Department of Head and Neck Surgery, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, 510095, Guangdong Province, PR China.
Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou, 570102, Hainan Province, PR China.
Int J Surg. 2020 Apr;76:163-170. doi: 10.1016/j.ijsu.2020.03.010. Epub 2020 Mar 12.
Recurrence is still major obstacle to long-term survival in laryngeal squamous cell carcinoma (LSCC). We aimed to establish and validate a nomogram to precisely predict recurrence probability in patients with LSCC.
A total of 283 consecutive patients with LSCC received curative-intend surgery between 2011 and 2014 at were enrolled in this study. Subsequently, 283 LSCC patients were randomly assigned to a training cohort (N = 171) and a validation cohort (N = 112) in a 3:2 ratio. According to the results of multivariable Cox regression analysis in the training cohort, we developed a nomogram. The predictive accuracy and discriminative ability of the nomogram were evaluated by calibration curve and concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was performed to estimate clinical value of our nomogram.
Six independent factors rooted in multivariable analysis of the training cohort to predict recurrence were age, tumor site, smoking, alcohol, N stage and hemoglobin, which were all integrated into the nomogram. The calibration curve for the probability of recurrence presented that the nomogram-based predictions were in good correspondence with actual observations. The C-index of the nomogram was 0.81 (0.75-0.88), and the area under curve (AUC) of nomogram in predicting recurrence free survival (RFS) was 0.894, which were significantly better than traditional TNM stage. Decision curve analysis further affirmed that our nomogram had a larger net benefit than TNM stage. The results were confirmed in the validation cohort.
A risk prediction nomogram for patients with LSCC, incorporating readily assessable clinicopathologic variables, generates more accurate estimations of the recurrence probability when compared TNM stage alone, but still needs additional data before being used in clinical implications.
复发仍然是喉鳞状细胞癌（LSCC）长期生存的主要障碍。我们旨在建立和验证一个列线图，以准确预测 LSCC 患者的复发概率。
本研究共纳入 2011 年至 2014 年间接受根治性手术的 283 例连续 LSCC 患者。随后，将 283 例 LSCC 患者按 3:2 的比例随机分配至训练队列（N=171）和验证队列（N=112）。根据训练队列中多变量 Cox 回归分析的结果，我们制定了一个列线图。通过校准曲线和一致性指数（C 指数）评估列线图的预测准确性和区分能力，并通过 C 指数、接受者操作特征（ROC）分析与 TNM 分期系统进行比较。通过决策曲线分析（DCA）评估我们的列线图的临床价值。
多变量分析确定了 6 个独立因素来预测训练队列中的复发，包括年龄、肿瘤部位、吸烟、饮酒、N 分期和血红蛋白，这些因素都被纳入了列线图。复发概率的校准曲线表明，列线图预测与实际观察结果具有良好的一致性。列线图的 C 指数为 0.81（0.75-0.88），预测无复发生存率（RFS）的曲线下面积（AUC）为 0.894，均明显优于传统的 TNM 分期。决策曲线分析进一步证实，我们的列线图比 TNM 分期具有更大的净获益。验证队列的结果得到了证实。
一个包含易于评估的临床病理变量的 LSCC 患者风险预测列线图，与单独使用 TNM 分期相比，可以更准确地估计复发概率，但在临床应用之前仍需要更多的数据。
Zotero 插件