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The increasing use of statistical modelling and lower certainty evidence to expand screening and the aggressive marketing of multicancer early detection tests raises questions about evidence thresholds for updating existing screening recommendations.
Since 2018, five of the updated cancer screening recommendations of the US Preventive Services Task Force (USPSTF) have included statistical models (breast, colorectal, lung, cervical and prostate). All five have recommended more intensive screening than the earlier recommendation, either by recommending newer screening technologies or expanding the population eligible for screening. For example, the 2021 colorectal cancer screening recommendation lowered the starting age from 50 to 45 years based on a microsimulation model of hypothetical patient panels.1 2 The models for updating recommendations for all of these cancers relied heavily on either intermediate outcomes or performance characteristics of the screening test. Several blood-based cancer screening tests for multiple cancers are being developed and promoted without randomised controlled trials with health outcomes.3 Soon, evidence-based organisations will be faced with proposals for further intensification of screening using these new technologies.
Recommendations of new screening strategies from evidence-based organisations such as the USPSTF, the Canadian Task Force on Preventive Health Care (CTFPHC) and the International Agency for Research on Cancer (IARC) are based on several factors, but especially evaluation of complex bodies of research, using methods that specify a high threshold for evidence of sufficient certainty to estimate net benefit (the balance between desirable and undesirable effects in the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision framework).4 This high evidence threshold often includes the requirement for randomised controlled trials (RCTs) and/or consistent evidence from several high-quality studies with alternative designs to reach the degree of certainty of outcome effects to allow recommendation panels to assess net benefit before making a recommendation that incorporates patient …
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X @AHuffstetler, @kennylinafp
Contributors RPH is a former member of the US Preventive Services Task Force and has coauthored several papers describing its methods. KWL is a former medical officer for the US Preventive Services Task Force programme at the US Agency for Healthcare Research and Quality and coauthored systematic reviews to support previous recommendation updates. RPH conceived the article. AH completed the first draft of the article. All authors participated in revising subsequent drafts. KWL is the guarantor.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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