Evidence map›Paper›PMID 40378132›Full record

SynthesisPloS one2025

Menstrual disturbance associated with COVID-19 vaccines: A comprehensive systematic review and meta-analysis.

Kunchok Dorjee, R C Sadoff, Farima Rahimi Mansour, Sangyal Dorjee, Eli M Binder, Maria Stetson, Regina Yuen, Hyunju Kim

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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

1 citing paper in PubMed.

  1. Article
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.

Kunchok DorjeeCenter for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0003-0992-0631
R C SadoffCenter for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-5907-1976
Farima Rahimi MansourPreventative Gynecology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Sangyal DorjeeCenter for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Eli M BinderAdams County Health Department, Brighton, Colorado, United States of America.ORCID https://orcid.org/0000-0002-8590-5786
Maria StetsonCenter for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Regina YuenCenter for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Hyunju KimDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-1707-7018

Funding

Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Anna Palmer Durbin · 2012 to 2026
$67.0M
Tuberculosis Transmission and Preventive Therapy in Tibetan Children and Young Adults in IndiaK01AI148583 · NIAID · JOHNS HOPKINS UNIVERSITY · PI DORJEE, KUNCHOK · 2020 to 2024
$734k
NIAID NIH HHS K01 AI148583NIAID NIH HHS P30 AI094189
6 · The paper itself

Abstract

backgroundThe relationship between COVID-19 vaccines and menstrual disturbance is unclear, in part because researchers have measured different outcomes (e.g., delays vs. changes to cycle length) with various study designs. Menstrual disruption could be a decisive factor in people's willingness to accept the COVID-19 vaccine.

methodsWe searched Medline, Embase, and Web of Science for studies investigating menstrual cycle length, flow volume, post-menopausal bleeding, and unexpected or intermenstrual bleeding. Data were analyzed using fixed-effects meta-analysis with Shore's adjusted confidence intervals for heterogeneity.

findingsSeventeen studies with >1·9 million participants were analyzed. We found a 19% greater risk of increase in menstrual cycle length as compared to unvaccinated people or pre-vaccination time-periods (summary relative risk (sRR): 1·19; 95% CI: 1·11-1·26; n = 23,718 participants). The increase in risk was the same for Pfizer-BioNTech (sRR: 1·15; 1·05-1·27; n = 16,595) and Moderna vaccines (sRR: 1·15; 1·05-1·25; n = 7,523), similar for AstraZeneca (sRR: 1·27; 1·02-1·59; n = 532), and higher for the Janssen (sRR: 1·69; 1·14-2·52; n = 751) vaccine. In the first cycle after vaccination, length increased by <half-day (summary mean difference (sMD): 0·34 days; 0·21-0·46 days; n = 30,320) after the first dose and by 0·62 days (sMD: 0·62: 0·41-0·82; n = 17,608) after the second dose. In the second cycle after vaccination, the risk was not elevated (sMD: -0·02; -0·16-0·12; n = 18,602). The increase in risk was between 7-9% but statistically insignificant for heavier flow; 7% for post-menopausal bleeding (first dose: 1·07; 1·01-1·12; n = 1,321,268 and second dose: 1·07; 1·03-1·11; n = 1,482,884); and 16-41% for unexpected or intermenstrual bleeding (first dose: 1·16; 0·83-1·61; n = 1,303,687 and second dose: 1·41; 0·99-2·01; n = 1,390,317).

interpretationWe observed a mild increase in the risk of menstrual disturbance associated with COVID-19 vaccines. Such risks are likely clinically unmeaningful. Vaccine recipients should be appropriately counseled.

Indexed as

COVID-19COVID-19 VaccinesMenstruation DisturbancesFemaleHumansMenstrual CycleSARS-CoV-2VaccinationCOVID-19 Vaccines

Identifiers

PMID40378132
PMCPMC12083795

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.