Preoperative prediction of central lymph node metastasis in thyroid papillary microcarcinoma using clinicopathologic and sonographic features

Kyung Eun Kim, Eun Kyung Kim, Jung Hyun Yoon, Kyung Hwa Han, Hee Jung Moon, Jin Young Kwak

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72 Citations (Scopus)

Abstract

Background: The purpose of the present study was to evaluate the clinicopathologic factors and ultrasound (US) features predictive of central lymph node metastasis (LNM) in patients diagnosed with papillary thyroid microcarcinoma (PTMC). Methods: From March 2008 to August 2008, the clinicopathologic features and preoperative US features of 483 patients who were diagnosed with conventional PTMC were included. Medical records, US features, and pathology reports of all patients were retrospectively reviewed. Univariate and multivariate analysis was performed to identify clinicopathological prognostic factors associated with central LNM. Odds ratios (OR) with relative 95 % confidence intervals (95 % CI) were calculated to determine the relevance of all potential predictors of central LNM. Results: Among the 483 patients with PTMC, 139 (28.8 %) patients had central LNM. The OR of significant independent factors were 2.055 (95 % CI, 1.137-3.716), 2.075 (95 % CI, 1.27-3.39), 1.71 (95 % CI, 1.073-2.724), and 15.897 (95 % CI, 4.173-60.569), respectively, for bilaterality, larger tumor size (>5 mm), extracapsular invasion, and lateral LNM. No significant association was seen among the US features of PTMC with central LNM. Conclusions: Central lymph node metastasis in patients with PTMC was significantly associated with various clinicopathological factors, including larger tumor size (>5 mm), bilaterality, extracapsular invasion, and lateral LNM. When these features are detected on preoperative US, selective central compartment dissection may be helpful in patients diagnosed with PTMC.

Original languageEnglish
Pages (from-to)385-391
Number of pages7
JournalWorld Journal of Surgery
Volume37
Issue number2
DOIs
Publication statusPublished - 2013 Feb 1

All Science Journal Classification (ASJC) codes

  • Surgery

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