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

Witczak, Justyna, Taylor, Peter, Chai, Jason, Amphlett, Bethan, Soukias, Jean-Marc, Das, Gautam, Tennant, Brian P., Geen, John and Okosieme, Onyebuchi E. 2016. Predicting malignancy in thyroid nodules: feasibility of a predictive model integrating clinical, biochemical, and ultrasound characteristics. Thyroid Research 9 (1) , 4. 10.1186/s13044-016-0033-y

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Abstract

Background: Although the majority of thyroid nodules are benign the process of excluding malignancy is challenging and sometimes involves unnecessary surgical procedures. We explored the development of a predictive model for malignancy in thyroid nodules by integrating a combination of simple demographic, biochemical, and ultrasound characteristics. Methods: Retrospective case-record review. We reviewed records of patients with thyroid nodules referred to our institution from 2004 to 2011 (n = 536; female 84 %, mean age 51 years). All malignancy was proven histologically while benign disease was either confirmed histologically, or on cytology with minimum 36-month observation period. We focused on the following predictors: age, sex, smoking status, thyroid hormones (FT4 and TSH) and nodule characteristics on ultrasound. Variables were included in a multivariate logistic regression and bootstrap analyses were used to confirm results. Results: Independent predictors of malignancy in the fully adjusted model were TSH (OR 1.53, 95 % CI 1.10, 2.12, p = 0.01), male gender (OR 3.45, 95 % CI 1.33, 8.92, p = 0.01), microcalcifications (OR 6.32, 95 % CI 2.82, 14.1, p < 0.001), and irregular nodule margins (OR 5.45, 95 % CI 1.61, 18.6, p = 0.006) Bootstrap analyses strengthened these associations and a parsimonious analysis consisting of these variables and age-group demonstrated an area under the curve of 0.77. A predictive score was sensitive (86.9 %) at low scores and highly specific (94.87 %) at higher scores for distinguishing benign from malignant disease. Conclusions: A predictive model for malignancy using a combination of clinical, biochemical, and radiological characteristics may support clinicians in reducing unnecessary invasive procedures in patients with thyroid nodules.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Medicine
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Additional Information: © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)
Publisher: BioMed Central
ISSN: 1756-6614
Date of First Compliant Deposit: 10 November 2016
Date of Acceptance: 19 May 2016
Last Modified: 09 Jul 2019 15:52
URI: http://orca.cf.ac.uk/id/eprint/96030

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