Evidence map›Paper›PMID 36920222›Full record

ArticleAmerican journal of epidemiology2023

Risk and Benefit of mRNA COVID-19 Vaccines for the Omicron Variant by Age, Sex, and Presence of Comorbidity: A Quality-Adjusted Life Years Analysis.

Taito Kitano, David A Thompson, Lilly Engineer, Matthew Z Dudley, Daniel A Salmon

Abstract read
PubMed Publisher
In one paragraph

Article in American journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Taito Kitano
David A Thompson
Lilly Engineer
Matthew Z Dudley
Daniel A Salmon
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of the mutant omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 2019 (COVID-19) pandemic raised the importance of reevaluating the risk and benefit of COVID-19 vaccines. With a decision tree model, we calculated the benefit-risk ratio and the benefit-risk difference of receiving monovalent messenger RNA (mRNA) COVID-19 vaccine (primary 2 doses, a third dose, and a fourth dose) in the 4-5 months after vaccination using quality-adjusted life years. The analysis was stratified by age, sex, and the presence of comorbidity. Evidence from peer-reviewed publications and gray literature was reviewed on September 16, 2022, to inform the study. Benefit-risk ratios for receipt of the BNT162b2 vaccine (Pfizer-BioNTech) ranged from 6.8 for males aged 12-17 years without comorbidity for the primary doses to 221.3 for females aged ≥65 years with comorbidity for the third dose. The benefit-risk ratios for receipt of the mRNA-1273 vaccine (Moderna) ranged from 7.2 for males aged 18-29 years without comorbidity for the primary doses to 101.4 for females aged ≥65 years with comorbidity for the third dose. In all scenarios of the one-way sensitivity analysis, the benefit-risk ratios were more than 1, irrespective of age, sex, comorbidity status, and type of vaccine, for both primary and booster doses. The benefits of mRNA COVID-19 vaccines in protecting against the omicron variant outweigh the risks, irrespective of age, sex, and comorbidity.

Indexed as

COVID-19COVID-19 Vaccines2019-nCoV Vaccine mRNA-1273BNT162 VaccineComorbidityFemaleHumansMaleQuality-Adjusted Life YearsRNA, MessengerSARS-CoV-22019-nCoV Vaccine mRNA-1273BNT162 VaccineCOVID-19 VaccinesRNA, Messengercoronavirus disease 2019COVID-19quality-adjusted life yearsrisksafetyvaccines

Identifiers

PMID36920222
OpenAlexW4324306044

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.