应用Nomogram术前预测老年胰腺神经内分泌肿瘤远处转移。

Gang Li, Yun-Tao Bing, Mao-Lin Tian, Chun-Hui Yuan, Dian-Rong Xiu
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引用次数: 2

摘要

目的建立预测老年胰腺神经内分泌肿瘤(pNETs)远处转移风险的形态图。方法从监测、流行病学和最终结果(SEER)数据库中提取1973年至2015年年龄≥65岁诊断为pNETs的患者数据。所有符合条件的患者随机分为训练组和验证组。对训练队列进行单因素和多因素logistic回归分析,以确定远处转移的独立因素。采用R软件的rms包,根据独立危险因素绘制nomogram,内部由培训队列进行验证,外部由验证队列使用C-index和校准曲线进行验证。结果共纳入411例老年患者,其中训练组260例,验证组151例。单因素和多因素logistic回归分析显示:肿瘤部位(胰腺体/尾部):优势比[OR]=2.282;95%置信区间[CI]: 1.174 ~ 4.436, POR=2.600, 95% CI: 1.266 ~ 5.339, POR=8.913, 95% CI: 1.985 ~ 40.010, POR=11.830, 95% CI: 2.530 ~ 55.350, POR=68.650, 95% CI: 8.020 ~ 587.600, POR=3.480, 95% CI: 1.807 ~ 6.703, PCI: 0.757 ~ 0.861),内部验证和外部验证分别为0.795 (95% CI: 0.723 ~ 0.867)。预测的远处转移率与标定曲线的观测值吻合较好。结论所建立的nomogram评估老年pNETs患者远处转移风险的能力和准确性较高,可为老年pNETs患者的个体化肿瘤评估和治疗决策提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using a Nomogram to Preoperatively Predict Distant Metastasis of Pancreatic Neuroendocrine Tumor in Elderly Patients.

Objective To establish a nomogram for predicting the distant metastasis risk of pancreatic neuroendocrine tumors (pNETs) in elderly patients. Methods We extracted data of patients with diagnosis of pNETs at age ≥65 years old between 1973 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. All eligible patients were divided randomly into a training cohort and validation cohort. Uni- and multivariate logistic regression analyses were performed on the training cohort to identify independent factors for distant metastasis. A nomogram was developed based on the independent risk factors using rms packages of R software, and was validated internally by the training cohort and externally by the validation cohort using C-index and calibration curves. Results A total of 411 elderly patients were identified, of which 260 were assigned to training cohort and 151 to validation cohort. Univariate and multivariate logistic regression analyses indicated the tumor site (body/tail of pancreas: odds ratio [OR]=2.282; 95% confidence interval [CI]: 1.174 - 4.436, P<0.05), histological grade (poorly differentiated/undifferentiated: OR=2.600, 95% CI: 1.266-5.339, P<0.05), T stage (T2: OR=8.913, 95% CI: 1.985-40.010, P<0.05; T3: OR=11.830, 95% CI: 2.530-55.350, P<0.05; T4: OR=68.650, 95% CI: 8.020-587.600, P<0.05), and N stage (N1: OR=3.480, 95% CI: 1.807-6.703, P<0.05) were identified as independent risk factors for distant metastasis of pNETs in elderly. The nomogram exhibited good predicting accuracy, with a C-index of 0.809 (95% CI: 0.757 - 0.861) in internal validation and 0.795 (95% CI: 0.723 - 0.867) in external validation, respectively. The predicted distant metastasis rates were in satisfactory agreement with the observed values by the calibration curves. Conclusion The nomogram we established showed high discriminative ability and accuracy in evaluation of distant metastasis risk in elderly pNETs patients, and could provide a reference for individualized tumor evaluation and treatment decision in elderly pNETs patients.

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