Developing Preoperative Nomograms to Predict Any-Stage and Stage III-IV Endometriosis in Infertile Women

Frontiers in Medicine

article

Zaixin Guo¹  Penghui Feng¹  Xiaohan Chen¹  Ruiyi Tang¹  Qi Yu¹ 

[1] Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences

关键词: endometriosis;    infertility;    logistic regression;    nomogram;    predictive model;   

DOI  :  10.3389/fmed.2020.570483

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Study objective: To generate and validate nomograms to predict any-stage and stage III-IV endometriosis before surgery in infertile women. Design: A single center retrospective cohort study. Setting: University affiliated hospital. Patients: Infertile patients ( n = 1,016) who underwent reproductive surgery between July 1, 2016 and June 30, 2019. Interventions: None. Main outcome measurements: We randomly selected 2/3 of the included patients (667 patients, training sample) to analyze and generate predictive models and validated the models on the remaining patients (339 patients, validation sample). A multivariate logistic regression model was used with the training sample to select variables using a back stepwise procedure. Nomograms to predict any-stage and stage III–IV endometriosis were constructed separately. The discriminations and calibrations of both nomograms were tested on the overall population and a subgroup without endometrioma diagnosed on transvaginal sonography (TVS) of training and validation samples. The impact of different variables in these models was evaluated. Results: There were 377 (55.7%) women in the training sample and 196 (57.8%) in the validation sample who were diagnosed with endometriosis. The nomogram predicting any-stage endometriosis had an area under the curve (AUC) of 0.760 for the training sample and 0.744 for the validation sample, with favorable calibrations in the overall population. However, the performance was significantly decreased in patients without endometrioma on TVS, with an AUC of 0.726 in the training sample and 0.694 in the validation sample. Similarly, the nomogram predicting stage III–IV endometriosis had an AUC of 0.833 and 0.793 for the training and validation samples, respectively, as well as a favorable calibration. However, the performance of the nomogram on patients without endometrioma on TVS was poor. Endometrioma on TVS strongly predicted both any stage and stage III–IV endometriosis on both samples. Conclusion: We developed nomograms to predict any-stage and stage III–IV endometriosis but their performance were significantly decreased in patients without endometrioma on TVS. Endometrioma on TVS strongly predicted any and III–IV stage endometriosis in both sample groups. Therefore, we recommend that this study be used as encouragement to advance the utilization of advanced imaging for endometriosis for better clinical prognosis.

【 授权许可】

CC BY