Evidence map›Paper›PMID 38853494›Full record

ArticleTurkish journal of obstetrics and gynecology2024

Effects of bazedoxifene on endometriosis in experimental animal models: A systematic review and meta-analysis.

Reza Hassanzadeh Makoui, Shiva Fekri, Negar Ansari, Masoud Hassanzadeh Makoui

Abstract read
In one paragraph

Article in Turkish journal of obstetrics and gynecology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

4 authors.

Reza Hassanzadeh MakouiZanjan University Faculty of Medicine, Department of Immunology, Zanjan, Iran.ORCID 0000-0001-6673-6692
Shiva FekriZanjan University Faculty of Medicine, Department of Obstetrics and Gynecology, Zanjan, Iran.ORCID 0009-0008-1435-9053
Negar AnsariZanjan University Faculty of Medicine, Department of Internal Medicine, Zanjan, Iran.ORCID 0000-0003-2263-359X
Masoud Hassanzadeh MakouiZanjan University Faculty of Medicine, Department of Immunology, Zanjan, Iran.ORCID 0000-0002-0821-4420

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endometriosis is a prevalent condition in women that causes pelvic pain and fertility issues due to the growth of endometrial tissue outside the uterus during menstrual cycles. Steroid hormones play a crucial role in the development and growth of endometriosis lesions; therefore, researchers have investigated several effective drugs that target hormones for treating this disease. One such drug is bazedoxifene, but despite several animal studies, there has yet to be a comprehensive evaluation of their combined results. A systematic search was conducted across several databases (Embase, PubMed, Scopus, and Web of Sciences) to identify studies investigating the effectiveness of bazedoxifene in animal models of endometriosis. Meta-analysis was performed using the size of endometriosis implants before and after drug administration in the case and control groups, along with the p-value of the associations. Begg's and Egger's tests were used to assess publication bias. This study included four eligible studies consisting of 45 endometrial animal models and 35 control subjects. The meta-analysis showed that bazedoxifene significantly reduced the size of endometriosis implants in animal models compared with the control group (odds ratio: 0.122, 95% confidence interval: 0.050-0.298, p<0.001). Detailed investigation determined that there was no significant heterogeneity between the studies (I2=38.81, and p-value of the Q test=0.179). However, according to Egger's test, the study showed publication bias (p=0.035). This study found that bazedoxifene is a promising treatment option for endometriosis in animal models. However, more research on animals and humans is required to confirm these results.

Indexed as

Animal modelbazedoxifeneendometriosismeta-analysis

Identifiers

PMID38853494
PMCPMC11589230

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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.