| 李沛,刘志科,赵厚宇,刘学洋,沈鹏,林鸿波,詹思延,孙凤.基于巢式病例对照设计开发宫颈癌发病风险预测模型[J].Chinese journal of Epidemiology,2023,44(7):1139-1145 |
| 基于巢式病例对照设计开发宫颈癌发病风险预测模型 |
| A risk prediction model of cervical cancer developed based on nested case-control design |
| Received:December 23, 2022 |
| DOI：10.3760/cma.j.cn112338-20221223-01079 |
| KeyWord: 宫颈癌 预测模型 巢式病例对照 |
| English Key Word: Cervical cancer Prediction model Nested case-control study |
| FundProject: |
| Author Name | Affiliation | E-mail | | Li Pei | Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | | Liu Zhike | Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | | Zhao Houyu | Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | | Liu Xueyang | National Engineering Research Center for Software Engineering, Peking University, Beijing 100871, China | | | Shen Peng | Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315100, China | | | Lin Hongbo | Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315100, China | lin73160@163.com | | Zhan Siyan | Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | | Sun Feng | Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | sunfeng@bjmu.edu.cn |
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| Abstract: |
| 目的 基于宁波市鄞州区域健康信息平台，使用巢式病例对照的研究设计构建宫颈癌发病风险预测模型。方法 2018年10月31日前建档的25~75岁无宫颈癌史的常住女性中，至少随访3年的过程中新发生的宫颈癌患者纳入病例组，以1∶10的比例匹配对照组，预测因子提取时间限制在结局发生前。变量选择采用Lasso-logistic回归，选择β不为0的变量拟合logistic回归模型并用Bootstrap法进行内部验证。模型的区分度用受试者工作曲线下面积（AUROC）评价，校准度用校准曲线图和Hosmer-Lemeshow检验来评价。结果 最终模型纳入的预测因子包括年龄、吸烟状况、宫颈炎史、HPV检测情况和液基薄层细胞检查情况。内部验证500次Bootstrap的AUROC为0.740（95%CI：0.739~0.740），校准曲线与理想曲线几乎重合，Hosmer-Lemeshow检验P=0.991，模型区分度和校准度均较好。结论 本研究开发了一个简便且实用的宫颈癌发病风险预测模型，模型的可解释性强，内部验证区分度良好，校准度良好，可以用于一般人群，为个人对自身宫颈癌发病风险的评估提供依据。 |
| English Abstract: |
| Objective To construct a cervical cancer risk prediction model based on nested case-control study design and Yinzhou Health Information Platform in Ningbo, and provide reliable reference for self-risk assessment of cervical cancer in local women. Methods In local women aged 25-75 years old who had no history of cervical cancer registered in Yinzhou before October 31, 2018, a follow up was conducted for at least three years, the patients who developed cervical cancer during the follow up period were selected as the case group and matched with a control group at a ratio of 1:10. The prediction indicators before the onset was used in model construction. Variables were selected by Lasso-logistic regression, the variables with non-zero β were selected to fit the logistic regression model and Bootstrap was used for internal validation. The discrimination of the model was evaluated by area under the receiver operating characteristic curve(AUROC), and the calibration was evaluated by calibration curve and Hosmer-Lemeshow test.Results The prediction indicators included in the final model were age, smoking status, history of cervicitis, history of adenomyosis, HPV testing, and thinprep cytologic test. The AUROC calculated in the internal validation was 0.740 (95%CI:0.739-0.740), and the calibration curve was almost identical with the ideal curve, P=0.991 in Hosmer-Lemeshow test, indicating that the model discrimination and calibration were good. Conclusions In this study, a simple and practical cervical cancer risk prediction model was developed. The model can be used in general population with strong interpretability, good discrimination and calibration in internal validation, which can provide a reference for women to assess their risk of cervical cancer. |
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