Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. Cancer screening in the healthy population involves an initial risk stratification step to determine the screening method and frequency, primarily to optimize resource allocation by targeting screening towards individuals who draw most benefit. For most screening programs, age and clinical risk factors such as family history are part of the initial risk stratification algorithm. In this paper, we focus on developing a blood marker-based risk stratification approach, which could be used to identify patients with elevated cancer risk to be encouraged for taking a diagnostic test or participate in a screening program. We demonstrate that the combination of simple, widely available blood tests, such as complete blood count and complete metabolic panel, could potentially be used to identify patients at risk for colorectal, liver, and lung cancers with areas under the ROC curve of 0.76, 0.85, 0.78, respectively. Furthermore, we hypothesize that such an approach could not only be used as pre-screening risk assessment for individuals but also as population health management tool, for example to better interrogate the cancer risk in certain sub-populations.

翻译：早期癌症筛查已被证实能提高患者生存率，并避免因晚期诊断而接受高强度且昂贵的治疗。健康人群的癌症筛查包含初始风险分层步骤，以确定筛查方法和频率，其主要目的是通过将筛查目标锁定在获益最大的个体来优化资源配置。对于大多数筛查项目，年龄和家族史等临床风险因素被纳入初始风险分层算法。本文重点开发一种基于血液标志物的风险分层方法，该方法可用于识别癌症风险升高的患者，鼓励其接受诊断检测或参与筛查项目。我们证明，通过结合使用简单且广泛可得的血液检测（如全血细胞计数和全套代谢检测），可有效识别结直肠癌、肝癌和肺癌高风险患者，其ROC曲线下面积分别为0.76、0.85和0.78。此外，我们提出假设：这种方法不仅可作为个体筛查前的风险评估工具，还可作为人群健康管理工具，例如用于更精准地评估特定亚人群的癌症风险。