Department of Gastroenterology, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui, China (mainland).
Med Sci Monit. 2020 Jun 21;26:e922613. doi: 10.12659/MSM.922613.
BACKGROUND This study was designed to predict prognosis of patients with primary duodenal neuroendocrine neoplasms (D-NENs) by developing nomograms. MATERIAL AND METHODS Patients diagnosed with D-NENs between 1988 and 2015 were queried from the SEER database and a total of 965 appropriate cases were randomly separated into the training and validation sets. Kaplan-Meier analysis was used to generated survival curves, and the difference among the groups was assessed by the log-rank test. Independent prognostic indicators were acquired by Cox regression analysis, and were used to develop predictive overall survival (OS) and cancer-specific survival (CSS) nomograms. Harrell's concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the efficacy of nomograms. Tumor stage was regarded as a benchmark in predicting prognostic compared with the nomograms built in this study. RESULTS The C-index was 0.739 (0.690-0.788) and 0.859 (0.802-0.916) for OS and CSS nomograms, respectively. Calibration curves exhibited obvious consistency between the nomograms and the actual observations. In addition, C-index, AUC, and DCA were better than tumor stage in the evaluative performance of nomograms. CONCLUSIONS The nomograms were able to predict the 1-, 5-, and 10-year OS and CSS for D-NENs patients. The good performance of these nomograms suggest that they can be used for evaluating the prognosis of patients with D-NENs and can facilitate individualized treatment in clinical practice.
背景 本研究旨在通过建立列线图来预测原发性十二指肠神经内分泌肿瘤(D-NENs)患者的预后。
材料与方法 从 SEER 数据库中检索 1988 年至 2015 年间诊断为 D-NENs 的患者,共随机分为训练集和验证集。Kaplan-Meier 分析生成生存曲线,对数秩检验评估组间差异。采用 Cox 回归分析获得独立预后指标,并用于建立预测总生存(OS)和癌症特异性生存(CSS)列线图。采用 Harrell 一致性指数(C-index)、曲线下面积(AUC)、校准曲线和决策曲线分析(DCA)评估列线图的效能。将肿瘤分期作为与本研究建立的列线图相比预测预后的基准。
结果 OS 和 CSS 列线图的 C-index 分别为 0.739(0.690-0.788)和 0.859(0.802-0.916)。校准曲线显示列线图与实际观察结果之间具有明显的一致性。此外,C-index、AUC 和 DCA 在评估列线图性能方面优于肿瘤分期。
结论 该列线图能够预测 D-NENs 患者的 1、5 和 10 年 OS 和 CSS。这些列线图性能良好,表明它们可用于评估 D-NENs 患者的预后,并有助于临床实践中的个体化治疗。