Understanding the Link Between PCOS, Endometrial Hyperplasia, and Metabolic Health

Understanding the Link Between PCOS, Endometrial Hyperplasia, and Metabolic Health

November 30, 2024 Catherine Williams - Chief Editor Tech

Introduction

Polycystic ovary syndrome (PCOS) affects 6% to 10% of women of childbearing age. It disrupts reproductive health, often leading to infertility in 70-80% of affected women. PCOS causes chronic anovulation, resulting in prolonged estrogen exposure without progesterone. This increases the risk of endometrial hyperplasia (EH) and endometrial cancer (EC). About 30% of PCOS patients develop EH, and their chance of EC is 3 to 10 times higher than healthy women. EH can decrease fertility rates and lead to pregnancy complications.

Insulin resistance plays a key role in PCOS. Body Mass Index (BMI) does not differentiate between fat and muscle. Studies show that PCOS patients with normal weight but central obesity are at high risk for insulin resistance and metabolic disorders. These factors may also affect the endometrium, complicating the PCOS scenario.

This study examines body composition, glucose and lipid metabolism, and uric acid levels in patients. The goal is to assess the risk of EH in PCOS and help protect fertility in these women.

Materials and Method

Study Design and Patients

This is a retrospective study approved by the ethics committee at Tianjin Medical University General Hospital, collecting data from June 1, 2021, to March 1, 2024.

Inclusion Criteria

  1. Pathological diagnosis of EH without atypia, AH, or normal endometrial phases.
  2. Body composition analysis conducted at our hospital.
  3. Fasting blood glucose, insulin, lipid, and uric acid tests completed.
  4. Absence of malignant tumors or serious comorbidities.

Exclusion Criteria

  1. Current hormone therapy.
  2. Missing clinical and pathological data.

Sample Size Calculation

For this retrospective case-control study, we calculated a minimum sample size of 74 based on the prevalence of EH in women.

Diagnostic Criteria for PCOS

PCOS diagnosis requires:

  1. Rare or absent ovulation accompanied by abnormal menstruation.
  2. Symptoms of hyperandrogenism.
  3. Ultrasound findings of polycystic ovaries.

Data Collection

General clinical data included age and ultrasound measurements. Anthropometric data included height and circumferences. Body composition was analyzed using the In Body 270 device. Laboratory tests measured fasting blood glucose, insulin, lipids, and uric acid from peripheral blood.

Statistical Methods

We used SPSS, R, and GraphPad Prism for statistical analysis. One-way ANOVA compared continuous variables, and logistic regression identified significant risk factors.

Results

We studied 232 patients divided into four groups:

  • Group A: Non-PCOS with normal endometrium (118 patients).
  • Group B: PCOS with normal endometrium (34 patients).
  • Group C: Non-PCOS with EH (38 patients).
  • Group D: PCOS with EH (42 patients).

Weight and BMI were significantly higher in Group D than in other groups. Body composition revealed that Group D had increased fat and muscle mass compared to non-PCOS groups.

Multivariate Regression Analysis

FMI was identified as an independent risk factor for EH in PCOS patients. Increased age acted as a protective factor. FMI successfully predicted EH in PCOS patients with an AUC of 0.82.

Correlation Analysis

FMI exhibited positive correlations with fasting glucose, insulin, HOMA-IR, lipids, and uric acid levels in PCOS patients.

Discussion

The prevalence of EH in PCOS ranges from 1% to 48.8%. The combination of obesity and insulin resistance significantly raises the risk of EH. This study showed that PCOS patients with EH exhibited distinctive body fat distributions compared to healthy women.

Insulin resistance and hyperinsulinemia increase androgen levels, affecting endometrial health. The TG/HDL ratio serves as a marker for insulin resistance. High triglycerides are associated with fat accumulation, impacting insulin signaling.

Limitations

This was a single-center retrospective study. We implemented strict criteria to minimize selection bias but could not eliminate it completely. Future research should involve multiple centers and large samples to enhance reliability.

Ethics Approval

Ethics approval obtained.

Funding

The study received support from multiple research programs, with no effect on study design or outcomes.

Disclosure

No conflict of interest reported.

Data Sharing Statement

Data is available from corresponding authors if necessary.