Mustard Connor, Snell Kym, Lee Kim May, Pike Cleo, Bhogal Sharandeep, Horne Andrew, Dodds Julie, Allotey John, Rivas Carol, Ball Elizabeth
Operational Excellence, Maple, Toronto, Ontario, Canada
Public Health, Epidemiology & Biostatistics, University of Birmingham, Birmingham, UK.
BMJ Open. 2025 Aug 27;15(8):e099374. doi: 10.1136/bmjopen-2025-099374.
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.
A retrospective secondary data analysis with patient workshops.
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.
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.
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).
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.
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.
利用术中发现和患者特征,开发并验证用于预测哪些子宫内膜异位症患者在治疗性腹腔镜检查后可能疼痛减轻的模型。
一项带有患者研讨会的回顾性二次数据分析。
对英国全国性的专科中心手术数据库(英国妇科内镜学会,BSGE)(2013 - 2019年,N = 9171)以及两个研究数据库MEDAL(2011 - 2013年,N = 667)和LUNA(1998 - 2005年,N = 592)进行分析,以进行探索性分析和外部验证。
数据库中的患者经腹腔镜确诊(BSGE)或临床怀疑患有子宫内膜异位症(MEDAL、LUNA),年龄在16至65岁之间。患者研讨会包括来自英国各地社区的子宫内膜异位症患者、二级护理医生和子宫内膜异位症护士。
在模型开发和内部验证之后,主要结局指标包括针对五个具有临床意义的疼痛领域中每个领域的疼痛改善模型的区分度(C统计量)和校准(校准斜率和整体校准)的模型性能统计数据。次要结局指标包括外部验证模型的性能统计数据和净效益(使用决策曲线分析)。
在对性交困难(性交时疼痛)、非周期性盆腔疼痛(NPP)、排便困难(排便疼痛)和生活质量进行内部验证后,我们的模型显示出良好的区分能力,C统计量分别为0.768、0.750、0.808和0.792。疼痛缓解几率的显著增加与尝试受孕时间少于18个月、腹腔镜检查时卵巢或子宫骶韧带的任何已治疗的子宫内膜异位症或子宫切除术有关。对于有足够数据进行外部验证的那些模型,性交困难和NPP显示出良好的预测手术疼痛减轻的能力,C统计量分别为0.759和0.741,但在外部验证后,只有性交困难模型具有良好的区分能力(C统计量 = 0.718)。尽管如此,决策曲线分析表明所有外部验证模型都有一定的净效益。
临床预测模型有助于识别在治疗性腹腔镜检查后疼痛会减轻的女性,但需要更多工作对当前模型进行外部验证。切除卵巢和子宫骶韧带子宫内膜异位症似乎在手术后能缓解疼痛,而切除浅表腹膜子宫内膜异位症则不能。