Lv Yang, Pu Ning, Mao Wei-Lin, Chen Wen-Qi, Wang Huan-Yu, Han Xu, Ji Yuan, Zhang Lei, Jin Da-Yong, Lou Wen-Hui, Xu Xue-Feng
Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China.
Endocr Connect. 2018 Nov;7(11):1178-1185. doi: 10.1530/EC-18-0353.
We aim to investigate the clinical characteristics of the rectal NECs and the prognosis-related factors and construct a nomogram for prognosis prediction.
The data of 41 patients and 1028 patients with rectal NEC were retrieved respectively from our institution and SEER database. OS or PFS was defined as the major study outcome. Variables were compared by chi-square test and t-test when appropriate. Kaplan-Meier analysis with log-rank test was used for survival analysis and the Cox regression analysis was applied. The nomogram integrating risk factors for predicting OS was constructed by R to achieve superior discriminatory ability. Predictive utility of the nomogram was determined by concordance index (C-index) and calibration curve.
In the univariate and multivariate analyses, tumor differentiation, N stage, M stage and resection of primary site were identified as independent prognostic indicators. The linear regression relationship was found between the value of Ki-67 index and the duration of OS (P < 0.05). Furthermore, the independent prognostic factors were added to formulate prognostic nomogram. The constructed nomogram showed good performance according to the C-index.
Contrary to WHO classification guideline, we found that the rectal NEC diseases are heterogeneous and should be divided as different categories according to the pathological differentiation. Besides, the nomogram formulated in this study showed excellent discriminative capability to predict OS for those patients. More advanced predictive model for this disease is required to assist risk stratification via the formulated nomogram.
我们旨在研究直肠神经内分泌癌(NECs)的临床特征、预后相关因素,并构建用于预后预测的列线图。
分别从我们机构和监测、流行病学与最终结果(SEER)数据库中检索41例患者及1028例直肠NEC患者的数据。总生存期(OS)或无进展生存期(PFS)被定义为主要研究结局。适当情况下,变量通过卡方检验和t检验进行比较。采用Kaplan-Meier分析和对数秩检验进行生存分析,并应用Cox回归分析。通过R软件构建整合预测OS风险因素的列线图,以实现卓越的辨别能力。通过一致性指数(C指数)和校准曲线确定列线图的预测效用。
在单因素和多因素分析中,肿瘤分化、N分期、M分期和原发部位切除被确定为独立的预后指标。发现Ki-67指数值与OS持续时间之间存在线性回归关系(P < 0.05)。此外,添加独立预后因素以制定预后列线图。根据C指数,构建的列线图显示出良好的性能。
与世界卫生组织(WHO)分类指南相反,我们发现直肠NEC疾病具有异质性,应根据病理分化分为不同类别。此外,本研究制定的列线图在预测这些患者的OS方面显示出出色的辨别能力。需要针对该疾病构建更先进的预测模型,以通过制定的列线图辅助进行风险分层。