BMJ open · 2025
Predicting pain reduction following laparoscopic surgery for endometriosis: a retrospective cohort study using UK national and research databases.
СтатьяНазвание и аннотация: Перевод в очереди
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Mustard Connor, Snell Kym, Lee Kim May, Pike Cleo, Bhogal Sharandeep, Horne Andrew, Dodds Julie, Allotey John, Rivas Carol, Ball Elizabeth
Аннотация
OBJECTIVE: To develop and validate models to predict which endometriosis patients are likely to experience pain reduction following therapeutic laparoscopy using intraoperative findings and patient characteristics.
DESIGN: A retrospective secondary data analysis with patient workshops.
SETTING: Analysis of a UK nationwide, specialist centre, surgical database (British Society for Gynaecological Endoscopy, BSGE) (2013-2019, N=9171) and two research databases, MEDAL (2011-2013, N=667) and LUNA (1998-2005, N=592) for exploratory analyses and external validation.
PARTICIPANTS: Database patients had laparoscopically confirmed (BSGE) or clinically suspected endometriosis (MEDAL, LUNA) and ranged from 16 to 65 years. Patient workshops included UK-wide endometriosis patients from the community, secondary care doctors and endometriosis nurses.
PRIMARY AND SECONDARY OUTCOME MEASURES: Following model development and internal validation, primary outcome measures included model performance statistics for discrimination (C-statistic) and calibration (calibration slope and calibration-in-the-large) for pain-improvement models for each of the five clinically meaningful pain domains. Secondary outcome measures included performance statistics for externally validated models and net benefit (using decision curve analysis).
RESULTS: Following internal validation for dyspareunia (pain during sexual intercourse), non-cyclical pelvic pain (NPP), dyschezia (painful defecation) and quality of life our models showed good discrimination ability with C-statistics of 0.768, 0.750, 0.808 and 0.792, respectively. Significant increases in odds of pain relief were associated with trying to conceive for less than 18 months, any treated endometriosis of the ovary or uterosacral ligament or hysterectomy at the time of laparoscopy. For those models for which sufficient data were available to do external validation, dyspareunia and NPP showed good ability to predict pain reduction following surgery with C-statistics of 0.759 and 0.741, respectively, but after external validation only the model for dyspareunia good discriminatory ability (C-statistic=0.718). Despite this, decision curve analysis indicated some net benefit for all externally validated models.
CONCLUSIONS: Clinical prediction models can help identify women who will experience pain reduction after therapeutic laparoscopy, but more work is required to externally validate the current models. Removal of ovarian and utero-sacral ligament endometriosis appears to convey pain relief after surgery, whereas removal of superficial peritoneal endometriosis does not.
DESIGN: A retrospective secondary data analysis with patient workshops.
SETTING: Analysis of a UK nationwide, specialist centre, surgical database (British Society for Gynaecological Endoscopy, BSGE) (2013-2019, N=9171) and two research databases, MEDAL (2011-2013, N=667) and LUNA (1998-2005, N=592) for exploratory analyses and external validation.
PARTICIPANTS: Database patients had laparoscopically confirmed (BSGE) or clinically suspected endometriosis (MEDAL, LUNA) and ranged from 16 to 65 years. Patient workshops included UK-wide endometriosis patients from the community, secondary care doctors and endometriosis nurses.
PRIMARY AND SECONDARY OUTCOME MEASURES: Following model development and internal validation, primary outcome measures included model performance statistics for discrimination (C-statistic) and calibration (calibration slope and calibration-in-the-large) for pain-improvement models for each of the five clinically meaningful pain domains. Secondary outcome measures included performance statistics for externally validated models and net benefit (using decision curve analysis).
RESULTS: Following internal validation for dyspareunia (pain during sexual intercourse), non-cyclical pelvic pain (NPP), dyschezia (painful defecation) and quality of life our models showed good discrimination ability with C-statistics of 0.768, 0.750, 0.808 and 0.792, respectively. Significant increases in odds of pain relief were associated with trying to conceive for less than 18 months, any treated endometriosis of the ovary or uterosacral ligament or hysterectomy at the time of laparoscopy. For those models for which sufficient data were available to do external validation, dyspareunia and NPP showed good ability to predict pain reduction following surgery with C-statistics of 0.759 and 0.741, respectively, but after external validation only the model for dyspareunia good discriminatory ability (C-statistic=0.718). Despite this, decision curve analysis indicated some net benefit for all externally validated models.
CONCLUSIONS: Clinical prediction models can help identify women who will experience pain reduction after therapeutic laparoscopy, but more work is required to externally validate the current models. Removal of ovarian and utero-sacral ligament endometriosis appears to convey pain relief after surgery, whereas removal of superficial peritoneal endometriosis does not.