Metabolic syndrome is an independent risk factor for time to complete remission of fertility-sparing treatment in atypical endometrial hyperplasia and early endometrial carcinoma patients

Diagnostic significance and predictive efficiency of metabolic risk score for fertility-sparing treatment in patients with atypical endometrial hyperplasia and early endometrial carcinoma

OBJECTIVE

This study aims to assess the impact of the metabolic risk score (MRS) on time to achieve complete remission (CR) of fertility-sparing treatments for atypical endometrial hyperplasia (AEH) and early endometrial cancer (EC) patients.

METHODS

Univariate and multivariate cox analyses were employed to identify independent risk factors affecting the time to CR with patients at our center. These factors were subsequently incorporated into receiver operator characteristic curve analysis and decision curve analysis to assess the predictive accuracy of time to CR. Additionally, Kaplan-Meier analysis was utilized to determine the cumulative CR rate for patients.

RESULTS

The 173 patients who achieved CR following fertility preservation treatment (FPT) were categorized into three subgroups based on their time to CR (<6, 6-9, >9 months). Body mass index (hazard ratio [HR]=0.20; 95% confidence interval [CI]=0.03, 0.38; p=0.026), MRS (HR=0.31; 95% CI=0.09, 0.52; p=0.005), insulin resistance (HR=1.83; 95% CI=0.05, 3.60; p=0.045), menstruation regularity (HR=3.77; 95% CI=1.91, 5.64; p=0.001), polycystic ovary syndrome (HR=-2.16; 95% CI=-4.03, -0.28; p=0.025), and histological type (HR=0.36; 95% CI=0.10, 0.62; p=0.005) were identified as risk factors for time to CR, with MRS being the independent risk factor (HR=0.29; 95% CI=0.02, 0.56; p=0.021). The inclusion of MRS significantly enhanced the predictive accuracy of time to CR (area under the curve [AUC]=0.789 for Model 1, AUC=0.862 for Model 2, p=0.032). Kaplan-Meier survival curves revealed significant differences in the cumulative CR rate among different risk groups.

CONCLUSION

MRS emerges as a novel evaluation system that substantially enhances the predictive accuracy for the time to achieve CR in AEH and early EC patients seeking fertility preservation.

Prediction of complete regression in fertility-sparing patients with endometrial cancer and apical hyperplasia: the GLOBAL model in a large Chinese cohort

BACKGROUND

Fertility preservation treatment is increasingly essential for patients with apical endometrial hyperplasia (AEH) and early endometrial cancer (EEC) worldwide. Complete regression (CR) is the main endpoint of this treatment. Accurately predicting CR and implementing appropriate interventions during treatment are crucial for these patients.

METHODS

We conducted a retrospective study involving 193 patients diagnosed with atypical AEH or EEC, enrolled from January 2012 to March 2022 at our center. We evaluated 24 clinical parameters as candidate predictors and employed LASSO regression to develop a prediction model for CR. Subsequently, a nomogram was constructed to predict CR after the treatment. We evaluated the performance of the nomogram using receiver operator characteristic (ROC) curve and decision curve analysis (DCA) to assess its predictive accuracy. Additionally, we employed cumulative curves to determine the CR rate among patients.

RESULTS

Out of the 193 patients, 173 achieved CR after undergoing fertility preservation treatment. We categorized features with similar properties and provided a list of formulas based on their coefficients. The final model, named GLOBAL (including basic information, characteristics, blood pressure, glucose metabolism, lipid metabolism, immunohistochemistry, histological type, and medication), comprised eight variables identified using LASSO regression. A nomogram incorporating these eight risk factors was developed to predict CR. The GLOBAL model exhibited an AUC of 0.907 (95% CI 0.828-0.969). Calibration plots demonstrated a favorable agreement between the predicted probability by the GLOBAL model and actual observations in the cohort. The cumulative curve analysis revealed varying cumulative CR rates among patients in the eight subgroups. Categorized analysis demonstrated significant diversity in the effects of the GLOBAL model on CR among patients with different total points (p < 0.05).

CONCLUSION

We have developed and validated a model that significantly enhances the predictive accuracy of CR in AEH and EEC patients seeking fertility preservation treatment.