An Easy Sonographic Scoring System for Predicting Malignant Thyroid Nodules
NCT ID: NCT01307761
Last Updated: 2011-09-19
Study Results
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Basic Information
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UNKNOWN
500 participants
OBSERVATIONAL
2010-12-31
2013-08-31
Brief Summary
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Detailed Description
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Some sonographic appearance can help in selection of the correct thyroid nodes to aspirate with US(ultrasound)-guided FNA(fine needle aspiration) biopsy. Findings suggestive for malignant thyroid cancer include micro-calcification, blurred margins, intra-nodular vascular pattern, marked hypoechogenicity or taller-than-wide shape.1-3 However, no single criteria can perfectly predict malignant thyroid nodules. Applied multiple US criteria for the differentiation of thyroid nodule has an overall accuracy ranging from 59.5 to 73.4%.3
Objective:
The purpose of our study is to retrospectively evaluate the predictors of malignant thyroid nodules and established an useful scoring system based on sonographic findings and demographic data.
Material and methods:
This study will be conducted according to the principle of Helsinki declaration and the guidelines of the institutional ethical committee. We want to retrospectively review the medical records of 479 nodules which underwent head and neck ultrasound(US) examination and US-FNA cytology from 2007 July to 2010 Dec at Department of Otolaryngology, Far Eastern Memorial Hospital, Taipei, Taiwan. No patient included in this series had a previous diagnosis of thyroid malignancy.
Equipment for US studies consisted of a color Doppler US unit (Philips HDI 5000, Bothell, WA) and a 5-12 MHz broadband linear array transducer. Nodules were measured with AP and transverse (T) diameters in transverse section. Settings of power Doppler sonography were set for high sensitivity with a low wall filter to allow detection of vessels with low blood flow. The color gain was increased until background noise appeared and then reduced until the noise was suppressed, thus ensuring maximum sensitivity according to Bude and Rubin's description.4 The vascularity types are classified as avascular, peripheral and intra-nodule types1,5. The echo structure (predominantly solid or cyst), internal echo (homogeneous or heterogenicity), echogenicity (hyperechoic, isoechoic, hypoechoic), presented micro-calcification, and characteristics of nodule margin (well-defined or ill defined) were assessed. Thyroid incidentalomas are thyroid nodules without clinically apparent tumor but are incidentally found by US.
US-FNA was carried out with the array probe guiding the placement of a 22-gauge fine needle after informed consent was obtained. The final diagnosis of a lesion as benign (n=449) or malignancy (n=30) was confirmed by FNA biopsy. The relationship between demographic data, sonographic features and final diagnosis, i.e. benign or malignant disease was analyzed in all 479 nodules. In univariate analysis, Chi-square test or Fisher exact test was performed to compare for categorical variables, and student t- test for continuous variables. A stepwise multivariate logistic regression analysis was applied to identify significant independent variables for prophesying malignant nodal disease. The level of significance was set at p \< 0.05. The predictive formula was based on multivariate logistic regression analysis and programmed into a real-time, computerized sonographic reporting system. Hosmer-Lemeshow test6 was carried out to verify the significance of the prediction model. The association between prediction score and malignant nodal disease was analyzed using the receiver operating characteristic (ROC) curve. An optimal cutoff point was determined at the point of greatest "sensitivity" with the corresponding smallest "1-specificity".7 The c-value as a measure for the area under the curve represented the diagnostic accuracy of the model.8 All statistical analyses were accomplished using SAS software, version 9.1 (SAS Institute, Inc, Cary, North Carolina).
Expected Results: A simple and practical sonographic scoring system would be built to provide the physician prompt and reliable probability guidance for FNA cytology while managing thyroid nodule.
References:
1. Cappelli C, Castellano M, Pirola Iet al. The predictive value of ultrasound findings in the management of thyroid nodules. Qjm 2007; 100:29.
2. Kim E, Park C, Chung Wet al. New sonographic criteria for recommending fine-needle aspiration biopsy of nonpalpable solid nodules of the thyroid. American Journal of Roentgenology 2002; 178:687.
3. Moon W, Jung S, Lee Jet al. Benign and Malignant Thyroid Nodules: US Differentiation-Multicenter Retrospective Study1. Radiology 2008; 247:762.
4. Bude R, Rubin J. Power Doppler sonography. Radiology 1996; 200:21.
5. Rago T, Vitti P, Chiovato Let al. Role of conventional ultrasonography and color flow-doppler sonography in predicting malignancy in'cold'thyroid nodules. European Journal of Endocrinology 1998; 138:41.
6. Lemeshow S, Hosmer Jr D. A review of goodness of fit statistics for use in the development of logistic regression models. American Journal of Epidemiology 1982; 115:92.
7. Akobeng A. Understanding diagnostic tests 3: receiver operating characteristic curves. Acta Paediatrica 2007; 96:644-647.
8. McNeil B, Hanley J. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143:29-36.
Conditions
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Study Design
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RETROSPECTIVE
Study Groups
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Patients with thyroid nodule received US-FNA exam
Patients with thyroid nodules which underwent head and neck ultrasound(US) examination and US-FNA cytology at Department of Otolaryngology, Far Eastern Memorial Hospital, Taipei, Taiwan. No patient included in this series had a previous diagnosis of thyroid malignancy before US exam.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
90 Years
ALL
No
Sponsors
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Far Eastern Memorial Hospital
OTHER
Responsible Party
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Li-Jen Liao
Department of Otolaryngology
Locations
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Far Eastern Memorial Hospital
Taipei, , Taiwan
Countries
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Central Contacts
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Other Identifiers
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099144-E
Identifier Type: -
Identifier Source: org_study_id
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