
FOLLOWUS
Department of General Surgery, Peking University Third Hospital, Beijing 100191, China
Dianrong Xiu, xiudianrong1964@163.com
收稿日期:2020-02-20,
录用日期:2020-5-10,
纸质出版日期:2021-08-30
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李刚, 邴运韬, 田茂霖, 等. 使用列线图预测老年胰腺神经内分泌肿瘤患者手术前远处转移的风险[J]. 中国医学科学杂志(英文版), 2021,36(3):218-224.
Li Gang, Bing Yuntao, Tian Maolin, et al. Using a Nomogram to Preoperatively Predict Distant Metastasis of Pancreatic Neuroendocrine Tumor in Elderly Patients[J]. Chinese medical sciences journal, 2021, 36(3): 218-224.
李刚, 邴运韬, 田茂霖, 等. 使用列线图预测老年胰腺神经内分泌肿瘤患者手术前远处转移的风险[J]. 中国医学科学杂志(英文版), 2021,36(3):218-224. DOI: 10.24920/003722.
Li Gang, Bing Yuntao, Tian Maolin, et al. Using a Nomogram to Preoperatively Predict Distant Metastasis of Pancreatic Neuroendocrine Tumor in Elderly Patients[J]. Chinese medical sciences journal, 2021, 36(3): 218-224. DOI: 10.24920/003722.
目的
建立一个列线图来预测老年患者胰腺神经内分泌肿瘤(pancreatic neuroendocrine tumors
pNETs)远处转移的风险。
方法
从美国“肿瘤监测、流行病学和预后(Surveillance
Epidemiology
and End Results
SEER)数据库”中提取1973年至2015年之间年龄≥65岁pNETs患者的数据。所有符合条件的患者随机分为训练队列和验证队列。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风险因素。使用R软件的rms软件包基于独立风险因素开发列线图。使用C指数和校准曲线在训练队列进行内部验证
在验证队列进行外部验证。
结果
研究共确定了411名老年pNETs患者
260名被分配到训练队列
151名被分配到验证队列。单因素和多因素Logistic回归分析表明
肿瘤部位(胰腺体/尾:比值比[
OR
]=2.282;95%可信区间[
CI
]:1.174-4.436
P
<
0.05)
组织学分级(低分化/未分化:
OR
=2.600
95%
CI
:1.266-5.339
P
<
0.05)
T分期(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)和N分期(N1:
OR
=3.480
95%
CI
:1.807-6.703
P
<
0.05)被确定为老年人pNETs远处转移的独立危险因素。列线图显示出良好的预测准确性
内部验证的C指数为0.809(95%
CI
:0.757-0.861)
外部验证的C指数为0.795(95%
CI
:0.723-0.867)
预测的远处转移率与校准曲线的观察值吻合良好。
结论
我们建立的列线图在评估老年pNETs患者远处转移风险方面具有较好的辨别能力和准确性
可为老年pNETs患者的个体化评估和治疗决策提供参考。
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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