Provincial Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe efficacy of SARS-CoV-2 vaccines in preventing severe COVID-19 illness and death is uncertain due to the rarity of data in individual trials. How well the antibody concentrations can predict the efficacy is also uncertain. We aimed to assess the efficacy of these vaccines in preventing SARS-CoV-2 infections of different severities and the dose-response relationship between the antibody concentrations and efficacy.

methodsWe did a systematic review and meta-analysis of randomised controlled trials (RCTs). We searched PubMed, Embase, Scopus, Web of Science, Cochrane Library, WHO, bioRxiv, and medRxiv for papers published between Jan 1, 2020 and Sep 12, 2022. RCTs on the efficacy of SARS-CoV-2 vaccines were eligible. Risk of bias was assessed using the Cochrane tool. A frequentist, random-effects model was used to combine efficacy for common outcomes (ie, symptomatic and asymptomatic infections) and a Bayesian random-effects model was used for rare outcomes (ie, hospital admission, severe infection, and death). Potential sources of heterogeneity were investigated. The dose-response relationships of neutralising, spike-specific IgG and receptor binding domain-specific IgG antibody titres with efficacy in preventing SARS-CoV-2 symptomatic and severe infections were examined by meta-regression. This systematic review is registered with PROSPERO, CRD42021287238.

findings28 RCTs (n=286 915 in vaccination groups and n=233 236 in placebo groups; median follow-up 1-6 months after last vaccination) across 32 publications were included in this review. The combined efficacy of full vaccination was 44·5% (95% CI 27·8-57·4) for preventing asymptomatic infections, 76·5% (69·8-81·7) for preventing symptomatic infections, 95·4% (95% credible interval 88·0-98·7) for preventing hospitalisation, 90·8% (85·5-95·1) for preventing severe infection, and 85·8% (68·7-94·6) for preventing death. There was heterogeneity in the efficacy of SARS-CoV-2 vaccines against asymptomatic and symptomatic infections but insufficient evidence to suggest whether the efficacy could differ according to the type of vaccine, age of the vaccinated individual, and between-dose interval (p>0·05 for all). Vaccine efficacy against symptomatic infection waned over time after full vaccination, with an average decrease of 13·6% (95% CI 5·5-22·3; p=0·0007) per month but can be enhanced by a booster. We found a significant non-linear relationship between each type of antibody and efficacy against symptomatic and severe infections (p<0·0001 for all), but there remained considerable heterogeneity in the efficacy, which cannot be explained by antibody concentrations. The risk of bias was low in most studies.

interpretationThe efficacy of SARS-CoV-2 vaccines is higher for preventing severe infection and death than for preventing milder infection. Vaccine efficacy wanes over time but can be enhanced by a booster. Higher antibody titres are associated with higher estimates of efficacy but precise predictions are difficult due to large unexplained heterogeneity. These findings provide an important knowledge base for interpretation and application of future studies on these issues.

fundingShenzhen Science and Technology Programs.

Indexed as

COVID-19COVID-19 VaccinesAsymptomatic InfectionsHumansImmunoglobulin GRandomized Controlled Trials as TopicSARS-CoV-2COVID-19 VaccinesImmunoglobulin G

Identifiers

PMID36868258
PMCPMC9974155
OpenAlexW4322603953

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.