Evidence map›Paper›PMID 41323407›Full record

ReviewFrontiers in reproductive health2025

Genetic variation associated with side effects of hormonal contraception exposure: a narrative review.

Mariah Nuzzo, Elise N Erickson, Susan W Groth, Yang Yu, Theresa Koleck, Huashi Li, Kiana Martinez, Adnin Zaman, Caitlin Dreisbach

Abstract readReview
In one paragraph

Review in Frontiers in reproductive health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Mariah NuzzoGoergen Institute for Data Science, University of Rochester, Rochester, NY, United States.
Elise N EricksonDepartment of Physiology College of Medicine Tucson, University of Arizona, Tucson, AZ, United States.
Susan W GrothSchool of Nursing, University of Rochester, Rochester, NY, United States.
Yang YuSchool of Nursing, University of Rochester, Rochester, NY, United States.
Theresa KoleckSchool of Nursing, University of Pittsburgh, Pittsburgh, PA, United States.
Huashi LiStatistics Consulting Lab, BIO5 Institute, University of Arizona, Tucson, AZ, United States.
Kiana MartinezDepartment of Pharmacy Practice and Science, The University of Arizona R. Ken Coit College of Pharmacy, Tucson, AZ, United States.
Adnin ZamanDivision of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Rochester Medical Center, Rochester, NY, United States.
Caitlin DreisbachGoergen Institute for Data Science, University of Rochester, Rochester, NY, United States.

Funding

Genomic Intensive Data Science Research, Education and MentorshipR25HG012324 · NHGRI · UNIVERSITY OF ROCHESTER · PI Justin C Fay, Amanda Marie Larracuente · 2023 to 2026
$1.0M
NHGRI NIH HHS R25 HG012324
6 · The paper itself

Abstract

Hormonal contraceptives (HCs) are commonly prescribed medications that have had immeasurable impacts on quality of life and health of women and families globally. However, usage of exogenous hormones is not without risks, and patients often report a variety of side effects, ranging from burdensome to life-threatening. For some patients, side effects of HCs are severe enough to cause medication discontinuation or switching to alternative forms of contraception. Variability in side effect profiles may indicate heritable risk factors for some side effects. Understanding these patterns or risk profiles may help clinicians anticipate severe adverse events, match patients with suitable medications more rapidly, and improve patient outcomes and adherence. To support further research in this field, this narative review summarizes what is currently known about pharmacogenetic interactions with respect to HCs and specific polymorphisms suspected to contribute to adverse side effects and outcomes.

Indexed as

contraceptionpharmacogenomicsside effectssingle nucleotid polymorphism (SNP)symptoms

Identifiers

PMID41323407
PMCPMC12660243

What OpenQuestion 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 OpenQuestion graph.