Nomogram for predicting malignancy in thyroid nodules using clinical, biochemical, ultrasonographic, and cytologic features

Iain J. Nixon, Ian Ganly, Lucy E. Hann, Oscar Lin, Changhong Yu, Suzanne Brandt, Jatin P. Shah, Ashok Shaha, Michael W. Kattan, Snehal G. Patel

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Thyroid nodules often discovered incidentally and present a management problem particularly when investigations suggest atypical or suspicious cells. Prediction of the risk of malignancy within such a thyroid nodule is based on clinical, biochemical, ultrasonographic, and cytologic features. Our aim was to create a nomogram to predict accurately the chance of malignancy within a thyroid nodule. Methods: All patients with thyroid nodules who underwent ultrasonographic-guided fine needle aspiration and operative resection at our institution during 2007-2008 were identified. Clinical records, biochemical profiles, pathology reports, ultrasonographic images, and cytology slides were reviewed. A multivariate logistic regression was used to quantify the value of the variables in estimating the risk of malignancy. Results: The records of 158 patients with 190 nodules were reviewed. Eighteen nodules were excluded. The 8 variables with the greatest predictive value selected for the nomogram were biochemical (thyroid-stimulating hormone), ultrasonography (shape, echo texture, and vascularity), and cytology (nuclear grooves, pseudoinclusions, cellularity, and presence of colloid). The nomogram had an excellent predictive accuracy with a concordance index of 91%. Conclusion: We produced a nomogram that can quantify accurately the risk of malignancy in a thyroid nodule based on biochemical, ultrasonographic, and cytologic features.

Original languageEnglish
Pages (from-to)1120-1128
Number of pages9
JournalSurgery
Volume148
Issue number6
DOIs
Publication statusPublished - 1 Jan 2010

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