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基于TNM分期的胸腺上皮肿瘤完全切除后预测复发的列线图:多机构回顾性分析 ... ...

已有 27 次阅读2019-11-29 01:00 |个人分类:TET学习|系统分类:医学科学| 胸腺上皮肿瘤

基于TNM分期的胸腺上皮肿瘤完全切除后预测复发的列线图:多机构回顾性分析。
A nomogram for predicting recurrence after complete resection for thymic epithelial tumors based on the TNM classification: A multi-institutional retrospective analysis.

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.

KEYWORDS:
calibration; nomogram; recurrence; staging; thymic malignancy
PMID: 30919992 DOI: 10.1002/jso.25462

Yun JK, Lee GD, Kim HR, Kim DK, Zo JI, Shim YM, Kang CH, Kim YT, Paik HC,Chung KY; other members of the Korean Association for Research on the Thymus (KART). A nomogram for predicting recurrence after complete resection for thymic epithelial tumors based on the TNM classification: A multi-institutional retrospective analysis. J Surg Oncol. 2019 Jun;119(8):1161-1169. doi: 10.1002/jso.25462. Epub 2019 Mar 28. PubMed PMID: 30919992.

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