Evidence map›Paper›PMID 40896461›Full record

ArticleEClinicalMedicine2025

Estimating cardiovascular effects of influenza vaccination in older adults: a target trial emulation using proximal causal inference.

Jinxin Guo, Tiansheng Wang, Zhike Liu, Weihong Zeng, Peng Shen, Yexiang Sun, Siyan Zhan, Yang Xu

Registry-linked trialAbstract read
In one paragraph

Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07512401 (Safety of Reduced Methotrexate Lab Monitoring), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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.

NCT07512401 completednot on this map

Safety of Reduced Methotrexate Lab Monitoring: a Population-based, Target Trial Emulation Study

TypeobservationalSponsorMayo ClinicRan2012 to 2025Enrolled2,414ConditionsRheumatic DiseasesArmsStandard methotrexate lab monitoring, Reduced methotrexate lab monitoring
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

8 authors.

Jinxin GuoKey Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Tiansheng WangDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Zhike LiuKey Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Weihong ZengDepartment of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Peng ShenYinzhou District Center for Disease Control and Prevention, Yinzhou District, Ningbo, China.
Yexiang SunYinzhou District Center for Disease Control and Prevention, Yinzhou District, Ningbo, China.
Siyan ZhanKey Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yang XuDepartment of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The substantial burden of cardiovascular diseases highlights the urgent need for cost-effective interventions to mitigate their impact. While existing evidence on the cardioprotective effect of the influenza vaccine comes primarily from populations with cardiovascular comorbidities, these studies remain susceptible to several sources of bias, including immortal time bias and unmeasured confounding. To attenuate these limitations, our study aimed to assess the effect of influenza vaccination on cardiovascular events in an older population in China, utilizing a target trial emulation framework in conjunction with a proximal causal inference (PCI) approach. Methods: This is a sequentially designed, propensity score (PS) matched, vaccine effectiveness study under a target trial emulation framework. We used data from the Yinzhou Regional Health Care Database and included permanent residents of Yinzhou, China, aged 65 years or older. We employed a sequential trial approach in which participants were categorized as influenza vaccinees or non-vaccinees based on their vaccination regimen during the one-week enrollment period of each sequential trial from 2020 to 2022. The outcomes of interest were major adverse cardiovascular events (MACE) and acute coronary syndromes (ACS) within one year of follow-up. To address measured and unmeasured confounding, PS matching was performed in conjunction with PCI using a two-stage Poisson regression to estimate incidence rate ratios (IRRs). Findings: A total of 8,181,638 older adults were included across the 50 emulated trials between 2020 and 2022. Of these, 170,011 received influenza vaccination, while 8,011,627 remained unvaccinated. Vaccinated participants were generally frailer (severely frail: 19.1% Interpretation: Influenza vaccination may reduce the risk of MACE and ACS among older adults. Aligned with the World Health Organization guidelines, our findings further support influenza vaccination as an effective public health strategy for potentially reducing cardiovascular disease burden. Funding: National Natural Science Foundation of China; Science and Technology Project of Science and Technology Bureau of Yinzhou District, Ningbo City; Zhejiang Provincial Centre for Disease Control and Prevention Science and Technology Program; Bill & Melinda Gates Foundation.

Indexed as

Acute coronary syndromesInfluenza vaccinationMajor adverse cardiovascular eventsProximal causal inference

Identifiers

PMID40896461
PMCPMC12398818

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LicenceCC BY-NC-ND
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Registered trials

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.