Kaiser Permanente Southern California Research and Evaluation, 100 S. Los Robles Ave, Pasadena, CA, USA.
Kaiser Permanente Southern California Research and Evaluation, 100 S. Los Robles Ave, Pasadena, CA, USA.
Pancreatology. 2024 Nov;24(7):1115-1122. doi: 10.1016/j.pan.2024.09.015. Epub 2024 Sep 14.
BACKGROUND/OBJECTIVES: The Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) model relies primarily on fasting glucose values. Health systems have increasingly shifted practice towards use of glycated hemoglobin (HbA1c) measurement. We modified the ENDPAC model using patients with new onset hyperglycemia.
Four cohorts of patients 50-84 years of age with HbA1c results ≥6.2-6.5 % in 2011-2018 were identified. A combine cohort was formed. A widened eligibility criterion was applied to form additional four individual cohorts and one combined cohort. The primary outcome was the diagnosis of pancreatic cancer within 3 years after the first elevated HbA1c testing. The performance of the modified ENDPAC model was evaluated by AUC, sensitivity, positive predictive value, cases detected, and total number of patients screened.
The individual and combined cohorts consisted of 39,001-79,060 and 69,334-92,818 patients, respectively (mean age 63.5-65.0 years). The three-year PC incidence rates were 0.47%-0.54 %. The AUC measures were in the range of 0.75-0.77 for the individual cohorts and 0.75 for the combined cohorts. When the four individual cohorts were combined, more PC cases can be identified (149 by the combined vs. 113-116 by individual cohorts when risk score was 5+). Performance measures were compromised in nonwhites. Asian and Pacific islanders had lower sensitivity compared to other racial and ethnic groups (29 % vs. 50-60 %) when risk score was 5+.
The modified ENDPAC model targets a broader population and thus identifies more high-risk patients for cancer screening. The differential performance needs to be considered when the model is applied to non-white population.
背景/目的：Enriching New-Onset Diabetes for Pancreatic Cancer（ENDPAC）模型主要依赖于空腹血糖值。医疗系统已经越来越多地将实践转向使用糖化血红蛋白（HbA1c）测量。我们使用新发生高血糖的患者修改了 ENDPAC 模型。
在 2011-2018 年期间，确定了四个年龄在 50-84 岁之间、HbA1c 结果≥6.2-6.5%的患者队列。形成了一个合并队列。应用放宽的纳入标准形成了另外四个单独队列和一个合并队列。主要结局是在首次升高的 HbA1c 检测后 3 年内诊断为胰腺癌。通过 AUC、灵敏度、阳性预测值、检出病例数和筛查总患者数来评估修改后的 ENDPAC 模型的性能。
单个和合并队列分别包含 39001-79060 和 69334-92818 名患者（平均年龄 63.5-65.0 岁）。三年 PC 发生率为 0.47%-0.54%。个体队列的 AUC 测量值在 0.75-0.77 之间，合并队列的 AUC 测量值为 0.75。当四个单独队列合并时，可以识别出更多的 PC 病例（当风险评分为 5+时，联合队列的 149 例 vs. 单独队列的 113-116 例）。非白人的表现指标较差。当风险评分为 5+时，与其他种族和族裔群体相比，亚洲和太平洋岛民的敏感性较低（29% vs. 50-60%）。
修改后的 ENDPAC 模型针对更广泛的人群，因此可以识别更多高危癌症筛查患者。在将模型应用于非白人人群时，需要考虑到模型的不同性能。
