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早期检测倡议:一项基于算法的筛查在新发高血糖和糖尿病患者中用于早期检测胰腺导管腺癌的随机对照试验。

Early Detection Initiative: A randomized controlled trial of algorithm-based screening in patients with new onset hyperglycemia and diabetes for early detection of pancreatic ductal adenocarcinoma.

机构信息

University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.

Pancreatic Cancer Action Network, Manhattan Beach, CA, USA.

出版信息

Contemp Clin Trials. 2022 Feb;113:106659. doi: 10.1016/j.cct.2021.106659. Epub 2021 Dec 23.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the only leading cause of cancer death without an early detection strategy. In retrospective studies, 0.5-1% of subjects >50 years of age who newly develop biochemically-defined diabetes have been diagnosed with PDAC within 3 years of meeting new onset hyperglycemia and diabetes (NOD) criteria. The Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) algorithm further risk stratifies NOD subjects based on age and changes in weight and diabetes parameters. We present the methodology for the Early Detection Initiative (EDI), a randomized controlled trial of algorithm-based screening in patients with NOD for early detection of PDAC. We hypothesize that study interventions (risk stratification with ENDPAC and imaging with Computerized Tomography (CT) scan) in NOD will identify earlier stage PDAC. EDI uses a modified Zelen's design with post-randomization consent. Eligible subjects will be identified through passive surveillance of electronic medical records and eligible study participants randomized 1:1 to the Intervention or Observation arm. The sample size is 12,500 subjects. The ENDPAC score will be calculated only in those randomized to the Intervention arm, with 50% (n = 3125) expected to have a high ENDPAC score. Consenting subjects in the high ENDPAC group will undergo CT imaging for PDAC detection and an estimate of potential harm. The effectiveness and efficacy evaluation will compare proportions of late stage PDAC between Intervention and Observation arm per randomization assignment or per protocol, respectively, with a planned interim analysis. The study is designed to improve the detection of sporadic PDAC when surgical intervention is possible.

摘要

胰腺导管腺癌 (PDAC) 是唯一一种没有早期检测策略的癌症死亡主要原因。在回顾性研究中,50 岁以上新诊断为生化定义的糖尿病患者中,有 0.5-1%在符合新发高血糖和糖尿病 (NOD) 标准后 3 年内被诊断为 PDAC。Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) 算法进一步根据年龄和体重及糖尿病参数的变化对 NOD 患者进行风险分层。我们介绍了早期检测倡议 (EDI) 的方法学,这是一项针对 NOD 患者进行基于算法筛查的随机对照试验,旨在早期检测 PDAC。我们假设研究干预措施(基于 ENDPAC 的风险分层和计算机断层扫描 (CT) 扫描成像)在 NOD 中可以识别更早阶段的 PDAC。EDI 使用改良的 Zelen 设计,在随机分组后进行知情同意。符合条件的患者将通过电子病历的被动监测进行识别,符合条件的研究参与者将以 1:1 的比例随机分配到干预组或观察组。样本量为 12500 例。仅在随机分配到干预组的患者中计算 ENDPAC 评分,预计 50%(n=3125)的患者具有高 ENDPAC 评分。高 ENDPAC 组的同意患者将接受 CT 成像以检测 PDAC 并评估潜在危害。有效性和疗效评估将分别比较干预组和观察组按随机分组或按方案分配的晚期 PDAC 比例,并计划进行中期分析。该研究旨在提高手术干预可能时散发性 PDAC 的检测率。

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