Xue Peng, Wei Bingrui, Seery Samuel, Li Qing, Ye Zichen, Jiang Yu, Qiao Youlin
Department of Epidemiology and Biostatistics, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Faculty of Health and Medicine, Division of Health Research, Lancaster University, Lancaster, LA1 4YW, United Kingdom.
Chin J Cancer Res. 2022 Aug 30;34(4):395-405. doi: 10.21147/j.issn.1000-9604.2022.04.07.
This study aimed to develop a nomogram that can predict occult high-grade squamous intraepithelial lesions or worse (HSIL+) and determine the need for endocervical curettage (ECC) in patients referred for colposcopy.
This retrospective multicenter study included 4,149 patients who were referred to any one of six tertiary hospitals in China for colposcopy between January 2020 and November 2021 because of abnormal screening results. ECC data were extracted from the medical records. Univariate and multivariate logistic regression analyses were performed to identify factors that could predict HSIL+ on ECC. Patients were randomly assigned to a training set or to an internal validation set for performance and comparability testing. The model was externally validated and tested in patients from two additional hospitals. The nomogram was assessed in terms of discrimination and calibration and subjected to decision curve analysis.
HSIL+ was found on ECC in 38.8% (n=388) of cases. Our predictive nomogram included age group, cytology, human papillomavirus (HPV) status, visibility of the cervix and colposcopic impression. The nomogram had good overall discrimination, which was internally validated [area under the receiver-operator characteristic (AUC), 0.839; 95% confidence interval (95% CI), 0.773-0.904]. In terms of external validation, the AUC was 0.843 (95% CI, 0.773-0.912) for the consecutive sample and 0.843 (95% CI, 0.783-0.902) for the comparative sample. Calibration analysis suggested good consistency between predicted and observed probabilities. Decision curve analysis suggested this nomogram would be clinically useful with almost the entire range of threshold probabilities.
This internally and externally validated nomogram can be easily applied and incorporates multiple clinically relevant variables that can be used to identify patients with occult HSIL+ who need ECC.
本研究旨在开发一种列线图，用于预测隐匿性高级别鳞状上皮内病变或更严重病变（HSIL+），并确定接受阴道镜检查的患者是否需要进行宫颈管刮除术（ECC）。
这项回顾性多中心研究纳入了2020年1月至2021年11月期间因筛查结果异常而被转诊至中国六家三级医院之一进行阴道镜检查的4149例患者。从病历中提取ECC数据。进行单因素和多因素逻辑回归分析，以确定可预测ECC上HSIL+的因素。患者被随机分配到训练集或内部验证集进行性能和可比性测试。该模型在另外两家医院的患者中进行了外部验证和测试。对列线图进行了鉴别和校准评估，并进行了决策曲线分析。
38.8%（n = 388）的病例在ECC上发现HSIL+。我们的预测列线图包括年龄组、细胞学、人乳头瘤病毒（HPV）状态、宫颈可见度和阴道镜印象。该列线图具有良好的总体鉴别能力，经内部验证[受试者操作特征曲线（AUC）下面积为0.839；95%置信区间（95%CI）为0.773 - 0.904]。在外部验证方面，连续样本的AUC为0.843（95%CI，0.773 - 0.912），比较样本的AUC为0.843（95%CI，0.783 - 0.902）。校准分析表明预测概率与观察概率之间具有良好的一致性。决策曲线分析表明，该列线图在几乎整个阈值概率范围内在临床上都有用。
这种经过内部和外部验证的列线图易于应用，纳入了多个临床相关变量，可用于识别需要ECC的隐匿性HSIL+患者。
