Kim Tae Hyuk, Ki Chang-Seok, Kim Hye Seung, Kim Kyunga, Choe Jun-Ho, Kim Jung-Han, Kim Jee Soo, Oh Young Lyun, Hahn Soo Yeon, Shin Jung Hee, Jang Hye Won, Kim Sun Wook, Chung Jae Hoon
Division of Endocrinology and Metabolism, Department of Medicine, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
J Clin Endocrinol Metab. 2017 May 1;102(5):1757-1764. doi: 10.1210/jc.2016-3434.
Currently, no recurrence or mortality risk systems consider molecular testing when predicting thyroid cancer outcomes.
We developed an integrative prognostic system that incorporates telomerase reverse transcription (TERT) promoter mutations into the recently proposed risk reclassification system after initial therapy [dynamic risk stratification (DRS)] to better categorize and predict outcomes.
A total of 357 differentiated thyroid cancer (DTC) patients without initial distant metastasis were enrolled. Among patients with mutated TERT and wild-type, recurrence-free survival (RFS) was compared according to DRS grouping. Cox regression was used to calculate adjusted hazard ratios (AHRs) to derive AHR groups. Performance of the AHR grouping system with respect to prediction of structural recurrence and cancer-specific survival (CSS) was assessed against the current DRS system and the tumor/node/metastasis (TNM) classification.
Among 357 patients, there were 90 recurrences and 15 cancer-related deaths during a median of 14 years of follow-up. Patients in higher AHR groups were at higher risk of recurrence (10-year RFS for AHR 1, 2, 3, and 4: 94.9%, 82.7%, 50.2%, and 23.1%; P < 0.001) and cancer-related death (10-year CSS: 100.0%. 98.7%, 94.2%, and 76.9%; P < 0.001). The proportions of variance explained (PVEs) for the ability of AHR and DRS grouping to predict recurrence were 22.4% and 18.5%. PVEs of AHR and TNM system to predict cancer-related deaths were 11.5% and 7.4%.
The AHR grouping system, a simple two-dimensional prognostic system, is as effective as DRS at predicting structural recurrence and provides clinical implication for long-term CSS in patients with nonmetastatic DTC.
目前，在预测甲状腺癌预后时，尚无复发或死亡风险系统考虑分子检测。
我们开发了一种综合预后系统，将端粒酶逆转录（TERT）启动子突变纳入初始治疗后最近提出的风险重新分类系统[动态风险分层（DRS）]，以更好地分类和预测预后。
共纳入357例无初始远处转移的分化型甲状腺癌（DTC）患者。在TERT突变和野生型患者中，根据DRS分组比较无复发生存期（RFS）。采用Cox回归计算调整后的风险比（AHR）以得出AHR组。将AHR分组系统在预测结构复发和癌症特异性生存（CSS）方面的表现与当前的DRS系统和肿瘤/淋巴结/转移（TNM）分类进行比较。
在357例患者中，中位随访14年期间有90例复发和15例癌症相关死亡。AHR组较高的患者复发风险较高（AHR 1、2、3和4组的10年RFS：94.9%、82.7%、50.2%和23.1%；P<0.001），癌症相关死亡风险也较高（10年CSS：100.0%、98.7%、94.2%和76.9%；P<0.001）。AHR和DRS分组预测复发能力的方差解释比例（PVE）分别为22.4%和18.5%。AHR和TNM系统预测癌症相关死亡的PVE分别为11.5%和7.4%。
AHR分组系统是一种简单的二维预后系统，在预测结构复发方面与DRS一样有效，并为非转移性DTC患者的长期CSS提供临床指导。
