Status and related factors of postoperative recurrence of ovarian endometriosis: a cross-sectional study of 874 cases

Influencing factors and prediction model construction for recurrence in patients with ovarian endometriosis after laparoscopic conservative surgery

OBJECTIVE

To investigate the factors influencing recurrence following laparoscopic conservative surgery in patients with ovarian endometriosis (OEM) and to develop a predictive model.

METHODS

In this retrospective study, the clinical data from 212 OEM patients who underwent laparoscopic conservative surgery at Suzhou Ninth People's Hospital from May 2013 to December 2021 were meticulously reviewed. According to disease recurrence over a 2-year follow-up period, the patients were divided into a recurrence group and a non-recurrence group. Univariate and multivariate logistic regression analyses were performed to identify factors associated with postoperative recurrence in OEM patients. A nomogram prediction model for postoperative recurrence in OEM patients was constructed using R 3.4.3 software. The discriminative power of the model was assessed using the area under the receiver operating characteristic (ROC) curve (AUC), with goodness of fit evaluated using the H-L goodness-of-fit test and Bootstrap method (self-sampling method). Clinical net benefit was analyzed through decision curve analysis.

RESULTS

Over a two-year follow-up, 36 cases of recurrence were observed, yielding a recurrence rate of 16.98%. Bilateral cysts (OR = 2.257, P = 0.005), high r-ASRM stage (OR = 2.651, P = 0.001), and elevated postoperative TNF-α levels (OR = 3.607, P = 0.004) were identified as risk factors for recurrence after laparoscopic conservative surgery in patients with OEM, while older age (OR = 0.566, P = 0.018) and postoperative adjuvant medication (OR = 0.509, P = 0.016) were protective factors. The nomogram prediction model, based on the above indicators, had an AUC of 0.895 for postoperative recurrence risk in OEM patients, with no overfitting phenomenon indicated by the goodness-of-fit test (χ2 = 1.786, P = 0.987). The Bootstrap validation (1000 samples) showed an average absolute error of 0.018 between predicted and actual probabilities. Decision curve analysis showed that the model effectively predicted a clinically relevant net benefit for postoperative recurrence risk.

CONCLUSION

A nomogram prediction model incorporating age, cyst distribution, r-ASRM staging, postoperative TNF-α levels, and postoperative adjuvant drugs effectively assesses the recurrence risk in OEM patients.

Exploration of Diagnostic Deubiquitinating Enzymes in Endometriosis and Its Immune Infiltration

The mechanism involved in the pathogenesis of endometriosis is poorly understood. The purpose of this study is to identify key deubiquitinating enzymes (DUBs) for endometriosis diagnosis and elucidate the possible mechanism, offering novel insights for noninvasive early diagnosis and treatment. Four gene expression datasets were employed from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) between endometriosis and normal controls. GO and KEGG pathways were performed for enrichment analysis. Calibration curves, ROC, DCA, and clinical impact curves verified the clinical usefulness of the nomogram model. In addition, the ssGSEA method was conducted to estimate 23 types of immune cells. A specific DUB gene signature was constructed with Lasso regression, univariate logistic regression, and SVM analysis. RT-qPCR validated the expression of biomarkers. A total of 85 endometriosis-related DUBs were identified in the eutopic endometrium. Among them, 20 DUBs were found to be correlated with the severity of endometriosis. A diagnostic risk model based on five DUB-related genes (USP21, USP48, ZRANB1, COPS5, and EIF3F) was developed using lasso-cox regression analysis. The nomogram model exhibited a strong predictive ability to diagnose endometriosis. KEGG analysis revealed that ubiquitin-mediated proteolysis was activated in patients suffering from severe symptoms. Analysis of immune cell infiltration revealed a positive correlation between USP21 and multiple immune cells in the eutopic endometrium. However, EIF3F showed an opposite relationship. Dysregulation of DUBs was related to the immune microenvironment in endometriosis. Results from RT-qPCR confirmed the expression of DEGs in clinical samples. In summary, the diagnostic model for endometriosis constructed using five differentially expressed DUB genes demonstrates strong diagnostic capability, suggesting that these genes could serve as potential candidate biomarkers and therapeutic targets.

Perioperative hormone treatment of endometriosis

PURPOSE OF REVIEW

The use of hormonally suppressive medication to reduce levels of reproductive hormones around the time of surgery is widely used in the management of endometriosis. This review summarizes the current evidence concerning the perioperative use of hormonal treatment in the management of endometriosis.

RECENT FINDINGS

European Society of Human Reproduction and Embryology (ESHRE) guidanceSurgical Outcomes and Complications of Laparoscopic Hysterectomy for Endometriosis: A Multicentre Cohort StudyPre and postsurgical medical therapy for endometriosis surgery. Cochrane 2020Postoperative hormonal treatment for prevention of endometrioma recurrence after ovarian cystectomy: a systematic review and network meta-analysis. BJOG 2021.

SUMMARY

The literature highlights the importance of hormonal treatment for symptom relief, reduced surgical complications and postoperative benefits, including a reduction in pain, disease recurrence and improved pregnancy rates. The treatment of endometriosis can be broadly categorized into medical, commonly using hormonal suppression medications and surgical, in which endometriosis tissue is excised or ablated. This review aims to outline current management strategies and examines the relationship between the two treatment modalities.