Department of Ear Reconstruction, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Thirty-three Badachu Road, Shijingshan District.
Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China.
J Craniofac Surg. 2021;32(2):e184-e189. doi: 10.1097/SCS.0000000000007068.
Microtia is a severe congenital malformation of the external ear. This study aimed to explore the epidemiologic characteristics and the possible risk factors in patients with severe microtia in China, and integrate significant variables into a predictive nomogram.
A total of 965 patients with microtia were included. This retrospective case study was conducted from July 2014 to July 2019 at Plastic Surgery Hospital in China. The detailed questionnaires concerning potential risk factors were completed and data were gathered. Chi-Square and Fisher tests were used to analyze the variables, and a multivariate logistic regression model was used to select variables related to severe microtia, and then construct a nomogram. The nomogram model was evaluated by the concordance index (C-index), calibration plot, and receiver operating characteristics (ROCs) curve. Bootstraps with 1000 resamples were applied to these analyses.
Of the 965 microtia patients, 629 (65.2%) were male and 867 (89.8%) were sporadic. The cases were observed more commonly in unilateral (83.1%) and right-sided (52.0%). And multiple malformations were observed in 392 (40.6%) cases. Multivariate logistic regression analysis showed that maternal age, miscarriage frequency, virus infection, anemia, using progesterone, paternal alcohol intake, and topography of living areas were associated with a higher risk of severe microtia. All the significant variables were combined into a predictive nomogram (C-index = 0.755,95% CI = 0.703-0.807). Higher prediction accuracy (adjusted C-index = 0.749) was further verified via bootstrap validation. The calibration plot showed good performance, and the ROCs curve analysis demonstrated high sensitivity and specificity.
Most microtia patients are male, sporadic, and accompanied by other malformations, which are similar to the phenotypic analysis results of other studies. A nomogram predicting severe microtia was constructed to provide scientific guidance for individualized prevention in clinical practice.
小耳畸形是一种严重的外耳先天性畸形。本研究旨在探讨中国严重小耳畸形患者的流行病学特征和可能的危险因素,并将显著变量整合到一个预测列线图中。
共纳入 965 例小耳畸形患者。这是一项回顾性病例研究,于 2014 年 7 月至 2019 年 7 月在中国整形外科医院进行。详细的潜在危险因素调查问卷完成并收集数据。采用卡方检验和 Fisher 精确检验分析变量,采用多变量 logistic 回归模型选择与严重小耳畸形相关的变量,并构建列线图。通过一致性指数(C 指数)、校准图和受试者工作特征(ROC)曲线评估列线图模型。应用 1000 次 bootstrap 进行这些分析。
在 965 例小耳畸形患者中,629 例(65.2%)为男性,867 例(89.8%)为散发。单侧(83.1%)和右侧(52.0%)更为常见。392 例(40.6%)有多种畸形。多变量 logistic 回归分析显示,母亲年龄、流产次数、病毒感染、贫血、使用孕激素、父亲饮酒和居住地区地形与严重小耳畸形风险增加相关。所有显著变量均被组合到一个预测列线图中(C 指数=0.755,95%CI=0.703-0.807)。通过 bootstrap 验证进一步验证了更高的预测准确性(调整后的 C 指数=0.749)。校准图显示出良好的性能,ROC 曲线分析显示出高灵敏度和特异性。
大多数小耳畸形患者为男性、散发,伴有其他畸形,与其他研究的表型分析结果相似。构建了预测严重小耳畸形的列线图,为临床实践中的个体化预防提供了科学指导。