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首页> 外文期刊>Scientific reports. >Clinical Value of Lymph Node Ratio Integration with the 8th Edition of the UICC TNM Classification and 2015 ATA Risk Stratification Systems for Recurrence Prediction in Papillary Thyroid Cancer
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Clinical Value of Lymph Node Ratio Integration with the 8th Edition of the UICC TNM Classification and 2015 ATA Risk Stratification Systems for Recurrence Prediction in Papillary Thyroid Cancer

机译:乳头状甲状腺癌复发预测淋巴结比与2015年第8版淋巴结比集成的临床价值

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摘要

Recently, the 2015 American Thyroid Association (ATA) risk stratification and the 8supth/sup edition of the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) TNM staging system were released. This study was conducted to assess the clinical value of the lymph node ratio (LNR) as a predictor of recurrence when integrated with these newly released stratification systems, and to compare the predictive accuracy of the modified systems with that of the newly released systems. The optimal LNR threshold value for predicting papillary thyroid cancer (PTC) recurrence was 0.17857 using the Contal and O'Quigley method. The 8supth/sup edition of the AJCC/UICC TNM staging system with the LNR and the 2015 ATA risk stratification system with the LNR were significant predictors of recurrence. Furthermore, calculation of the proportion of variance explained (PVE), the Akaike information criterion (AIC), Harrell's c index, and the incremental area under the curve (iAUC) revealed that the 8supth/sup edition of the TNM staging system with the LNR, and the 2015 ATA risk stratification system with the LNR, showed the best predictive performance. Integration of the LNR with the TNM staging and the ATA risk stratification systems should improve prediction of recurrence in patients with PTC.
机译:最近,2015年美国甲状腺协会(ATA)风险分层和美国联合癌症/国际癌症控制联盟委员会(AJCC / UICC)TNM分期系统的8 TH 版本被释放。进行该研究以评估淋巴结比(LNR)的临床价值作为与这些新释放的分层系统集成的复发的预测因子,并比较了新释放系统的改进系统的预测精度。用于预测乳头状甲状腺癌(PTC)复发的最佳LNR阈值为0.17857,使用常见和O'Quigley方法。具有LNR和2015年ATA风险分层系统的AJCC / UICC TNM分期系统的8 TN 版本具有LNR的重要预测因子。此外,计算曲线下解释(PVE),Akaike信息标准(AIC),Harrell的C指数和增量区域的变化比例的计算揭示了8 th 版本与LNR的TNM分期系统,以及2015年ATA风险分层系统与LNR,显示出最佳的预测性能。 LNR与TNM分期的整合和ATA风险分层系统应改善PTC患者的复发预测。

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