Diagnosis of thyroid cancer: state of art

Boufraqech, Myriem; Patel, Dhaval; Xiong, Yin; Kebebew, Electron

doi:10.1517/17530059.2013.800481

Cited by 18 publications

(16 citation statements)

References 89 publications

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“…To date, there is no strong evidence either for or against routine BRAF evaluation in the initial work up of thyroid nodules. Also, this approach appears difficult in FNA samples . Potentially, analysis of BRAF mutational status could be useful in the risk stratification of thyroid lesions, which are read as indeterminate at FNA.…”

Section: Introductionmentioning

confidence: 99%

BRAF‐mutated carcinomas among thyroid nodules with prior indeterminate FNA report: a systematic review and meta‐analysis

Trimboli

Treglia

Condorelli

et al. 2015

Clinical Endocrinology

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Section: Introductionmentioning

confidence: 99%

BRAF‐mutated carcinomas among thyroid nodules with prior indeterminate FNA report: a systematic review and meta‐analysis

Trimboli

Treglia

Condorelli

et al. 2015

Clinical Endocrinology

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“…Thyroid cancer (TC) is the most common endocrine malignancy, accounting for 95% of all endocrine malignancies ( Boufraqech, Patel, Xiong, & Kebebew, 2013 ), and which has an increasing incidence for 1999-2008: going up by an estimated 6.2% per year for men and 7.3% per year for women ( Simard, Ward, Siegel, & Jemal, 2012 ). Unfortunately, neoplasias of the thyroid have been largely ignored because of the overall favorable prognosis of papillary thyroid cancers (PTC) and follicular thyroid cancers (FTC), with 5-year survival rates of approximately 98% when submitted to timely and appropriate treatment ( SEER Cancer Statistics Factsheets: Thyroid Cancer.…”

Section: Introductionmentioning

confidence: 99%

Methylation Markers for Early Detection and Differentiation of Follicular Thyroid Cancer Subtypes

Stephen¹,

Chen²,

Merritt³

et al. 2015

CCO

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Thyroid cancer has the fastest rising incidence rates and is the fifth most common cancer in women. There are four main types of which the papillary and follicular types together account for >90%, followed by medullary cancers (3%−5%) and anaplastic carcinomas (<3%). For individuals who present with early stage disease of papillary and follicular cancers, there are no accurate markers to predict whether they will develop metastatic or recurrent disease. Our immediate goal is to molecularly differentiate follicular cancer subtypes for enhanced classification. Promoter methylation status of genes with reported associations in thyroid cancer (CASP8, CDKN2A, DAPK1, ESR1, NIS, RASSF1 and TIMP3) were examined in a cohort of follicular thyroid cancers comprising of 26 Hurthle and 27 Classic subtypes utilizing quantitative methylation-specific PCR. RASSF1 was differentially methylated in Classic tumor tissue compared to Hurthle (p<0.001). Methylation of RASSF1 pointed to racial group differences between African Americans and Caucasian Americans (p=0.05). Extra thyroidal extension was found to be associated with DAPK1 (p=0.014) and ESR1 (p=0.036) methylation. Late stage disease was associated with older age (p<0.001) and methylation of DAPK1 (p=0.034) and ESR1 (p=0.035). The methylation status of RASSF1, DAPK1 and ESR1 suggests the utility of methylation markers to molecularly differentiate thyroid cancer subtypes for enhanced classification and early detection of thyroid cancer.

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“…Fine-needle aspiration biopsy (FNAB) is the best first-line procedure for differential diagnosis of a thyroid nodule, and pathological examination is considered as the gold standard. However, up to one-third of those FNAB results are inconclusive [ 16 – 18 ]. Sonography is another option for screening unknown thyroid nodule and lymph node structure, but this procedure has a relatively low capacity for differential diagnosis [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

A new computational model for human thyroid cancer enhances the preoperative diagnostic efficacy

Sheng

et al. 2015

Oncotarget

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Considering the high rate of missed diagnosis and delayed treatments for thyroid cancer, an effective systematic model for the differential diagnosis is highly needed. Thus we analyzed the data on the clinicopathological characteristics, routine laboratory tests and imaging examinations in a cohort of 13,980 patients with thyroid cancer to establish a new diagnostic model for differentiating thyroid cancer in clinical practice. Here, we randomly selected two-thirds of the population to develop the thyroid malignancy risk scoring system (TMRS) for preoperative differentiation between thyroid cancer and benignant thyroid diseases, and then validated its differential diagnostic power in the rest one-third population. The 18 predictors finally enrolled in the TMRS included male gender, clinical manifestations (fever, neck sore, neck lump, palpitations or sweating), laboratory findings (TSH>1.56mIU/L, FT3>5.85pmol/L, TPOAb>14.97IU/ml, TgAb>48.00IU/ml, Tg>34.59μg/L, Ct>64.00ng/L, and CEA>0.41μg/L), and ultrasound features (tumor number≤ 23mm, site, size, echo texture, margins, and shape of neck lymphnodes). The TMRS is validated to be well-calibrated (P = 0.437) and excellently discriminated (AUC = 0.93, 95% CI [0.92, 0.94]), with an accuracy of 83.2%, a sensitivity of 89.3%, a specificity of 81.5%, positive and negative predictive values of 56.8% and 96.6%, positive and negative likelihood ratios of 4.83 and 0.13 in the development cohort, respectively. The TMRS highlights that this differential diagnostic system could help provide accurate preoperative risk stratification for thyroid cancer, and avoid unnecessary over- and under-treatment for such patients.

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Diagnosis of thyroid cancer: state of art

Cited by 18 publications

References 89 publications

BRAF‐mutated carcinomas among thyroid nodules with prior indeterminate FNA report: a systematic review and meta‐analysis

BRAF‐mutated carcinomas among thyroid nodules with prior indeterminate FNA report: a systematic review and meta‐analysis

Methylation Markers for Early Detection and Differentiation of Follicular Thyroid Cancer Subtypes

A new computational model for human thyroid cancer enhances the preoperative diagnostic efficacy

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