Literature DB >> 21134542

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

Iain J Nixon1, Ian Ganly, Lucy E Hann, Oscar Lin, Changhong Yu, Suzanne Brandt, Jatin P Shah, Ashok Shaha, Michael W Kattan, Snehal G Patel.   

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.
Copyright © 2010. Published by Mosby, Inc.

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Mesh:

Year:  2010        PMID: 21134542     DOI: 10.1016/j.surg.2010.09.030

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  9 in total

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7.  The gray zone of thyroid nodules: Using a nomogram to provide malignancy risk assessment and guide patient management.

Authors:  Elham Yousefi; Gloria H Sura; Jonathan Somma
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8.  External validation of a nomogram that predicts the pathological diagnosis of thyroid nodules in a Chinese population.

Authors:  Ridong Wu; Liling Zhu; Wen Li; Qing Tang; Fushun Pan; Weibin Wu; Jie Liu; Chen Yao; Shenming Wang
Journal:  PLoS One       Date:  2013-06-04       Impact factor: 3.240

9.  Predicting malignancy in thyroid nodules: feasibility of a predictive model integrating clinical, biochemical, and ultrasound characteristics.

Authors:  Justyna Witczak; Peter Taylor; Jason Chai; Bethan Amphlett; Jean-Marc Soukias; Gautam Das; Brian P Tennant; John Geen; Onyebuchi E Okosieme
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  9 in total

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