Zhang Chuanzhao, Wu Yanxia, Zhuang Hongkai, Li Dezhi, Lin Ye, Yin Zi, Lu Xin, Hou Baohua, Jian Zhixiang
Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, People's Republic of China.
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510080, People's Republic of China.
Cancer Manag Res. 2019 Aug 5;11:7345-7352. doi: 10.2147/CMAR.S200340. eCollection 2019.
Development of an accurate model to predict prognosis for patients with pancreatic neuroendocrine tumors (P-NETs) after surgical resection is urgently needed.
In the present study, we conducted Cox proportional hazards regression to identify critical prognostic factors for P-NETs by analyzing data from 2174 patients in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of multivariate analysis, a novel nomogram was established. Finally, the novel nomogram for P-NETs was validated in a cohort of 81 patients from a Chinese institute.
In the multivariate analysis, age, tumor location, American Joint Committee on Cancer (AJCC) stage, histologic grade, lymph node ratio (LNR) and tumor size were independent risk factors for overall survival (OS) in P-NET patients who underwent radical resection. A nomogram consisting of age, sex, AJCC stage and histologic grade was found to have a concordance index (C-index) of 0.79 for OS in the SEER database, which was significantly higher than the C-index based on the AJCC stage, European Neuroendocrine Tumor Society (ENETS) stage or histologic grade alone. In the validation cohort, the C-index based on the nomogram reached 0.78 for OS. We also defined high-risk (total points >13.5 based on the nomogram) and low-risk populations (total points <13.5 based on the nomogram) in the validation cohort. We found that the actual 5-year recurrence rate in the high-risk group was significantly higher than that in the low-risk group (80.8% vs 23.4%, <0.001). Kaplan-Meier analysis showed that the 5-year recurrence-free survival (RFS) in the low-risk group was significantly higher than that in the high-risk group (<0.001).
An AJCC stage- and histologic grade-based model was found to be extremely efficient in predicting survival for patients with P-NETs after surgical resection and deserves further evaluation for future clinical applications.
迫切需要开发一种准确的模型来预测胰腺神经内分泌肿瘤（P-NETs）患者手术切除后的预后。
在本研究中，我们通过分析监测、流行病学和最终结果（SEER）数据库中2174例患者的数据，进行Cox比例风险回归以确定P-NETs的关键预后因素。基于多变量分析结果，建立了一种新型列线图。最后，在一家中国机构的81例患者队列中对新型P-NETs列线图进行了验证。
在多变量分析中，年龄、肿瘤位置、美国癌症联合委员会（AJCC）分期、组织学分级、淋巴结比率（LNR）和肿瘤大小是接受根治性切除的P-NET患者总生存（OS）的独立危险因素。发现由年龄、性别、AJCC分期和组织学分级组成的列线图在SEER数据库中OS的一致性指数（C指数）为0.79，显著高于仅基于AJCC分期、欧洲神经内分泌肿瘤学会（ENETS）分期或组织学分级的C指数。在验证队列中，基于列线图的OS的C指数达到0.78。我们还在验证队列中定义了高危人群（基于列线图总分>13.5）和低危人群（基于列线图总分<13.5）。我们发现高危组的实际5年复发率显著高于低危组（80.8%对23.4%，<0.001）。Kaplan-Meier分析显示低危组的5年无复发生存（RFS）显著高于高危组（<0.001）。
发现基于AJCC分期和组织学分级的模型在预测P-NET患者手术切除后的生存方面极其有效，值得在未来临床应用中进一步评估。
