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논문 기본 정보

자료유형
학위논문
저자정보

이준호 (성균관대학교, 성균관대학교 일반대학원)

지도교수
김지수
발행연도
2015
저작권
성균관대학교 논문은 저작권에 의해 보호받습니다.

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이 논문의 연구 히스토리 (3)

초록· 키워드

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Background Detection of Thyroglobulin (Tg) in fine-needle aspiration cytology (FNAC) washout fluid (FNA-Tg) is used to identify recurrent/metastatic papillary thyroid cancer (PTC). However, the influence of serum Tg and thyroidectomy status on FNA-Tg is unclear. We defined the optimized cutoff value for FNA-Tg according to thyroidectomy status and serum Tg.

Methods A total of 264 lymph nodes (LNs) from 73 patients who received modified radical neck dissection (mRND) with or without thyroidectomy underwent FNAC, FNA-Tg, frozen and permanent biopsy, prospectively. Serum Tg and Tg-auto-antibody were sampled just before operation. FNAC and FNA-Tg were performed on randomly selected LNs in situ. We evaluated the diagnostic performance of recurrence/metastasis detection by thyroidectomy status and serum Tg level according to several predetermined FNA-Tg cutoff values. Comparison of the diagnostic performances was analyzed by the Youden Index.

Results The lower FNA-Tg cutoff values showed higher diagnostic sensitivity, whereas the higher FNA-Tg showed higher specificity. Diagnostic performances of the FNA-Tg cutoff value varied according to serum Tg level and thyroidectomy status. The optimized cutoff value of FNA-Tg was 1 ng/ml for a total of 264 LNs (sensitivity: 87.5%, specificity: 83.6%). However, FNA-Tg over 10 ng/ml showed better diagnostic performance in patients with pre-thyroidectomy status with high serum Tg level (sensitivity: 90.9%, specificity: 90.0%). FNA-Tg/serum-Tg>1 showed the best diagnostic performance (sensitivity: 100%, specificity: 100%) in post-thyroidectomy status.

Conclusions Applying the optimal cutoff values of FNA-Tg according to serum Tg level and thyroidectomy status facilitates the diagnostic evaluation of neck LN recurrences/metastases in patients with PTC.

목차

Abstract 1
Introduction 3
Material and Methods 4
Results 7
Discussion 10
Conclusion 13
References 14
Table 18
Figure 24
Thesis Summary 27

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