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Optimal Cut-Off Values of Lymph Node Ratio Predicting Recurrence in Papillary Thyroid Cancer

机译:淋巴结比率预测乳头状甲状腺癌复发的最佳临界值

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摘要

Regional lymph node (LN) metastasis has a significant impact for prediction of recurrence in patients with papillary thyroid cancers (PTC); however, the prognostic value of the lymph node ratio (LNR), which is defined as the ratio of the number of metastatic LNs to the total number of investigated LNs, is controversial. In this study, we determined the optimal cut-off values of LNRs for the prediction of recurrence in PTC patients.This large cohort study retrospectively evaluated 2294 patients who had undergone total thyroidectomy for PTC at a single institution from October 1985 to June 2009. The prediction probability of central LNR (cLNR, level VI) and total LNR (tLNR, levels II–VI) were estimated by binominal logistic regression analysis. Hazard ratios of the cut-off LNR values for cancer recurrence were calculated for relevant covariates using multivariate Cox regression analyses. Kaplan–Meier analyses were also utilized to assess the effects of estimated LNR cut-off values on recurrence-free survival (RFS).Of the 2294 patients, 138 (6.0%) presented cancer recurrence during the follow-up period (median duration = 107.1 months). The prediction probability indicated that LNRs of 0.4 and 0.5 for central LN and total LN, respectively, are optimal cut-off values for precise prediction with minimization of outliers. Multivariate Cox regression analyses revealed that cLNR ≥0.4 was independently predictive of recurrence in patients with N0 and N1a PTCs (hazard ratio [HR]: 7.016, 95% confidence interval [CI]: 3.72–12.986, P < 0.001) and that tLNR ≥0.5 indicated a significantly increased risk of recurrence in patients with N1b PTCs (HR: 2.372, 95% CI: 1.458–3.860, P < 0.001). In addition, Kaplan–Meier analyses clearly demonstrated that these LNR cut-off values are precisely operational in RFS estimation.The cut-off LNR values of 0.4 and 0.5 for cLNR and tLNR, respectively, were identified. Risk stratification combined with these LNR cut-off values may prove useful to determine treatment and follow-up strategies for PTC patients.
机译:区域淋巴结转移对预测甲状腺乳头状癌(PTC)患者的复发有重要影响。然而,淋巴结比率(LNR)的预后价值是有争议的,LNR定义为转移性LN数目与所调查LN总数的比率。在这项研究中,我们确定了预测PTC患者复发的LNR的最佳临界值。这项大型队列研究回顾性评估了从1985年10月至2009年6月在同一机构接受过甲状腺全切术的2294例患者。通过二项式logistic回归分析估计中心LNR(cLNR,VI级)和总LNR(tLNR,II–VI级)的预测概率。使用多元Cox回归分析计算相关协变量的癌症复发临界LNR值的危险比。 Kaplan–Meier分析还用于评估估计的LNR截止值对无复发生存(RFS)的影响。在2294例患者中,有138例(6.0%)在随访期间出现了癌症复发(中位持续时间= 107.1个月)。预测概率表明,对于中央LN和总LN而言,分别为0.4和0.5的LNR是最佳预测值,对于精确预测具有最小的离群值。多因素Cox回归分析显示,cLNR≥0.4独立预测N0和N1a PTC患者的复发(危险比[HR]:7.016,95%置信区间[CI]:3.72–12.986,P,<0.001),并且tLNR≥ 0.5表示N1b PTC患者的复发风险显着增加(HR:2.372,95%CI:1.458–3.860,P <0.001)。此外,Kaplan–Meier分析清楚地表明,这些LNR截止值在RFS估计中是精确可操作的。cLNR和tLNR的截止LNR值分别为0.4和0.5。风险分层与这些LNR截止值相结合可能被证明对于确定PTC患者的治疗和随访策略很有用。

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