Department of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles, 2nd Floor, Pasadena, CA, 91101, USA.
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.
Dig Dis Sci. 2021 Jan;66(1):78-87. doi: 10.1007/s10620-020-06139-z. Epub 2020 Feb 28.
The risk of pancreatic cancer is elevated among people with new-onset diabetes (NOD). Based on Rochester Epidemiology Project Data, the Enriching New-Onset Diabetes for Pancreatic Cancer (END-PAC) model was developed and validated.
We validated the END-PAC model in a cohort of patients with NOD using retrospectively collected data from a large integrated health maintenance organization.
A retrospective cohort of patients between 50 and 84 years of age meeting the criteria for NOD in 2010-2014 was identified. Each patient was assigned a risk score (< 1: low risk; 1-2: intermediate risk; ≥ 3: high risk) based on the values of the predictors specified in the END-PAC model. Patients who developed pancreatic ductal adenocarcinoma (PDAC) within 3 years were identified using the Cancer Registry and California State Death files. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were estimated.
Out of the 13,947 NOD patients who were assigned a risk score, 99 developed PDAC in 3 years (0.7%). Of the 3038 patients who had a high risk, 62 (2.0%) developed PDAC in 3 years. The risk increased to 3.0% in white patients with a high risk. The AUC was 0.75. At the 3+ threshold, the sensitivity, specificity, PPV, and NPV were 62.6%, 78.5%, 2.0%, and 99.7%, respectively.
It is critical that prediction models are validated before they are implemented in various populations and clinical settings. More efforts are needed to develop screening strategies most appropriate for patients with NOD in real-world settings.
新发糖尿病(NOD)患者的胰腺癌风险升高。基于罗切斯特流行病学项目数据,开发并验证了新发糖尿病合并胰腺癌风险预测模型(END-PAC)。
我们使用大型综合医疗保健组织回顾性收集的数据,在 NOD 患者队列中验证 END-PAC 模型。
确定了 2010-2014 年符合 NOD 标准的 50-84 岁之间的回顾性队列患者。根据 END-PAC 模型中规定的预测因素值,为每位患者分配一个风险评分(<1:低风险;1-2:中风险;≥3:高风险)。通过癌症登记处和加利福尼亚州死亡档案确定在 3 年内发生胰腺导管腺癌(PDAC)的患者。估计曲线下面积(AUC)、敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)。
在被分配风险评分的 13947 名 NOD 患者中,有 99 名在 3 年内发生 PDAC(0.7%)。在 3038 名高风险患者中,有 62 名(2.0%)在 3 年内发生 PDAC。高风险的白人患者风险增加到 3.0%。AUC 为 0.75。在 3+阈值时,敏感性、特异性、PPV 和 NPV 分别为 62.6%、78.5%、2.0%和 99.7%。
在将预测模型应用于不同人群和临床环境之前,对其进行验证至关重要。需要做出更多努力,为真实世界环境中患有 NOD 的患者制定最适合的筛查策略。