Department of Otolaryngology, Far Eastern Memorial Hospital, Taipei, Taiwan.
Department of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan.
Laryngoscope. 2021 Jan;131(1):E157-E162. doi: 10.1002/lary.28591. Epub 2020 Feb 28.
To create a sonographic scoring model in the prediction of major salivary gland tumors and to assess the utility of this predictive model.
Retrospective case series, academic tertiary referral center.
Two hundred fifty-nine patients who underwent ultrasound (US), US-guided needle biopsies, and subsequent operations were enrolled. These data were used to build a predictive scoring model and the model was validated by 10-fold cross-validation.
We constructed a sonographic scoring model by multivariate logistic regression analysis: 2.08 × (boundary) + 1.75 × (regional lymphadenopathy) + 1.18 × (shape) + 1.45 × (posterior acoustic enhancement) + 2.4 × (calcification). The optimal cutoff score was 3, corresponding to 70.2% sensitivity, 93.9% specificity, and 89.6% overall accuracy. The mean areas under the receiver operating characteristic curve (c-statistic) in 10-fold cross-validation was 0.90.
The constructed predictive scoring model is beneficial for patient counseling under US exam and feasible to provide us the guidance on which kind of needle biopsy should be performed in major salivary gland tumors.
3b Laryngoscope, 131:E157-E162, 2021.
建立预测主要涎腺肿瘤的超声评分模型，并评估该预测模型的效用。
回顾性病例系列，学术性三级转诊中心。
共纳入 259 例接受超声（US）、US 引导下针吸活检和随后手术的患者。这些数据用于建立预测评分模型，并通过 10 折交叉验证对模型进行验证。
我们通过多变量逻辑回归分析构建了一个超声评分模型：2.08×（边界）+1.75×（区域淋巴结病）+1.18×（形状）+1.45×（后向声增强）+2.4×（钙化）。最佳截断评分为 3，对应 70.2%的敏感性、93.9%的特异性和 89.6%的总体准确性。10 折交叉验证的平均受试者工作特征曲线下面积（c 统计量）为 0.90。
构建的预测评分模型有利于 US 检查下的患者咨询，并可提供指导，帮助我们决定在主要涎腺肿瘤中应进行哪种类型的针吸活检。
3b 喉镜，131：E157-E162，2021 年。
