Singh Vivek, Chaganti Shikha, Siebert Matthias, Rajesh Sowmya, Puiu Andrei, Gopalan Raj, Gramz Jamie, Comaniciu Dorin, Kamen Ali
Siemens Healthineers, Digital Technology and Innovation, Princeton, 08540, USA.
Siemens Healthineers, Digital Technology and Innovation, 91052, Erlangen, Germany.
Sci Rep. 2025 Apr 12;15(1):12661. doi: 10.1038/s41598-025-97331-6.
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.
癌症早期筛查已被证明可提高生存率，并使患者避免因晚期诊断而接受强化和昂贵的治疗。健康人群的癌症筛查包括一个初始风险分层步骤，以确定筛查方法和频率，主要是通过针对受益最大的个体进行筛查来优化资源分配。对于大多数筛查项目来说，年龄和家族史等临床风险因素是初始风险分层算法的一部分。在本文中，我们专注于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，鼓励他们进行诊断测试或参与筛查项目。我们证明，简单且广泛可用的血液检测，如全血细胞计数和全代谢组检测，联合使用可能有助于识别结直肠癌、肝癌和肺癌的高危患者，其受试者工作特征曲线下面积分别为0.76、0.85、0.78。此外，我们推测这种方法不仅可用作个体的预筛查风险评估，还可用作人群健康管理工具，例如更好地调查某些亚人群的癌症风险。
