Compliance With Lung Cancer Screening

描述（由申请人提供）：随机癌症筛查试验被认为是评估新的癌症筛查技术的最佳方法。不幸的是，如果研究参与者未能遵守筛查、诊断确认或治疗，这些试验可能低估了一种新的筛查技术的功效。在这项研究中，我们建议在一项大型多中心肺癌筛查试验中检查与癌症筛查不依从性相关的因素。本研究将使用美国放射学会（ACRIN）国家肺筛查试验（NLST）部门收集的现有数据进行。ACRIN负责在美国23个地点对18,843名参与者进行筛查。目前正在对这些参与者进行随访，以确定低剂量螺旋计算机断层扫描（CT）或胸部x射线（CXR）筛查是否能降低肺癌死亡率。我们将重点关注在基线筛查检查中被诊断为肺癌阴性或假阳性的参与者（即筛查检查是阳性的，但进一步的测试表明筛查异常是良性的）。我们在这项试验中的第一个目的是确定在基线筛查检查中被诊断为肺癌假阳性的参与者是否比接受筛查结果为阴性的参与者更不可能在下一次计划的筛查检查中再次接受筛查。我们在这项试验中的第二个目的是确定那些参与者的特征，在基线筛查检查之前测量，这些特征与下一次计划筛查检查的不依从性有关。在这一阶段的研究中，我们计划考察人口统计学因素的影响，包括性别、年龄、种族、教育程度、收入、国家地区，以及健康史、肺癌家族史、吸烟状况和吸烟史、健康相关的生活质量指数、肺癌感知风险。获得与不依从性相关的特征信息有两个原因：1)与不依从性相关的特征信息可用于在未来的临床试验和临床实践中更好地针对干预措施并减少不依从性，2)分析临床试验的标准方法是治疗意图（ITT）分析，在该分析中，无论参与者是否不依从，都比较两个随机分组的结果。然而，使用ITT分析，假设在试验中观察到的不遵守率将与实施干预的社区中的不遵守率相等。通常情况并非如此。在筛查试验中，参与者多而预期癌症病例少，即使一小部分参与者不遵守筛查、随访或治疗，也可能导致对筛查检查效果的不准确估计。本研究的重点是筛查阶段的不依从性。未来的工作将检查诊断随访和治疗的不依从性，并将不依从性信息用于开发模型，以估计在不同条件下和不同目标人群中肺癌筛查的潜在有效性。本研究旨在探讨与癌症筛查不依从性相关的因素。有关不依从性原因的信息可用于制定量身定制的干预措施，旨在提高未来临床试验和临床实践中的依从性。这些信息也可用于开发模型，以估计在不同条件下和不同目标人群中肺癌筛查的潜在有效性。

DESCRIPTION (provided by applicant): Randomized cancer screening trials are considered the best approach for evaluating new cancer screening technologies. Unfortunately, these trials may underestimate the efficacy of a new screening technique if study participants fail to comply with screening, diagnostic confirmation, or treatment. In this study, we propose to examine the factors associated with cancer screening nonadherence in a large, multi-center lung cancer screening trial. This study will be conducted using existing data collected as part of the American College of Radiology (ACRIN) arm of the National Lung Screening Trial (NLST). ACRIN is responsible for screening 18,843 participants at 23 sites across the United States. These participants are currently being followed to determine whether screening with low-dose spiral computed tomography (CT) or chest X-ray (CXR) reduces lung cancer mortality. We will focus on participants who receive a diagnosis at the baseline screening exam that is negative or false positive for lung cancer (meaning that the screening exam is positive, but further testing indicates that the screening abnormality is benign). Our first aim in this trial is to determine whether participants who receive a diagnosis that is false positive for lung cancer at the baseline screening exam are less likely to return for screening at their next scheduled screening exam than are participants who receive a screening result negative for lung cancer. Our second aim in this trial is to identify those participant characteristics, measured before the baseline screening exam, that are associated with nonadherence at the next scheduled screening exam. In this phase of the study, we plan to examine the influence of demographic factors, including sex, age, race, education level, income, area of the country, as well as health history, family history of lung cancer, smoking status and history, health related quality of life indices, and perceived risk of lung cancer. Obtaining information on characteristics associated with noncompliance is useful for two reasons: 1) Information on characteristics associated with noncompliance can be used to better target interventions and reduce nonadherence in future clinical trials and clinical practice, and 2) The standard approach to analyzing clinical trials is the intent to treat (ITT) analysis, in which the outcome of interest is compared between the two randomization groups regardless of participant noncompliance. Using an ITT analysis, however, assumes that the noncompliance rate observed in the trial will be equal to that in the communities in which the intervention will be implemented. This is often not the case. In screening trials, with many participants and few anticipated cancer cases, noncompliance by even a small proportion of participants with screening, follow-up, or treatment, may lead to inaccurate estimates of the efficacy of the screening exam. This study focuses on noncompliance at the screening stage. Future work will examine noncompliance with diagnostic follow-up and treatment and use the information on noncompliance to developed models that estimate the potential effectiveness of lung cancer screening under different conditions and in different target populations. This study proposes to examine factors that are associated with cancer screening nonadherence. Information on the reasons for nonadherence may be used to develop tailored interventions designed to improve adherence in future clinical trials and in clinical practice. This information may also be used to develop models that estimate the potential effectiveness of lung cancer screening under different conditions and in different target populations.