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浙江大学学报（医学版）
J Zhejiang Univ (Med Sci)  2018, Vol. 47 Issue (4): 351-356    DOI: 10.3785/j.issn.1008-9292.2018.08.04
    
Establishment of a prognostic model for preterm delivery in women after cervical conization
LOU Yelin1,2(),ZHOU Yimin1,LU Hong1,LYU Weiguo3,*()
1. Department of Ultrasonography, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
2. Department of Ultrasonography, Jinhua Hospital of Zhejiang University, Jinhua 321000, Zhejiang Province, China
3. Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang Province, Department of Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
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Abstract  

Objective: To establish a prognostic model for preterm birth in women after cervical conization, and to evaluate its effectiveness. Methods: Seventy three women after cervical conization in Women's Hospital of Zhejiang University were included for this retrospective study. The influencing factors of preterm delivery were analyzed by Logistic regression analysis and a prognostic model was created. Receiver operating characteristic (ROC) curve was used for evaluation of the predictive ability of the model. Forty five women who underwent cervical conization were included for testing the validity of the model. Results: For women after cervical conization, mother's age (OR=1.20, 95%CI:1.01-1.43, P < 0.05) and cervical length during middle pregnancy (OR=0.06, 95%CI:0.01-0.21, P < 0.01) were independent predictors for preterm birth. The regression model was Logit (P)=1.408-2.903×cervical length+0.186×age. The areas under the ROC curve (AUC) of the training dataset was 0.93 (95%CI:0.87-0.99). The sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV) and accuracy with the cutoff value of -1.512 were 91.7%, 81.5%, 0.732, 68.8%, 95.7% and 84.5% respectively. The AUC of the testing dataset was 0.94 (95%CI:0.86-1.00). The sensitivity, specificity, Youden index, PPV, NPV and accuracy with the cutoff value of -0.099 were 92.9%, 90.3%, 0.832, 81.3%, 96.5% and 91.1%, respectively. Conclusion: The model based on the age and cervical length during middle pregnancy can effectively predict preterm delivery in pregnant women after cervical conization.

Key words： Cervical intraepithelial neoplasia/surgery      Uterine cervical neoplasms/surgery      Hysterectomy      Postoperative period      Premature birth      Forecasting      Models, theoretical      Retrospective studies     
Received: 05 July 2018      Published: 04 December 2018
CLC:  R711.74  
Corresponding Authors: LYU Weiguo     E-mail: snowflack100@163.com;lbwg@zju.edu.cn
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LOU Yelin
ZHOU Yimin
LU Hong
LYU Weiguo
Cite this article:

LOU Yelin,ZHOU Yimin,LU Hong,LYU Weiguo. Establishment of a prognostic model for preterm delivery in women after cervical conization. J Zhejiang Univ (Med Sci), 2018, 47(4): 351-356.

URL:

http://www.zjujournals.com/med/10.3785/j.issn.1008-9292.2018.08.04     OR     http://www.zjujournals.com/med/Y2018/V47/I4/351


宫颈锥切术后孕妇早产预测模型的建立

目的: 建立宫颈锥切术后孕妇发生早产的预测模型，并对模型的临床价值进行初步评估。方法: 回顾性分析浙江大学医学院附属妇产科医院有宫颈锥切术史的73名孕妇妊娠病历资料，以此为训练数据集采用Logistic回归分析筛选早产的影响因素并建立预测模型。选择宫颈锥切术后45名孕妇作为验证数据集，采用ROC曲线进行宫颈锥切术后孕妇早产预测模型的临床价值评估。结果: 对于宫颈锥切术后孕妇，年龄（OR=1.20，95% CI：1.01~1.43，P < 0.05）和孕中期子宫颈长度（OR=0.06，95% CI：0.01~0.21，P < 0.01）是早产的独立预测因素。通过Logistic回归分析建立回归模型Logit（P）=1.408-2.903×孕中期子宫颈长度+0.186×孕妇年龄。训练数据集使用构建的模型预测早产的AUC值为0.93（95%CI：0.87~0.99），该模型预测早产的最佳阈值为-1.512，敏感度、特异度、约登指数、阳性预测值、阴性预测值、准确率分别为91.7%、81.5%、0.732、68.8%、95.7%、84.5%；测试数据集使用构建的模型预测早产的AUC值为0.94（95%CI：0.86~1.00），当最佳阈值为-0.099时，模型预测早产的敏感度、特异度、约登指数、阳性预测值、阴性预测值、准确率分别为92.9%、90.3%、0.832、81.3%、96.5%、91.1%。结论: 以宫颈锥切术后孕妇的年龄和孕中期子宫颈长度建立的早产预测模型可以较准确地预测早产的发生，值得临床进一步研究。


关键词： 宫颈上皮内瘤样病变/外科学,  宫颈肿瘤/外科学,  子宫切除术,  手术后期间,  早产,  预测,  模型, 理论,  回顾性研究 
[n(%)或M(Q1~Q3)]
变量 ＜37周分娩(n=30) ≥37周分娩(n=54) OR(95%CI) P值
手术方法 环形电刀切除术 15(50.0) 38(70.4) 1 —
         冷刀锥切术 15(50.0) 16(29.6) 2.38(0.94~5.98) ＞0.05
子宫颈组织病理级别 CINⅠ 5(16.7) 21(38.9) 1 —
              CINⅡ 10(33.3) 14(25.9) 2.86(0.80~10.20) ＞0.05
              CINⅢ 15(50.0) 19(35.2) 3.00(0.92~9.83) ＞0.05
孕妇年龄(岁) 37.0(30.0~39.8) 30(29.0~32.3) 1.18(1.05~1.32) ＜0.01
孕次 3(2~4) 2(1~3) 1.31(0.97~1.77) ＞0.05
产次 0(0~1) 0(0~0) 1.94(0.92~4.07) ＞0.05
孕前体质指数(kg/m2) 19.7(18.8~22.2) 20.5(19.1~22.3) 0.96(0.82~1.13) ＞0.05
辅助生殖次数 6(20.0) 4(7.4) 3.13(0.81~12.12) ＞0.05
孕期风险因素* 15(50.0) 27(50.0) 1.00(0.41~2.44) ＞0.05
孕中期子宫颈长度(mm) 2(1.8~2.7) 3.4(3.0~3.7) 0.05(0.01~0.17) < 0.01
“—”无相关数据；CIN：宫颈上皮内瘤变.*包括妊娠期糖尿病、妊娠期肝内胆汁淤积症、高血压、乙型肝炎病毒阳性和羊水偏少.
Tab 1 Univariate logistic regression analysis of related factors of preterm delivery after cervical conization
变量 OR值(95%CI) P值 回归系数 标准误 χ2值
孕妇年龄 1.20(1.01~1.43) ＜0.05 0.186 0.089 4.355
孕中期子宫颈长度 0.06(0.01~0.21) < 0.01 -2.903 0.690 17.687
Tab 2 Multivariate logistic regression analysis of related factors of preterm delivery after cervical conization
Fig 1 ROC curves of the risk of preterm delivery predicted by the established model
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