CA: A Cancer Journal for Clinicians ( IF 503.1 ) Pub Date : 2024-03-22 , DOI: 10.3322/caac.21836 Sam M Hanash 1 , Peter P Yu 2
The concept of blood-based multicancer early detection (MCED) tests has generated much excitement, in part because of the potential of such tests to reduce cancer mortality by encompassing cancers for which screening is currently not available. A review in this issue of CA: A Cancer Journal for Clinicians, largely authored by members in the Division of Cancer Prevention at the National Cancer Institute (NCI), addresses the current status of the field.1 The authors convey a reluctance to refer to the field as MCED. In their view and that of others, the evidence to date does not support substantial performance in detecting cancer at an early stage.2 Therefore, instead, they use the designation multicancer detection (MCD) tests. The authors describe a strategy for MCD tests adopted by developers, consisting of first detecting a cancer signal based on shared biomarkers across cancer types, followed by assessment of the tissue of origin based on another set of biomarkers. The review includes a list of developers of MCD tests and the performance of tests for which data have become publicly available based on their positive and negative predictive values. The authors also provide details of the NCI Vanguard program aimed, in the short term, at testing the performance of MCD platforms they have selected among applicants and, in the longer term, at conducting prospective, randomized clinical studies.
Although the review provides an assessment of the current status of the MCD/MCED field, there is much that we do not know and that remains to be determined. From an effectiveness point of view, the optimal number of cancer types to be included may be debated. Currently, screening is available in the United States for lung, breast, colon, cervical, and prostate cancers. Screening is also available for gastric cancer in Asian countries, where the incidence is high. Although MCD tests have the potential to encompass a much broader range of cancers, notably including cancers for which screening is not available, it is clear that a relatively small number of cancers account for the vast majority of cancer deaths. American Cancer Society cancer statistics 2024 data for US cancer mortality project that five cancer types account for greater than 50% of cancer deaths.3 For men, they include pancreas and hepatobiliary cancers and, for women, pancreas and ovarian cancers. Given that an MCD test may vary in its performance by cancer type in terms of sensitivity and specificity, overall test performance may degrade with attempts to universally cover a vast number of cancer types. Moreover, for common cancers for which screening strategies are recommended, should MCD tests result in improved positive predictive value of screening programs? For other malignancies, the underlying cancer biology or treatment approaches may obviate any benefit of an MCD test. For example, the authors point out that hematologic malignancies comprised 57% of early stage diagnoses in the Pathfinder study (ClinicalTrials.gov identifier NCT04241796)4 and that mortality gains are unlikely to come from the diagnoses of these cancer types. It may be argued that, because MCD tests are developed based on a comprehensive search for biomarkers, in addition to studying a set of molecular markers that identify cancer tissue of origin, it would be beneficial for MCD tests to encompass biomarkers that correlate with lethality, such as invasiveness and escape from immune surveillance, which are relevant for prognostication.
As the authors note, the underlying incidence of a cancer influences the positive predictive value of a screening test. If it were possible to identify individuals who are at higher risk for cancer either through their clinical, environmental, behavioral, or social determinants of health characteristics, then MCD testing would be expected to be of greater effectiveness. A recent study applied artificial intelligence methods to clinical data from several million individuals in Denmark and in the United States, resulting in a risk profile that, when applied, would improve the ability to design realistic surveillance programs for individuals at elevated risk.5 Populations with higher cancer risk caused by various exposures would be another rich opportunity to build an evidence base for the clinical utility of MCD.
A critical question remains around the performance requirements for MCD tests for their implementation in clinical practice. A recent publication covered the Early Detection Research Network's Phases of Biomarker Development for the rigorous evaluation of novel early detection biomarkers.6 Criteria include sufficient sensitivity in a prospective screening setting and a shift in detection to early curable stages, leading to clinically significant mortality benefit. The latter has yet to be demonstrated for MCD tests. Whether it should be a requirement may be debated, given the need for randomized screening trials at substantial cost and, with survival being a trailing metric, requiring long follow-up to ascertain, by which time the technology may have very well moved on. Models to evaluate clinical utility with alternative trial designs are needed. The Firefighters Cancer Registry Act directed the National Institute for Occupational Safety and Health and the Centers for Disease Control and Prevention to administer a cancer registry for firefighters, a population with known higher cancer risk. This registry could function as a database of MCD testing and provide real-world data to inform policy (https://www.cdc.gov/niosh/firefighters/registry/aboutnfr.html).
Because we do not know the clinical utility of MCD tests, at their current level of performance, we also do not understand how these tests should be optimally priced relative to their clinical value. The Pathfinder study required 473 tests to detect one individual with early stage cancer; the ratio for the DETECT-A study (Detecting Cancers Earlier Through Elective Mutation-Based Blood Collection and Testing) was one patient per 1239 tests. The downstream costs of false-positive tests, the quality of life-years gained by earlier detection, the cost reduction through avoidance of expensive interventions for advanced disease, and other economic outcome measures are unknown.
The implications of a negative MCD test and how often MCD tests should be administered are currently undetermined. There is concern that an individual who has a negative MCD test may forego recommended screening, although MCD tests are not considered an alternative to current screening modalities. Patients who have a positive MCD test but for whom further diagnostic testing fails to detect cancer are left with the troubling question of whether the MCD test was a false-positive result and no cancer is present or whether repeated diagnostic testing is needed in the event that occult cancer is indeed present. Moreover, how long is the reassurance of a negative MCD test good for, and how often should it be repeated since it is only a snapshot in time? Is there value in serial measurements wherein the predictive capability lies not in a threshold test value but in a rising pattern? A trajectory for such repeated tests may be beneficial. In a cohort study of pancreatic cancer, levels of CA 19-9 increased exponentially starting at 2 years before diagnosis,7 pointing to a potential benefit of establishing trajectories for biomarkers.
The authors largely represent the NCI’s perspective on test development. However, multiple federal agencies have regulatory interest in MCD, including the US Food and Drug Administration and the Centers for Medicare and Medicaid Services, as well as commercial insurance entities, along with patient advocacy organizations and unions in industries with occupational exposure. The adoption of MCD tests into clinical use is a microcosm of the larger discourse on how transformative technologies are both nurtured to maximize benefit and regulated to minimize risk.
MCD tests are representative of emergent technologies arising out of artificial intelligence. They incorporate biologic intelligence through the use of genomic, proteomic, and metabolomic biomarkers and other types of biomarkers. And their adoption in clinical practice will require emotional intelligence as part of shared decision making with consumers when the evidence base concerning the risk and benefit is still in formation. A cautious approach would be to first explore the value of MCD tests for individuals at increased risk for multiple cancer types, such as heavy smokers who have an increased risk not only for lung cancer but also cancers of the throat, esophagus, liver, and colorectum among others. An enhanced coverage policy will be needed that provides for necessary downstream testing and clinical follow-up while evidence of improved outcomes is sought. The potential for MCD tests to save lives through earlier detection of cancer is real, but we cannot be satisfied with a minimal viable product.
中文翻译:
多种癌症检测测试:我们所知道的和我们不知道的
基于血液的多癌早期检测(MCED)测试的概念引起了极大的关注,部分原因是此类测试有可能通过涵盖目前无法筛查的癌症来降低癌症死亡率。本期《CA:临床医生癌症杂志》中的一篇评论主要由美国国家癌症研究所 (NCI) 癌症预防部门的成员撰写,探讨了该领域的现状。 1作者表示不愿意将该领域称为 MCED。在他们和其他人看来,迄今为止的证据并不支持在早期阶段检测癌症方面的实质性表现。 2因此,他们使用多癌检测(MCD) 测试这一名称。作者描述了开发人员采用的 MCD 测试策略,包括首先根据跨癌症类型的共享生物标志物检测癌症信号,然后根据另一组生物标志物评估起源组织。审查包括 MCD 测试开发人员名单以及测试的性能,这些测试的数据已根据其阳性和阴性预测值公开。作者还提供了 NCI Vanguard 计划的详细信息,该计划旨在短期内测试他们在申请人中选择的 MCD 平台的性能,并从长远来看进行前瞻性随机临床研究。
尽管该审查对 MCD/MCED 领域的现状进行了评估,但仍有很多我们不知道且有待确定的事情。从有效性的角度来看,纳入的最佳癌症类型数量可能存在争议。目前,美国可以对肺癌、乳腺癌、结肠癌、宫颈癌和前列腺癌进行筛查。在发病率较高的亚洲国家,也可进行胃癌筛查。尽管 MCD 检测有可能涵盖更广泛的癌症,尤其是无法筛查的癌症,但很明显,相对少数的癌症占癌症死亡的绝大多数。美国癌症协会 2024 年癌症统计数据显示,美国癌症死亡率数据显示,五种癌症占癌症死亡人数的 50% 以上。 3对于男性,包括胰腺癌和肝胆癌;对于女性,包括胰腺癌和卵巢癌。鉴于 MCD 测试的敏感性和特异性可能因癌症类型而异,因此,如果试图普遍覆盖大量癌症类型,整体测试性能可能会下降。此外,对于推荐筛查策略的常见癌症,MCD 检测是否应该提高筛查项目的阳性预测值?对于其他恶性肿瘤,潜在的癌症生物学或治疗方法可能会消除 MCD 测试的任何益处。例如,作者指出,Pathfinder 研究(ClinicalTrials.gov 标识符 NCT04241796)中,血液系统恶性肿瘤占早期诊断的 57% ,4并且死亡率的增加不太可能来自这些癌症类型的诊断。 可能有人会说,由于 MCD 测试是基于对生物标志物的全面搜索而开发的,除了研究一组识别癌症起源组织的分子标志物之外,MCD 测试涵盖与致死率相关的生物标志物将是有益的,例如与预测相关的侵袭性和逃避免疫监视。
正如作者指出的,癌症的潜在发病率影响筛查测试的阳性预测值。如果能够通过健康特征的临床、环境、行为或社会决定因素来识别癌症风险较高的个体,那么 MCD 检测预计会更加有效。最近的一项研究将人工智能方法应用于丹麦和美国数百万人的临床数据,产生了风险概况,应用该方法后,将提高为高风险个体设计现实监测计划的能力。 5由各种暴露引起的癌症风险较高的人群将是为 MCD 的临床效用建立证据基础的另一个丰富机会。
一个关键问题仍然是在临床实践中实施 MCD 测试的性能要求。最近的一份出版物涵盖了早期检测研究网络的生物标记物开发阶段,以严格评估新型早期检测生物标记物。 6标准包括前瞻性筛查环境中足够的敏感性以及将检测转移到早期可治愈阶段,从而在临床上显着降低死亡率。后者尚未在 MCD 测试中得到证实。考虑到需要花费大量成本进行随机筛选试验,并且生存率是一个跟踪指标,需要长期随访才能确定,因此是否应该成为一项要求可能存在争议,到那时该技术可能已经很好地发展了。需要通过替代试验设计来评估临床效用的模型。 《消防员癌症登记法》指示国家职业安全与健康研究所和疾病控制与预防中心对消防员进行癌症登记,因为消防员是已知具有较高癌症风险的人群。该注册表可以充当 MCD 测试的数据库,并提供真实数据来为政策提供信息 (https://www.cdc.gov/niosh/firefighters/registry/aboutnfr.html)。
因为我们不知道 MCD 测试的临床效用,以目前的性能水平,我们也不了解这些测试应如何相对于其临床价值进行最佳定价。 Pathfinder 研究需要 473 次测试才能检测出一名患有早期癌症的人; DETECT-A 研究(通过基于选择性突变的血液采集和检测早期检测癌症)的比例为每 1239 次检测中有 1 名患者。假阳性检测的下游成本、通过早期检测获得的生命质量、通过避免对晚期疾病进行昂贵的干预措施而降低的成本以及其他经济结果措施都是未知的。
MCD 测试阴性的影响以及 MCD 测试的频率目前尚未确定。人们担心 MCD 测试呈阴性的个人可能会放弃推荐的筛查,尽管 MCD 测试不被认为是当前筛查方式的替代方法。 MCD 检测呈阳性但进一步的诊断检测未能检测出癌症的患者留下了一个令人不安的问题:MCD 检测是否为假阳性结果且不存在癌症,或者在以下情况下是否需要重复诊断检测:隐匿性癌症确实存在。此外,阴性 MCD 测试的保证可以持续多长时间?由于它只是时间快照,因此应该多久重复一次?连续测量是否有价值,其中预测能力不在于阈值测试值,而在于上升模式?这种重复测试的轨迹可能是有益的。在一项胰腺癌队列研究中,CA 19-9 水平从诊断前 2 年开始呈指数增加, 7表明建立生物标志物轨迹的潜在益处。
作者在很大程度上代表了 NCI 对测试开发的观点。然而,多个联邦机构对 MCD 具有监管兴趣,包括美国食品和药物管理局、医疗保险和医疗补助服务中心、商业保险实体、患者权益组织和职业暴露行业的工会。 MCD 测试在临床应用中的采用是关于如何培育变革性技术以实现利益最大化和如何监管以最小化风险的更广泛讨论的缩影。
MCD 测试代表了人工智能产生的新兴技术。它们通过使用基因组、蛋白质组和代谢组生物标记以及其他类型的生物标记来整合生物智能。当有关风险和收益的证据基础仍在形成时,它们在临床实践中的采用将需要情商作为与消费者共同决策的一部分。谨慎的方法是首先探索 MCD 检测对多种癌症风险增加的个体的价值,例如重度吸烟者,他们不仅患肺癌的风险增加,而且患咽喉癌、食道癌、肝癌和结直肠癌的风险也增加除其他外。需要加强覆盖政策,提供必要的下游测试和临床随访,同时寻求改善结果的证据。 MCD 测试通过早期检测癌症来拯救生命的潜力是真实的,但我们不能满足于最小可行的产品。