10.6084/M9.FIGSHARE.21275966.V1
Sean M. Hughes
Sean M.
Hughes
University of Washington
Claire N. Levy
Claire N.
Levy
University of Washington
Ronit Katz
Ronit
Katz
University of Washington
Erica M. Lokken
Erica M.
Lokken
University of Washington
Melis N. Anahtar
Melis N.
Anahtar
Massachusetts General Hospital
Melissa Barousse Hall
Melissa Barousse
Hall
University of Louisville
Frideborg Bradley
Frideborg
Bradley
Karolinska University Hospital
Philip E. Castle
Philip E.
Castle
National Cancer Institute
Valerie Cortez
Valerie
Cortez
University of California, Santa Cruz
Gustavo F. Doncel
Gustavo F.
Doncel
Eastern Virginia Medical School
Raina Fichorova
Raina
Fichorova
Harvard University
Paul L. Fidel
Paul L.
Fidel
Louisiana State University Health Sciences Center New Orleans
Keith R. Fowke
Keith R.
Fowke
University of Manitoba
Suzanna C. Francis
Suzanna C.
Francis
London School of Hygiene & Tropical Medicine
Mimi Ghosh
Mimi
Ghosh
George Washington University
Loris Y. Hwang
Loris Y.
Hwang
University of California, Los Angeles
Mariel Jais
Mariel
Jais
George Washington University
Vicky Jespers
Vicky
Jespers
Institute of Tropical Medicine Antwerp
Vineet Joag
Vineet
Joag
University of Minnesota
Rupert Kaul
Rupert
Kaul
University of Toronto
Jordan Kyongo
Jordan
Kyongo
Institute of Tropical Medicine Antwerp
Timothy Lahey
Timothy
Lahey
University of Vermont
Huiying Li
Huiying
Li
University of California, Los Angeles
Julia Makinde
Julia
Makinde
International AIDS Vaccine Initiative
Imperial College London
Lyle R. McKinnon
Lyle R.
McKinnon
University of Nairobi
University of Manitoba
Centre for the AIDS Programme of Research in South Africa
Anna-Barbara Moscicki
Anna-Barbara
Moscicki
University of California, Los Angeles
Richard M. Novak
Richard M.
Novak
University of Illinois at Chicago
Mickey V. Patel
Mickey V.
Patel
Dartmouth College
Intira Sriprasert
Intira
Sriprasert
University of Southern California
Andrea R. Thurman
Andrea R.
Thurman
Eastern Virginia Medical School
Sergey Yegorov
Sergey
Yegorov
McMaster University
Nelly Rwamba Mugo
Nelly Rwamba
Mugo
Kenya Medical Research Institute
University of Washington
Alison C. Roxby
Alison C.
Roxby
Fred Hutchinson Cancer Center
University of Washington
Elizabeth Micks
Elizabeth
Micks
University of Washington
Florian Hladik
Florian
Hladik
0000-0002-0375-2764
Fred Hutchinson Cancer Center
University of Washington
Additional file 5 of Changes in concentrations of cervicovaginal immune mediators across the menstrual cycle: a systematic review and meta-analysis of individual patient data
Additional file 5: Figure S1. Assessment of publication bias. A Funnel plots. Symbols show the effect of the menstrual cycle (x-axis) and the standard error of that effect (y-axis, reversed). Each symbol shows an individual study. Vertical solid line shows no effect. Vertical dashed line shows the meta-estimate of effect. Diagonal dashed lines enclose the region expected to include 95% of studies based on the estimated meta-effect and the standard errors. B Results of Egger’s tests for publication bias. Figure S2. Periovulatory meta-analyses. A The log2 difference between periovulatory and follicular phases (log2-pg/mL of the follicular phase minus log2-pg/mL of the periovulatory phase). For TGF-β1, the error bars for one study and the meta-estimate extend off-scale. B The log2 difference between periovulatory and luteal phases (log2-pg/mL of the luteal phase minus log2-pg/mL of the periovulatory phase). For IL-10, the error bars for one study extend off-scale. Each row represents a different immune mediator, with the symbols showing the mean and the lines showing the 95% confidence intervals. Gray symbols indicate individual studies and black the meta-estimates as determined by inverse-variance pooling random effects models. Black filled symbols indicate p < 0.05 while white filled symbols indicate p > 0.05. Positive numbers indicate higher during the follicular or luteal phase, while negative numbers indicate higher during the periovulatory phase. Fig S3. Subgroup analysis: Does the effect of menstrual cycle differ by assay method, geographical region, or method of determining menstrual phase? A Meta-analyses, comparing all studies (black circles) to studies grouped by assay method (ELISA: blue squares; MSD: yellow triangles; Luminex: green diamonds). B Meta-analyses, comparing all studies (black circles) to studies grouped by geographical region of sample origin (Africa: blue diamonds; Europe: red squares; North America: green triangles). C Meta-analyses, comparing all studies (black circles) to studies grouped by method of menstrual cycle phasing (Days since LMP: orange squares; Progesterone: pale purple diamonds; Progesterone plus LH: dark purple triangles). Figure S4. Secondary outcomes: Method of determining menstrual cycle phase and normalization to total protein. A The standard errors of the effect sizes for the difference between menstrual cycle phases, with phases determined by days since last menstrual period (“LMP”) or serum progesterone (“Prog”). Each symbol represents an immune factor, with lines connecting the same immune factor. B The standard errors of the effect sizes for the difference between menstrual cycle phases as determined using raw concentration measurements (pg/mL) and concentrations normalized to total protein (pg/pg total protein). Each symbol represents an immune factor, with lines connecting the same immune factor. Table S1. Summary of immune mediators measured in single studies. Table S2. Summary of follicular vs. periovulatory meta-analyses. Table S3. Summary of luteal vs. periovulatory meta-analyses. Table S4. Covariates adjusted for in multivariate analysis of each study.
Immunology
figshare
2022
2022-10-05
2024-02-16
Dataset
4839986 Bytes
10.6084/m9.figshare.21275966
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