title: A diagnostic predictor model for indeterminate or suspicious thyroid FNA samples.
abstract: 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.affiliation: Division of Plastic and Reconstructive Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA.
authors.forename: Nia D
authors.initials: ND
authors.lastname: Banks
authors.forename: Jeanne
authors.initials: J
authors.lastname: Kowalski
authors.forename: Hua-Ling
authors.initials: HL
authors.lastname: Tsai
authors.forename: Helina
authors.initials: H
authors.lastname: Somervell
authors.forename: Ralph
authors.initials: R
authors.lastname: Tufano
authors.forename: Alan P B
authors.initials: AP
authors.lastname: Dackiw
authors.forename: Michael R
authors.initials: MR
authors.lastname: Marohn
authors.forename: Douglas P
authors.initials: DP
authors.lastname: Clark
authors.forename: Christopher B
authors.initials: CB
authors.lastname: Umbricht
authors.forename: Martha A
authors.initials: MA
authors.lastname: Zeiger
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D044963:Biopsy, Fine-Needle / Q000379:methods*; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D013961:Thyroid Gland / Q000473:pathology / Q000601:surgery; D013964:Thyroid Neoplasms / Q000175:diagnosis; D016606:Thyroid Nodule / Q000175:diagnosis