Öcal Bülent, Korkmaz Mehmet Hakan, Yılmazer Demet, Taşkın Türkmenoğlu Tuğba, Bayır Ömer, Saylam Güleser, Çadallı Tatar Emel, Karahan Sevilay, Çakal Erman
Department of Otolaryngology, Ministry of Health Dışkapı Yıldırım Beyazıt Training and Research Hospital, Ankara, Turkey.
Department of Otolaryngology, Yıldırım Beyazıt University Medical School, Ankara, Turkey.
Eur Thyroid J. 2019 Apr;8(2):83-89. doi: 10.1159/000494720. Epub 2018 Nov 29.
The majority of thyroid nodules are discovered incidentally, and the management may be a challenge if the fine needle aspiration specimen yields indeterminate findings. Our aim was to develop an individualized risk prediction model to provide an accurate estimate of cancer risk in patients with cytologically indeterminate thyroid nodules.
Clinical records, ultrasound images, and cytopathology reports of patients who underwent thyroidectomy were retrospectively reviewed. Logistic regression analysis was used to identify the predictive ability of each variable for malignancy, and a nomogram was built by integrating patients' age, multiplicity of nodules, cytology results, and suspicious ultrasound features, such as microcalcifications and irregular margins.
For the 233 indeterminate nodules according to the Bethesda System for Reporting Thyroid Cytopathology, the malignancy rates of the subgroups "atypia of undetermined significance," "suspicious follicular neoplasia," and "suspicious for malignancy" were 44.3, 47.7, and 88.0%, respectively. It was found that the Bethesda category "suspicious for malignancy," microcalcifications, and irregular margins were independent risk factors for malignancy. The area under the receiver operating characteristics curve was 0.784, which suggested that the presented nomogram had considerable discriminative performance.
The nomogram developed in our study accurately predicts the malignancy risk of thyroid nodules with indeterminate cytology by using clinical, cytological, and ultrasonographic features.
大多数甲状腺结节是偶然发现的，如果细针穿刺标本结果不确定，其处理可能具有挑战性。我们的目的是开发一种个体化风险预测模型，以准确估计甲状腺细针穿刺结果不确定患者的癌症风险。
对接受甲状腺切除术患者的临床记录、超声图像和细胞病理学报告进行回顾性分析。采用逻辑回归分析确定各变量对恶性肿瘤的预测能力，并通过整合患者年龄、结节数量、细胞学结果以及可疑超声特征（如微钙化和边缘不规则）构建列线图。
根据甲状腺细胞病理学报告的贝塞斯达系统，233个不确定结节中，“意义不明确的非典型病变”“可疑滤泡性肿瘤”和“可疑恶性肿瘤”亚组的恶性率分别为44.3%、47.7%和88.0%。发现贝塞斯达分类“可疑恶性肿瘤”、微钙化和边缘不规则是恶性肿瘤的独立危险因素。受试者工作特征曲线下面积为0.784，表明所构建的列线图具有相当的鉴别性能。
我们研究中开发的列线图通过使用临床、细胞学和超声特征，准确预测了甲状腺细针穿刺结果不确定结节的恶性风险。
