基于TNM分类预测胸腺上皮肿瘤完全切除术后复发的列线图研究 ... ... ...

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.

本研究旨在比较Masaoka-Koga（M-K）分期系统和第8版TNM分期系统对胸腺上皮肿瘤（TETs）复发的预测能力。 此外，根据推荐的TNM分类建立列线图，以预测个体复发率。

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.

对2000年1月至2013年2月期间接受TETs完全切除（R0）的445例患者进行回顾性研究。使用一致性指数（C指数）作为统计指标来量化预测模型的预测能力。

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).

在多变量分析中，肿瘤分期和WHO分类是基于M-K和TNM分期预测模型中的独立复发因素。TNM模型显示出比M-K模型更高的C指数（0.837 vs 0.817）。在TNM模型的基础上，列线图显示出高度预测效能，自助修正的C指数为0.85（95％CI，0.76至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.

对于预测TETs的R0后的复发的模型效能，基于第8版TNM分期的预测模型略好于基于M-K分期的预测模型。 推荐列线图可用于估计个体复发率，并做出恰当的监测结果。

KEYWORDS:

calibration; nomogram; recurrence; staging; thymic malignancy

校准;列线图;复发;分期; 胸腺恶性肿瘤