Predicting disease recurrence in patients with endometriosis: an observational study

Abstract

Background: Despite surgical and pharmacological interventions, endometriosis can recur. Reliable information regarding risk of recurrence following a first diagnosis is scant. The aim of this study was to examine clinical and survey data in the setting of disease recurrence to identify predictors of risk of endometriosis recurrence.

Methods: This observational study reviewed data from 794 patients having surgery for pelvic pain or endometriosis. Patients were stratified into two analytic groups based on self-reported or surgically confirmed recurrent endometriosis. Statistical analyses included univariate, followed by multivariate logistic regression to identify risk factors of recurrence, with least absolute shrinkage and selection operator (Lasso) regularisation. Risk-calibrated Supersparse Linear Integer Models (RiskSLIM) and survival analyses (with Lasso) were undertaken to identify predictive features of recurrence.

Results: Several significant features were repeatedly identified in association with recurrence, including adhesions, high rASRM score, deep disease, bowel lesions, adenomyosis, emergency room attendance for pelvic pain, younger age at menarche, higher gravidity, high blood pressure and older age. In the surgically confirmed group, with a score of 5, the RiskSLIM method was able to predict the risk of recurrence (compared to a single diagnosis) at 95.3% and included adenomyosis and adhesions in the model. Survival analysis further highlighted bowel lesions, adhesions and adenomyosis.

Conclusions: Following an initial diagnosis of endometriosis, clinical decision-making regarding disease management should take into consideration the presence of bowel lesions, adhesions and adenomyosis, which increase the risk of endometriosis recurrence.

Keywords: Endometriosis; Endometriosis recurrence; Recurrent endometriosis; Reoperation; Repeat surgery.

Fig. 1

Flow chart illustrating the selection of participants in each analytic cohort. *There were n = 794 patients for inclusion in this study. Each analytic cohort was conducted independently; self-reported analysis or surgically confirmed analysis, and subjects crossed over into both cohorts

Fig. 2

RiskSLIM scores to assess predicted risk of recurrent endometriosis in the self-reported endometriosis analysis group. a Tally of points and resulting scores for the various combinations of present features in the recurrent endometriosis versus single diagnosis of endometriosis comparison. Variables were selected to maximise the 5 cross-validation (CV) test AUC. The final score can sit between −2 and 3, with a predicted risk of recurrence at 4.7% for a score of −2 and 88.1% for a high score of 3. d Points and scores for the recurrent endometriosis versus non-endometriosis control comparison. The final score can also sit between −2 and 3, with a predicted risk of recurrence at 11.9% for a score of −2 and 95.3% for a high score of 3. b and e Calibration reliability graphs with observed risk (y-axis) and predicated risk (x-axis). The final model is shown in black (with risk scores in black circles), and the 5-CV models on test data shown in grey. The 45° dashed grey line represents a perfect risk calibration. c and f Receiver operating characteristic (ROC) curve with true positive rate (y-axis) and false positive rate (x-axis). The final model is shown in black and the 5-CV models on test data shown in grey. Area under the ROC curve (AUC) for the 5-CV test and the final model are illustrated on the bottom right of the ROC curve diagram

Fig. 3

RiskSLIM scores to assess predicted risk of recurrent endometriosis in the surgically confirmed analysis group. a Tally of points and resulting scores for the various combinations of present features in the recurrent endometriosis versus single diagnosis of endometriosis comparison. Variables were selected to maximise the 5 cross-validation (CV) test AUC. The final score sat between −1 and 5, with a predicted risk of recurrence at 4.7% for a score of −1 and 95.3% for a high score of 5. d Points and scores for the recurrent endometriosis versus non-endometriosis control comparison. The final score sat between −2 and 6, with a predicted risk of recurrence at 1.8% for a score of −2 and 98.2% for a high score of 6. b and e Calibration reliability graphs with observed risk (y-axis) and predicated risk (x-axis). The final model is shown in black (with risk scores in black circles), and the 5-CV models on test data shown in grey. The 45° dashed grey line represents a perfect risk calibration. c and f Receiver operating characteristic (ROC) curve with true positive rate (y-axis) and false positive rate (x-axis). The final model is shown in black and the 5-CV models on test data shown in grey. Area under the ROC curve (AUC) for the 5-CV test and the final model are illustrated on the bottom right of the ROC curve diagram

Fig. 4

Kaplan-Meier curves for the surgically confirmed endometriosis recurrence group. Survival analysis was performed on data from patients with confirmed endometriosis (in the surgically confirmed analysis group). a Presence of lesions on the bowel, b self-reported diagnosis of adenomyosis and c presence of adhesions. a–c Red = no (variable not present), blue = yes (variable present). Vertical dashed line placed at 2 years and 5 years (time). Kaplan-Meier p values are included on the graph (bottom left)