子宫动脉栓塞术治疗子宫腺肌病痛经疗效的相关影响因素及疗效预测模型的构建与验证

Analysis of related factors on effects of uterine artery embolization in the treatment of dysmenorrhea of adenomyosis and the construction and validation of prediction model

目的：探讨子宫动脉栓塞术（UAE）治疗子宫腺肌病痛经疗效的相关影响因素，构建并验证疗效预测模型。方法回顾性分析1999年6月至2009年12月在广州市第一人民医院及南方医科大学南方医院就诊、有痛经症状的子宫腺肌病患者127例的临床资料，以痛经的改善情况作为疗效评价标准，分析影响疗效的相关因素。结合人工神经网络理论构建UAE治疗子宫腺肌病痛经疗效预测模型，使用受试者工作特征（ROC）曲线评价模型的预测效能并计算最佳效能截断点；选择2010年1月至2014年11月在南方医科大学南方医院就诊的子宫腺肌病患者68例，对构建的疗效预测模型进行验证。结果（1）UAE治疗子宫腺肌病痛经的有效率为77.2%（98/127）。（2）年龄是UAE治疗子宫腺肌病有效的保护性因素（HR=1.129，P=0.026），在本研究范围内年龄越大，UAE治疗的有效率越高。（3）子宫动脉卵巢支显影情况是UAE治疗有效的危险因素（HR=0.460，P=0.020），双侧子宫动脉卵巢支均不显影的患者治疗有效率为89.7%（35/39），单侧子宫动脉卵巢支显影的患者治疗有效率为84.1%（37/44），双侧子宫动脉卵巢支均显影患者的治疗有效率为59.1%（26/44）。（4）子宫腺肌病血液供应（血供）类型是UAE治疗有效的危险因素（HR=0.313，P=0.001），双侧子宫动脉供血为主型的患者治疗有效率为93.5%（43/46），双侧子宫动脉供血均衡型的患者治疗有效率为78.0%（39/50），单侧子宫动脉供血为主型的患者治疗有效率为51.6%（16/31）。（5）成功构建了UAE治疗子宫腺肌病痛经疗效人工神经网络预测模型，其ROC曲线下面积为0.808，最佳效能截断点为0.66913，预测模型的实际验证中，敏感度为96.5%，特异度为81.8%，阳性预测值为96.5%，阴性预测值为81.8%，总准确率为94.1%。结论（1）年龄、子宫动脉卵巢支显影情况以及子宫腺肌病血供类型是UAE治疗子宫腺肌病痛经疗效的独立预测因素。（2）本研究构建的UAE治疗子宫腺肌病痛经疗效人工神经网络预测模型具有满意的真实性以及预测准确率。

Objective To investigate the related factors on effects of uterine artery embolization （UAE） in the treatment of dysmenorrhea in patients with adenomyosis, and to construct and validate the efficacy prediction model. Methods A total of 127 cases of adenomyosis patients with symptoms of dysmenorrhea in Guangzhou No.1 People′s Hospital and Nanfang Hospital of Southern Medical University from June 1999 to December 2009 were reviewed. The evaluation standard was to improve the degree of＆nbsp;dysmenorrhea, the related factors of efficacy were analysed. Combined with artificial neural network theory, the effect prediction model was constructed, and the effectiveness of the model was evaluated using receiver operating characteristic （ROC） curve, and the effectiveness of the cut-off point was calculated. The model was validated by 68 cases of patients with adenomyosis in the Nanfang Hospital from January 2010 to November 2014. Results （1） In 127 cases of dysmenorrhea patients, UAE treatment was effective in 98 cases, effective rate was 77.2% （98/127）. （2） Age was an independent predictor of effective UAE treatment （HR=1.129, P=0.026）;in the range of this study, the greater the age, the higher the UAE treatment efficiency. （3） The developing situation of ovary branches of uterine artery was an independent predictor of effective UAE treatment （HR=0.460, P=0.020）, the efficiency of patients whose intraoperative bilateral uterine artery ovarian branch did not develop was 89.7%（35/39）, the efficiency of patients whose unilateral uterine artery ovarian branch was developing was 84.1% （37/44） and the efficiency of patients whose bilateral uterine artery ovarian branch were developing was 59.1% （26/44）. （4） Blood supply of adenomyosisis was an independent predictor of effective UAE treatment （HR=0.313, P=0.001）. Type Ⅰ （bilateral predominated） patients, efficiency was 93.5%（43/46）;typeⅡ（bilateral balanced） patients, efficiency was 78.0%（39/50）;type Ⅲ （unilateral predominated） patients, efficiency was 51.6% （16/31）. （5） UAE for the treatment of adenomyosis efficacy of artificial neural network prediction model was constructed, the model′s area under the ROC curve was 0.808, the optimal cut-off point was 0.669 13. Actual verification of the model, sensitivity was 96.5%, specificity was 81.8%, positive predictive value was 96.5%and negative predictive value was 81.8%, the total accuracy was 94.1%. Conclusions （1） Age, the developing situation of ovary branches and blood supply of adenomyosis are the independent predictors of effective UAE treatment. （2） The artificial neural network prediction model is satisfied with the accuracy and the accuracy of prediction.