Hu Miaomiao, Lv Lulu, Dong Hongfeng
Department of Radiology, The First People's Hospital of Huzhou, Huzhou, China.
Department of Radiology, Xuzhou Central Hospital, Xuzhou, China.
Front Oncol. 2024 Aug 29;14:1443213. doi: 10.3389/fonc.2024.1443213. eCollection 2024.
To construct a CT-based diagnostic nomogram for distinguishing grade 3 pancreatic neuroendocrine tumors (G3 PNETs) from pancreatic ductal adenocarcinomas (PDACs) and assess their respective survival outcomes.
Patients diagnosed with G3 PNETs (n = 30) and PDACs (n = 78) through surgery or biopsy from two medical centers were retrospectively identified. Demographic and radiological information, including age, gender, tumor diameter, shape, margin, dilatation of pancreatic duct, and invasive behavior, were carefully collected. A nomogram was established after univariate and multivariate logistic regression analyses. The Kaplan-Meier survival was performed to analyze their survival outcomes.
Factors with a p-value <0.05, including age, CA 19-9, pancreatic duct dilatation, irregular shape, ill-defined margin, pancreatic atrophy, combined pancreatitis, arterial/portal enhancement ratio, were included in the multivariate logistic analysis. The independent predictive factors, including age (OR, 0.91; 95% CI, 0.85-0.98), pancreatic duct dilatation (OR, 0.064; 95% CI, 0.01-0.32), and portal enhancement ratio (OR, 1,178.08; 95% CI, 5.96-232,681.2) were determined to develop a nomogram. The internal calibration curve and decision curve analysis demonstrate that the nomogram exhibits good consistency and discriminative capacity in distinguishing G3 PNETs from PDACs. Patients diagnosed with G3 PNETs exhibited considerably better overall survival outcomes compared to those diagnosed with PDACs (median survival months, 42 vs. 9 months, p < 0.001).
The nomogram model based on age, pancreatic duct dilatation, and portal enhancement ratio demonstrates good accuracy and discriminative ability effectively predicting the probability of G3 PNETs from PDACs. Furthermore, patients with G3 PNETs exhibit better prognosis than PDACs.
构建基于CT的诊断列线图,以区分3级胰腺神经内分泌肿瘤(G3 PNETs)和胰腺导管腺癌(PDACs),并评估它们各自的生存结局。
回顾性纳入两个医疗中心通过手术或活检确诊为G3 PNETs(n = 30)和PDACs(n = 78)的患者。仔细收集人口统计学和放射学信息,包括年龄、性别、肿瘤直径、形状、边缘、胰管扩张和侵袭行为。经过单因素和多因素逻辑回归分析后建立列线图。采用Kaplan-Meier生存分析来分析它们的生存结局。
多因素逻辑回归分析纳入p值<0.05的因素,包括年龄、CA 19-9、胰管扩张、形状不规则、边缘不清、胰腺萎缩、合并胰腺炎、动脉/门静脉强化率。确定独立预测因素包括年龄(OR,0.91;95%CI,0.85-0.98)、胰管扩张(OR,0.064;95%CI,0.01-0.32)和门静脉强化率(OR,1,178.08;95%CI,5.96-232,681.2),据此绘制列线图。内部校准曲线和决策曲线分析表明,该列线图在区分G3 PNETs和PDACs方面具有良好的一致性和鉴别能力。与诊断为PDACs的患者相比,诊断为G3 PNETs的患者总体生存结局明显更好(中位生存月数,42对9个月,p < 0.001)。
基于年龄、胰管扩张和门静脉强化率的列线图模型具有良好的准确性和鉴别能力,能有效预测G3 PNETs与PDACs的概率。此外,G3 PNETs患者的预后优于PDACs患者。