Department of Respiratory and Critical Care Medicine, Chengdu Second People's Hospital, Chengdu, China.
Department of Gastroenterology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
PLoS One. 2023 Apr 24;18(4):e0284930. doi: 10.1371/journal.pone.0284930. eCollection 2023.
Our study aimed to construct and validate prognostic nomograms for predicting survival for patients with Nonfunctional Pancreatic neuroendocrine tumor (NF-pNET).
This retrospective study included 1824 patients diagnosed with NF-pNET in the Surveillance, Epidemiology and End Results database between 2004 and 2016. Randomization divided the patients into training (n = 1278) and validation (n = 546) cohorts. Prognostic factors were determined using Cox regression analyses, nomograms based on AJCC 7th and 8th staging system were constructed separately. The prediction models were validated using internal validation and external validation.
Age, year of diagnosis, primary tumor site, grade, 7th or 8th TNM stage, surgery, tumor size were determined as prognostic indicator to construct two nomograms. Harrell's concordance index (C-index) of two nomograms exhibited a clinical predictive ability of 0.828 (95%CI, 0.8080.849) vs 0.828 (95% CI, 0.8080.849) in the internal verification. The c-index in the external validation was 0.812 (95%CI, 0.7780.864) vs 0.814 (95% CI, 0.7790.848). The predictive power of the two nomograms is comparable.
Our nomogram may be a effective tool for predicting overall survival in patients with NF-pNET. The AJCC 8th-edition system provides discrimination similar to that of the 7th-edition system.
本研究旨在构建并验证用于预测非功能性胰腺神经内分泌肿瘤(NF-pNET)患者生存的预后列线图。
本回顾性研究纳入了 2004 年至 2016 年间 Surveillance, Epidemiology and End Results 数据库中诊断为 NF-pNET 的 1824 例患者。通过随机分组,将患者分为训练队列(n = 1278)和验证队列(n = 546)。使用 Cox 回归分析确定预后因素,分别基于 AJCC 第 7 版和第 8 版分期系统构建列线图。通过内部验证和外部验证对预测模型进行验证。
年龄、诊断年份、原发肿瘤部位、分级、第 7 或第 8 版 TNM 分期、手术、肿瘤大小被确定为构建两个列线图的预后指标。两个列线图的 Harrell 一致性指数(C-index)在内部验证中分别为 0.828(95%CI,0.8080.849)和 0.828(95%CI,0.8080.849),具有良好的临床预测能力。外部验证的 C-index 分别为 0.812(95%CI,0.7780.864)和 0.814(95%CI,0.7790.848)。两个列线图的预测能力相当。
我们的列线图可能是预测 NF-pNET 患者总体生存的有效工具。AJCC 第 8 版系统提供的区分度与第 7 版系统相似。