title: Ultrasound-based clinical prediction rule model for detecting papillary thyroid cancer in cervical lymph nodes: A pilot study.
abstract: OBJECTIVE
  To identify sonographic features of cervical lymph nodes (LNs) that are associated with papillary thyroid cancer (PTC) and to develop a prediction model for classifying nodes as metastatic or benign.
  
  
  METHODS
  This retrospective study included the records of postthyroidectomy patients with PTC who had undergone cervical ultrasound and LN biopsy. LN location, size, shape, hilum, echopattern, Doppler flow, and microcalcifications were assessed. Model selection was used to identify features associated with malignant LNs and to build a predictive, binary-outcome, generalized linear mixed model. A cross-validated receiver operating characteristic analysis was conducted to assess the accuracy of the model for classifying metastatic nodes.
  
  
  RESULTS
  We analyzed records from 71 LNs (23 metastatic) in 44 patients (16 with PTC). The predictive model included a nonhomogeneous echopattern (odds ratio [OR], 5.73; 95% confidence interval [CI], 1.07-30.74; p = 0.04), microcalcifications (OR, 4.91; 95% CI, 0.91-26.54; p = 0.06), and volume (OR, 2.57; 95% CI, 0.66-9.99; p = 0.16) as predictors. The model had an area under the curve of 0.74 (95% CI, 0.60-0.85), sensitivity of 65% (95% CI, 50% to 78%), and specificity of 85% (95% CI, 73% to 94%) at the Youden optimal cut point of 0.38.
  
  
  CONCLUSIONS
  Nonhomogeneous echopattern, microcalcifications, and node volume were predictive of malignant LNs in patients with PTC. A larger sample is needed to validate this model.
authors.affiliation: Department of Radiology, University of Colorado School of Medicine, Aurora, CO, 80045.
authors.forename: Nayana U
authors.initials: NU
authors.lastname: Patel
authors.affiliation: Department of Radiology, University of Colorado School of Medicine, Aurora, CO, 80045.
authors.forename: Kristin
authors.initials: K
authors.lastname: McKinney
authors.affiliation: Department of Radiology, University of Colorado School of Medicine, Aurora, CO, 80045.
authors.forename: Sarah M
authors.initials: SM
authors.lastname: Kreidler
authors.affiliation: University of Colorado Hospital, Aurora, CO, 80045.
authors.forename: Teresa M
authors.initials: TM
authors.lastname: Bieker
authors.affiliation: Department of Radiology, University of Colorado School of Medicine, Aurora, CO, 80045.
authors.forename: Paul
authors.initials: P
authors.lastname: Russ
authors.affiliation: Department of Biostatistics and Informatics, University of Colorado School of Public Health, Aurora, CO, 80045.
authors.forename: Katherine
authors.initials: K
authors.lastname: Roberts
authors.affiliation: Department of Biostatistics and Informatics, University of Colorado School of Public Health, Aurora, CO, 80045.
authors.forename: Deborah H
authors.initials: DH
authors.lastname: Glueck
authors.affiliation: Department of GI Tumor and Endocrine Surgery, University of Colorado School of Medicine, Aurora, CO, 80045.
authors.forename: Maria
authors.initials: M
authors.lastname: Albuja-Cruz
authors.affiliation: Department of Medicine, Division of Endocrinology, University of Colorado School of Medicine and University of Colorado Cancer Center, Aurora, CO, 80045.
authors.forename: Joshua
authors.initials: J
authors.lastname: Klopper
authors.affiliation: Department of Medicine, Division of Endocrinology, University of Colorado School of Medicine and University of Colorado Cancer Center, Aurora, CO, 80045.
authors.forename: Bryan R
authors.initials: BR
authors.lastname: Haugen
mesh_terms: D002277:Carcinoma / Q000473:pathology*; D002291:Carcinoma, Papillary; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008198:Lymph Nodes / Q000000981:diagnostic imaging*; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D009333:Neck; D010865:Pilot Projects; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D000077273:Thyroid Cancer, Papillary; D013964:Thyroid Neoplasms / Q000473:pathology*; D014463:Ultrasonography / Q000379:methods*
keywords: fine-needle aspiration biopsy; lymph nodes; metastasis; predictive model; thyroid cancer; ultrasonography