학술논문

An efficient strategy for evaluating new non-invasive screening tests for colorectal cancer: the guiding principles
Document Type
Article
Source
Gut; 2023, Vol. 72 Issue: 10 p1904-1918, 15p
Subject
Language
ISSN
00175749; 14683288
Abstract
ObjectiveNew screening tests for colorectal cancer (CRC) are rapidly emerging. Conducting trials with mortality reduction as the end point supporting their adoption is challenging. We re-examined the principles underlying evaluation of new non-invasive tests in view of technological developments and identification of new biomarkers.DesignA formal consensus approach involving a multidisciplinary expert panel revised eight previously established principles.ResultsTwelve newly stated principles emerged. Effectiveness of a new test can be evaluated by comparison with a proven comparator non-invasive test. The faecal immunochemical test is now considered the appropriate comparator, while colonoscopy remains the diagnostic standard. For a new test to be able to meet differing screening goals and regulatory requirements, flexibility to adjust its positivity threshold is desirable. A rigorous and efficient four-phased approach is proposed, commencing with small studies assessing the test’s ability to discriminate between CRC and non-cancer states (phase I), followed by prospective estimation of accuracy across the continuum of neoplastic lesions in neoplasia-enriched populations (phase II). If these show promise, a provisional test positivity threshold is set before evaluation in typical screening populations. Phase IIIprospective studies determine single round intention-to-screen programme outcomes and confirm the test positivity threshold. Phase IVstudies involve evaluation over repeated screening rounds with monitoring for missed lesions. Phases III and IV findings will provide the real-world data required to model test impact on CRC mortality and incidence.ConclusionNew non-invasive tests can be efficiently evaluated by a rigorous phased comparative approach, generating data from unbiased populations that inform predictions of their health impact.