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Cited 7 time in webofscience Cited 9 time in scopus
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A nomogram for predicting recurrence after complete resection for thymic epithelial tumors based on the TNM classification: A multi-institutional retrospective analysis

Authors
Yun, JK[Yun, Jae Kwang]Lee, GD[Lee, Geun Dong]Kim, HR[Kim, Hyeong Ryul]Kim, DK[Kim, Dong Kwan]Zo, JI[Zo, Jae Il]Shim, YM[Shim, Young Mog]Kang, CH[Kang, Chang Hyun]Kim, YT[Kim, Young Tae]Paik, HC[Paik, Hyo Chae]Chung, KY[Chung, Kyoung Young]Hwang, SK[Hwang, Su Kyung]Choi, SH[Choi, Se Hoon]Kim, YH[Kim, Yong-Hee]Park, SI[Park, Seung-Il]Jung, JJ[Jung, Jae Jun]Shin, S[Shin, Sumin]Cho, JH[Cho, Jong Ho]Kim, HK[Kim, Hong Kwan]Choi, YS[Choi, Yong Soo]Kim, J[Kim, Jhingook]Park, S[Park, Samina]Hyun, KY[Hyun, Kwan Yong]Hwang, Y[Hwang, Yoohwa]Lee, HJ[Lee, Hyun Joo]Park, IK[Park, In Kyu]Lee, CY[Lee, Chang Young]Lee, JG[Lee, Jin Gu]Kim, DJ[Kim, Dae Joon]
Issue Date
15-Jun-2019
Publisher
WILEY
Keywords
calibration; nomogram; recurrence; staging; thymic malignancy
Citation
JOURNAL OF SURGICAL ONCOLOGY, v.119, no.8, pp.1161 - 1169
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF SURGICAL ONCOLOGY
Volume
119
Number
8
Start Page
1161
End Page
1169
URI
https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/9581
DOI
10.1002/jso.25462
ISSN
0022-4790
Abstract
Objectives This study aimed to compare the predictive ability between the Masaoka-Koga (M-K) staging system and the 8th TNM staging system for the recurrence of thymic epithelial tumors (TETs). In addition, a nomogram was developed on the basis of the proposed TNM classification to predict individual recurrence rate. Methods A retrospective study was performed on 445 patients who underwent complete resection (R0) of TETs between January 2000 and February 2013. Concordance index (C-index) was used as a statistical indicator to quantify the prediction power of the prediction models. Results In multivariate analysis, tumor stage and WHO classification were independent recurrence factors in a predictive model on the basis of M-K and TNM stage. The TNM model showed higher C-index than the M-K model (0.837 vs 0.817). The nomogram, on the basis of the TNM model, revealed a highly predictive performance, with a bootstrap-corrected C-index of 0.85 (95% CI, 0.76 to 0.93). Conclusions A predictive model based on the 8th TNM stage was slightly better than that based on M-K stage with respect to recurrence after R0 of TETs. The proposed nomogram could be applied to estimate the individual recurrence rate and make decisions for proper surveillance.
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