The Development of Predictive Nomogram of Recurrence for Patients With Endometrioma After Cystectomy Who Were Younger Than 45 Years Old and Received Postoperative Therapy

Zhiyue Gu; Xiaoyan Li; Jinghua Shi; Yushi Wu; Jing Zhang; Chenyu Zhang; Hailan Yan; Jinhua Leng

doi:10.3389/fmed.2022.872481

The Development of Predictive Nomogram of Recurrence for Patients With Endometrioma After Cystectomy Who Were Younger Than 45 Years Old and Received Postoperative Therapy

Front Med (Lausanne). 2022 Jun 9:9:872481. doi: 10.3389/fmed.2022.872481. eCollection 2022.

Authors

Zhiyue Gu^{1

2}, Xiaoyan Li^{1

2}, Jinghua Shi^{1

2}, Yushi Wu^{1

2}, Jing Zhang^{1

2}, Chenyu Zhang^{1

2}, Hailan Yan^{1

2}, Jinhua Leng^{1

2}

Affiliations

¹ Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
² National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China.

Abstract

Objective: This study aimed to establish an effective prognostic nomogram for the postoperative recurrence of endometrioma or endometriosis-related pain for patients with endometrioma after long-term follow-up, who were younger than 45 years old and received postoperative therapy.

Methods: The predictive nomogram was based on 323 patients who underwent cystectomy for endometrioma at Perking Union Medical College Hospital from January 2009 to April 2013, and the last follow-up occurred in September 2018. We collected information on all included patients, including preoperative data, intraoperative data, and long-term follow-up data after surgery. The Cox proportional hazards regression model was used to evaluate the prognostic effects of multiple clinical parameters on recurrence. The survival curve was depicted based on Kaplan-Meier method and compared by log-rank method. The Index of concordance (C-index) and calibration curves were used to access the discrimination ability and predictive accuracy of the nomogram respectively, and the results were further validated via bootstrap resampling. In addition, calculating the area under the curve (AUC) via risk scores of patients aimed to further access the prediction ability of the model.

Results: On multivariate analysis of derivation cohort, independent factors for recurrence such as dysmenorrhea degree, sum of both cyst diameters, presence of adenomyosis, and other essential factors for recurrence such as age at surgery, presence of uterine fibroids were all selected into the nomogram. The C-index of the nomogram for predicting recurrence was 0.683 (95% CI, 0.610- 0.755). The calibration curve for probability of recurrence for 7 years and 9 years showed great agreement between prediction by nomogram and actual observation. Furthermore, the AUCs of risk score for 7-year and 9-year were 0.680 and 0.790 respectively.

Conclusion: This research tried to develop the predictive nomogram of recurrence for patients with endometrioma after cystectomy. The C-index and calibration curve of nomogram, as well as the AUC of the nomogram was potential to predict the recurrence probability. In addition, this predictive nomogram needs external data sets to further validate its prognostic accuracy in the future.

Keywords: endometrioma; endometriosis; nomogram; predictive model; recurrence.