Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, California.
Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California.
Cancer Epidemiol Biomarkers Prev. 2022 Jan;31(1):242-253. doi: 10.1158/1055-9965.EPI-21-0712. Epub 2021 Nov 2.
Worsening glycemic control indicates elevated risk of pancreatic ductal adenocarcinoma (PDAC). We developed prediction models for PDAC among those with worsening glycemic control after diabetes diagnosis.
In 2000-2016 records within the Veterans Affairs Health System (VA), we identified three cohorts with progression of diabetes: (i) insulin initiation ( = 449,685), (ii) initiation of combination oral hypoglycemic medication ( = 414,460), and (iii) hemoglobin A1c (HbA1c) ≥8% with ≥Δ1% within 15 months ( = 593,401). We computed 12-, 36-, and 60-month incidence of PDAC and developed prediction models separately for males and females, with consideration of >30 demographic, behavioral, clinical, and laboratory variables. Models were selected to optimize Akaike's Information Criterion, and performance for predicting 12-, 36-, and 60-month incident PDAC was evaluated by bootstrap.
Incidence of PDAC was highest for insulin initiators and greater in males than in females. Optimism-corrected c-indices of the models for predicting 36-month incidence of PDAC in the male population were: (i) 0.72, (ii) 0.70, and (iii) 0.71, respectively. Models performed better for predicting 12-month incident PDAC [c-index (i) 0.78, (ii) 0.73, (iii) 0.76 for males], and worse for predicting 60-month incident PDAC [c-index (i) 0.69, (ii) 0.67, (iii) 0.68 for males]. Model performance was lower among females. For subjects whose model-predicted 36-month PDAC risks were ≥1%, the observed incidences were (i) 1.9%, (ii) 2.2%, and (iii) 1.8%.
Sex-specific models for PDAC can estimate risk of PDAC at the time of progression of diabetes.
Our models can identify diabetes patients who would benefit from PDAC screening.
血糖控制恶化表明胰腺导管腺癌(PDAC)的风险增加。我们在糖尿病诊断后血糖控制恶化的人群中开发了 PDAC 的预测模型。
在退伍军人事务部医疗系统(VA)的 2000-2016 年记录中,我们确定了糖尿病进展的三个队列:(i)胰岛素起始(=449685),(ii)联合口服降糖药起始(=414460),和(iii)糖化血红蛋白(HbA1c)≥8%,且在 15 个月内≥Δ1%(=593401)。我们计算了 PDAC 的 12、36 和 60 个月的发生率,并分别为男性和女性开发了预测模型,同时考虑了>30 个人口统计学、行为、临床和实验室变量。模型的选择是为了优化赤池信息量准则,通过自举法评估了预测 12、36 和 60 个月 PDAC 发生率的模型性能。
PDAC 的发生率在胰岛素起始者中最高,男性高于女性。男性人群中预测 36 个月 PDAC 发生率的模型的乐观校正 c 指数分别为:(i)0.72,(ii)0.70,和(iii)0.71。模型在预测 12 个月的 PDAC 发生率方面表现更好[c 指数(i)0.78,(ii)0.73,(iii)0.76 用于男性],而在预测 60 个月的 PDAC 发生率方面表现更差[c 指数(i)0.69,(ii)0.67,(iii)0.68 用于男性]。女性的模型性能较低。对于模型预测的 36 个月 PDAC 风险≥1%的受试者,观察到的发生率分别为:(i)1.9%,(ii)2.2%,和(iii)1.8%。
用于 PDAC 的性别特异性模型可以估计糖尿病进展时 PDAC 的风险。
我们的模型可以识别出从 PDAC 筛查中受益的糖尿病患者。