BACKGROUND: The management of patients with thyroid fine-needle aspiration (FNA) specimens that are neither benign nor malignant still remains problematic. Efforts to improve their management have focused on identifying risk factors that predict malignancy. This study seeks to identify clinical and tumor characteristics that predict thyroid malignancy among patients with indeterminate or suspicious FNA and to develop a diagnostic predictor model. METHODS: The records of 639 patients with an indeterminate or suspicious thyroid FNA between January 1995 and April 2005 were reviewed. Patient and tumor characteristics were evaluated for their potential to predict malignancy in the final surgical histopathology. A diagnostic predictor model was designed based on statistically significant predictors. Patients seen between April 2005 and April 2007 were used to validate the model. RESULTS: Patient age, nodule size, and FNA cytopathology were identified as risk factors. Patients at extremes of age were at increased risk. Patients 50 years of age had the lowest risk of malignancy. For patients less than age 50, the risk increased 3% for each year decrease in age (p = 0.001). After 50, the risk increased 3.4% for each year increase in age (p = 0.016). Nodules 2.5 cm had the lowest likelihood of malignancy. For smaller nodules, the risk increased 53% per cm decrease in size (p < 0.001). For larger nodules, the risk increased 39% per cm increase (p < 0.001). Patients with FNA cytology suspicious for papillary thyroid carcinoma had the greatest risk of malignancy (p < 0.001). CONCLUSIONS: A predictor model was created using the variables age, nodule size, and FNA cytology to predict thyroid malignancy.
BACKGROUND: The management of patients with thyroid fine-needle aspiration (FNA) specimens that are neither benign nor malignant still remains problematic. Efforts to improve their management have focused on identifying risk factors that predict malignancy. This study seeks to identify clinical and tumor characteristics that predict thyroid malignancy among patients with indeterminate or suspicious FNA and to develop a diagnostic predictor model. METHODS: The records of 639 patients with an indeterminate or suspicious thyroid FNA between January 1995 and April 2005 were reviewed. Patient and tumor characteristics were evaluated for their potential to predict malignancy in the final surgical histopathology. A diagnostic predictor model was designed based on statistically significant predictors. Patients seen between April 2005 and April 2007 were used to validate the model. RESULTS:Patient age, nodule size, and FNA cytopathology were identified as risk factors. Patients at extremes of age were at increased risk. Patients 50 years of age had the lowest risk of malignancy. For patients less than age 50, the risk increased 3% for each year decrease in age (p = 0.001). After 50, the risk increased 3.4% for each year increase in age (p = 0.016). Nodules 2.5 cm had the lowest likelihood of malignancy. For smaller nodules, the risk increased 53% per cm decrease in size (p < 0.001). For larger nodules, the risk increased 39% per cm increase (p < 0.001). Patients with FNA cytology suspicious for papillary thyroid carcinoma had the greatest risk of malignancy (p < 0.001). CONCLUSIONS: A predictor model was created using the variables age, nodule size, and FNA cytology to predict thyroid malignancy.
Authors: Nijaguna B Prasad; Jeanne Kowalski; Hua-Ling Tsai; Kristin Talbot; Helina Somervell; Guennadi Kouniavsky; Yongchun Wang; Alan P B Dackiw; William H Westra; Douglas P Clark; Steven K Libutti; Christopher B Umbricht; Martha A Zeiger Journal: Thyroid Date: 2012-01-26 Impact factor: 6.568
Authors: P Dalquen; B Rashed; A Hinsch; R Issa; T Clauditz; A Luebke; J Lüttges; W Saeger; K H Bohuslavizki Journal: Pathologe Date: 2016-09 Impact factor: 1.011
Authors: S Arena; A Latina; I Marturano; V Muscia; G L La Rosa; M Stornello; S Squatrito; S Italia; R Vigneri Journal: J Endocrinol Invest Date: 2013-05-06 Impact factor: 4.256
Authors: Frederico F R Maia; Patrícia S Matos; Elizabeth J Pavin; José Vassallo; Denise E Zantut-Wittmann Journal: Endocrine Date: 2011-04-16 Impact factor: 3.633