验证 ENDPAC 模型：识别有患胰腺癌风险的新发糖尿病患者。
Validation of the ENDPAC model: Identifying new-onset diabetics at risk of pancreatic cancer.
机构信息
Department of Medicine, School of Medicine, West Virginia University, USA.
Department of Pharmaceutical Systems and Policy, West Virginia University School of Pharmacy, USA; School of Mathematics and Natural Sciences, Tadulako University, Indonesia.
出版信息
Pancreatology. 2021 Apr;21(3):550-555. doi: 10.1016/j.pan.2021.02.001. Epub 2021 Feb 8.
BACKGROUND
Patients with new-onset diabetes are known to be at a higher risk of developing pancreatic cancer. The Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) model was recently developed to identify new-onset diabetics with this higher risk. Further validation is needed before the ENDPAC model is implemented as part of a screening program to identify pancreatic cancer.
METHODS
A retrospective case-control study was performed; a cohort of patients with new-onset diabetes was identified using hemoglobin A1c. Patients were scored by the ENDPAC model and then divided based on whether pancreatic cancer was diagnosed after the diagnosis of diabetes. The performance of the model was assessed globally and at different cutoffs.
RESULTS
There were 6254 controls and 48 cases of pancreatic cancer. Bivariate analysis showed that patients with pancreatic cancer lost weight before diagnosis while controls gained weight (-0.93 kg/m2 vs. 0.45 kg/m2, p < 0.00∗). Cases had a more significant increase in their HbA1C from one year before (1.3% vs. 0.82%, p = 0.02). Smoking and pancreatitis rates were higher in cases compared to controls (p < 0.00∗). The area under the curve (AUC) of the ENDPAC model was 0.72. A score >1 was the optimal cutoff. At this cutoff, the sensitivity was 56%, specificity was 75%, and pancreatic cancer prevalence increased from 0.78% at baseline to 1.7%.
CONCLUSION
The ENDPAC model was validated in an independent cohort of patients with new-onset diabetes.
背景
患有新发糖尿病的患者已知存在更高的罹患胰腺癌风险。最近开发了一种名为 Enriching New-Onset Diabetes for Pancreatic Cancer（ENDPAC）的模型，用于识别具有更高风险的新发糖尿病患者。在将 ENDPAC 模型作为识别胰腺癌的筛查计划的一部分实施之前，需要进一步验证。
方法
进行了一项回顾性病例对照研究；使用糖化血红蛋白鉴定了新诊断糖尿病患者的队列。通过 ENDPAC 模型对患者进行评分，然后根据在糖尿病诊断后是否诊断出胰腺癌对患者进行分组。对模型进行了全局评估和不同截断值的评估。
结果
共纳入 6254 例对照和 48 例胰腺癌病例。双变量分析显示，诊断前患有胰腺癌的患者体重减轻，而对照组患者体重增加（-0.93kg/m2 比 0.45kg/m2，p<0.00∗）。病例组患者从一年前开始，HbA1C 升高更明显（1.3%比 0.82%，p=0.02）。与对照组相比，病例组的吸烟率和胰腺炎发生率更高（p<0.00∗）。ENDPAC 模型的曲线下面积（AUC）为 0.72。评分>1 为最佳截断值。在此截断值下，敏感性为 56%，特异性为 75%，并且胰腺癌患病率从基线时的 0.78%增加到 1.7%。
结论
ENDPAC 模型在另一组新发糖尿病患者中得到了验证。
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