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Review 1: "Covid-19 Vaccination and Menstrual Cycle Length in the Apple Women’s Health Study"

Reviewers found this study to be potentially informative to reliable, with one reviewer suggesting clearer justifications of the analytic methods.

Published onAug 04, 2022
Review 1: "Covid-19 Vaccination and Menstrual Cycle Length in the Apple Women’s Health Study"
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key-enterThis Pub is a Review of
Covid-19 vaccination and menstrual cycle length in the Apple Women’s Health Study

AbstractBackgroundCOVID-19 vaccination may be associated with change in menstrual cycle length following vaccination.MethodsWe conducted a longitudinal analysis within a subgroup of 14,915 participants in the Apple Women’s Health Study (AWHS) who enrolled between November 2019 and December 2021 and met the following eligibility criteria: were living in the U.S., met minimum age requirements for consent, were English speaking, actively tracked their menstrual cycles, and responded to the COVID-19 Vaccine Update survey. In the main analysis, we included tracked cycles recorded when premenopausal participants were not pregnant, lactating, or using hormonal contraceptives. We used conditional linear regression and multivariable linear mixed-effects models with random intercepts to estimate the covariate-adjusted difference in mean cycle length, measured in days, between pre-vaccination cycles, cycles in which a vaccine was administered, and post-vaccination cycles within vaccinated participants, and between vaccinated and unvaccinated participants. We further compared associations between vaccination and menstrual cycle length by the timing of vaccine dose within a menstrual cycle (i.e., in follicular or luteal phase). We present Bonferroni-adjusted 95% confidence intervals to account for multiple comparisons.ResultsA total of 128,094 cycles (median = 10 cycles per participant; interquartile range: 4-22) from 9,652 participants (8,486 vaccinated; 1,166 unvaccinated) were included. The average within-individual standard deviation in cycle length was 4.2 days. Fifty-five percent of vaccinated participants received Pfizer-BioNTech’s mRNA vaccine, 37% received Moderna’s mRNA vaccine, and 7% received the Johnson & Johnson/Janssen vaccine (J&J). We found no evidence of a difference between mean menstrual cycle length in the unvaccinated and vaccinated participants prior to vaccination (0.24 days, 95% CI: −0.34, 0.82).Among vaccinated participants, COVID-19 vaccination was associated with a small increase in mean cycle length (MCL) for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimates for pre vs post cycle lengths were 0.14 days (95% CI: −0.13, 0.40) in the first cycle following vaccination, 0.13 days (95% CI: −0.14, 0.40) in the second, −0.17 days (95% CI: −0.43, 0.10) in the third, and −0.25 days (95% CI: −0.52, 0.01) in the fourth cycle post-vaccination. Follicular phase vaccination was associated with an increase in MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles.ConclusionsCOVID-19 vaccination was associated with an immediate short-term increase in menstrual cycle length overall, which appeared to be driven by doses received in the follicular phase. However, the magnitude of this increase was small and diminished in each cycle following vaccination. No association with cycle length persisted over time. The magnitude of change associated with vaccination was well within the natural variability in the study population. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.



  • Does the manuscript confirm previous work or refute the current understanding? Findings largely confirm previous work.

  • How well does the manuscript position the work within the current literature/understanding? This manuscript needs work prior to publishing. Authors need to justify their analytic approach. Please explain why conditional linear regression, which is not a standard approach, is the appropriate analysis. Why is the vaccinated comparison group not included in the main analysis? This weakens the analysis – having a comparison group is a strength of the data. Presenting probabilities of outcomes would be more useful than ORs. Revise Table titles so they can stand alone – make clear what comparisons are and include model Ns. Remove Cycle Ns from Table 1 – unit of analysis is the woman/individual. Clarify/expand on the data – what is included and how is it structured, logged by participants, etc. Error on in Bonferroni adjustment calculation (not 99.99)

  • Is there clarity regarding the recommended actions that result from the findings? The methods section is very long yet quite confusing and I had many questions after reading it.

  • Do authors pay attention to ethics, diversity, and inclusion? I’m not sure I buy the Authors claim that they have a very diverse sample. Why are race/ethnic categories White/Latina/other?


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