# 3/4, University of Illinois at Chicago Clinical Site- Reproductive Medicine Collaborative Consortium: A randomized placebo-controlled trial of EGCG to improve fertility in women with uterine fibroids

> **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2022 · $311,640

## Abstract

ABSTRACT
Uterine leiomyomas (fibroids) are the most important neoplastic threat to women's health worldwide,
disproportionately affect women of color and are a significant cause of infertility. Intramural and submucosal
fibroids reduce the likelihood of pregnancy (RR=0.3-0.7) compared to unaffected women. Surgical removal of
fibroids is afflicted with high recurrence rates and frequent postoperative consequences such as adhesions.
There is a critical need for innovative effective, non-hormonal, non-surgical fertility treatment options for
women with fibroids that may distort the uterine cavity. Our long-term goal is to develop novel non-hormonal
treatments for uterine fibroids. Green tea catechins, such as epigallocatechin gallate (EGCG) is safe during
conception and pregnancy. EGCG inhibits key pathways of tumor growth by modulating signaling pathways
involved in cell proliferation, transformation, apoptosis and inflammation. Our team evaluated the efficacy and
safety of EGCG in women with symptomatic uterine fibroids in a double-blinded, placebo-controlled
randomized clinical trial (NCT 01311869). In the placebo group, fibroid volume increased (24.3%); however,
patients randomized to EGCG (800 mg/day) showed significant reduction in total fibroid volume (32.6%;
P=0.0001). These data indicate that EGCG reduces fibroid size and represents a possible non-hormonal
treatment for women with fibroids pursuing pregnancy. The objective of this study is to conduct a randomized
clinical trial to determine the effect of EGCG on fibroids and subsequent pregnancy in women seeking fertility
treatment. Our central hypothesis is that EGCG will reduce fibroid size and increase the likelihood of
pregnancy. To test this hypothesis, we propose a placebo-controlled clinical trial to evaluate live birth
outcomes for women with unexplained infertility who have uterine fibroids. Subjects will be randomized to
either oral EGCG (800mg/day) vs. placebo for up to 7 months with a 3-month run-in period followed by ovarian
stimulation and intrauterine insemination for up to 4 cycles. Aim #1: Will determine the clinical efficacy of
EGCG in a randomized study in 654 women pursuing fertility care. Aim #2: Will determine pregnancy
outcomes in women seeking fertility care treated with EGCG compared to placebo. Overview of consortium:
To meet recruitment goals, the PIs have formed a consortium as described in RFA-HD-19-022. Yale will serve
as the data coordinating center and a clinical site, Hopkins will coordinate the single IRB and be a clinical site.
Investigators at University of Illinois @ Chicago have extensive experience with EGCG and clinical trials and
will serve as lead PI. Investigators at the University of Florida have special expertise in clinical trials for fibroids
and infertility treatment with prior experience in the Reproductive Medicine Network (AMIGOS, PPCOSII).
Each institution has high volume of eligible patients and an excellent fertility center. Impact: Fibr...

## Key facts

- **NIH application ID:** 10477436
- **Project number:** 5R01HD100367-04
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Ayman Al-Hendy
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $311,640
- **Award type:** 5
- **Project period:** 2019-09-26 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10477436

## Citation

> US National Institutes of Health, RePORTER application 10477436, 3/4, University of Illinois at Chicago Clinical Site- Reproductive Medicine Collaborative Consortium: A randomized placebo-controlled trial of EGCG to improve fertility in women with uterine fibroids (5R01HD100367-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10477436. Licensed CC0.

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