Multicancer Early Detection Technologies: A Review Informed by Past Cancer Screening Studies

Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling

BACKGROUND

Downstaging-reduction in late-stage incidence-has been proposed as an endpoint in randomized trials of multi-cancer early detection (MCED) tests. How downstaging depends on test performance and follow-up has been studied for some cancers but is understudied for cancers without existing screening and for MCED tests that include these cancer types.

METHODS

We develop a model for cancer natural history that can be fit to registry incidence patterns under minimal inputs and can be estimated for solid cancers without existing screening. Fitted models are combined to project downstaging in MCED trials given sensitivity for early- and late-stage cancers. We fit models for 12 cancers using incidence data from the Surveillance, Epidemiology, and End Results program and project downstaging in a simulated trial under variable preclinical latencies and test sensitivities.

RESULTS

A proof-of-principle lung cancer model approximated downstaging in the National Lung Screening Trial. Given published stage-specific sensitivities for 12 cancers, we projected downstaging ranging from 21% to 43% across plausible preclinical latencies in a hypothetical 3-screen MCED trial. Late-stage incidence reductions manifest soon after screening begins. Downstaging increases with longer early-stage latency or higher early-stage test sensitivity.

CONCLUSIONS

Even short-term MCED trials could produce substantial downstaging given adequate early-stage test sensitivity.

IMPACT

Modeling the natural histories of cancers without existing screening facilitates analysis of novel MCED products and trial designs. The framework informs expectations of MCED impact on disease stage at diagnosis and could serve as a building block for designing trials with late-stage incidence as the primary endpoint.

Circulating tumor DNA (ctDNA): can it be used as a pan-cancer early detection test?

Circulating tumor DNA (ctDNA, DNA shed by cancer cells) is emerging as one of the most transformative cancer biomarkers discovered to-date. Although potentially useful at all the phases of cancer detection and patient management, one of its most exciting possibilities is as a relatively noninvasive pan-cancer screening test. Preliminary findings with ctDNA tests such as Galleri or CancerSEEK suggest that they have high specificity (> 99.0%) for malignancy. Their sensitivity varies depending on the type of cancer and stage of disease but it is generally low in patients with stage I disease. A major advantage of ctDNA over existing screening strategies is the potential ability to detect multiple cancer types in a single test. A limitation of most studies published to-date is that they are predominantly case-control investigations that were carried out in patients with a previous diagnosis of malignancy and that used apparently healthy subjects as controls. Consequently, the reported sensitivities, specificities and positive predictive values might be lower if the tests are used for screening in asymptomatic populations, that is, in the population where these tests are likely be employed. To demonstrate clinical utility in an asymptomatic population, these tests must be shown to reduce cancer mortality without causing excessive overdiagnosis in a large randomized prospective randomized trial. Such trials are currently ongoing for Galleri and CancerSEEK.

Strong association between reduction of late-stage cancers and reduction of cancer-specific mortality in meta-regression of randomized screening trials across multiple cancer types

BACKGROUND

Late-stage cancer incidence has been proposed as an early surrogate for mortality in randomized controlled trials (RCTs) of cancer screening; however, its validity has not been systematically evaluated across screening RCTs of different cancers.

METHODS

We conducted a meta-regression analysis of cancer screening RCTs that reported both late-stage cancer incidence and cancer mortality. Based on a systematic literature review, we included 33 RCTs of screening programs targeting seven cancer types, including lung (n = 12), colorectal (n = 8), breast (n = 5), and prostate (n = 4), among others. We regressed the relative reduction of cancer mortality on the relative reduction of late-stage cancer incidence, inversely weighted for each RCT by the variance of estimated mortality reduction.

RESULTS

Across cancer types, the relative reduction of late-stage cancer incidence was linearly associated with the relative reduction of cancer mortality. Specifically, we observed this association for lung (R2 = 0.79 and 0.996 in three recent large trials), breast (R2 = 0.94), prostate (R2 = 0.98), and colorectal cancer (R2 = 0.75 for stage III/IV cancers and 0.93 for stage IV cancers). Trials with a 20% or greater reduction in late-stage cancers were more likely to achieve a significant reduction in cancer mortality. Our results also showed that no reduction of late-stage cancer incidence was associated with no or minimal reduction in cancer mortality.

CONCLUSIONS

Meta-regression of historical screening RCTs showed a strong linear association between reductions in late-stage cancer incidence and cancer mortality.

Benefits and Harms of Interception and Early Detection of Cancer

Strategies for early detection and interception of cancer are based on 2 synergistic elements: proactive search for asymptomatic cancer, precancer, or cancer predisposition and proactive disruption of cancer evolution. Benefits and harms of both these elements will vary widely depending on the screened populations, the types of cancers targeted, the detection modalities, and the health care delivery approaches following diagnosis. This article attempts to identify common elements that can inform the evaluation of alternative strategies across many of these scenarios.

Revisiting the standard blueprint for biomarker development to address emerging cancer early detection technologies

Novel liquid biopsy technologies are creating a watershed moment in cancer early detection. Evidence supporting population screening is nascent, but a rush to market the new tests is prompting cancer early detection researchers to revisit the standard blueprint that the Early Detection Research Network established to evaluate novel screening biomarkers. In this commentary, we review the Early Detection Research Network's Phases of Biomarker Development (PBD) for rigorous evaluation of novel early detection biomarkers and discuss both hazards and opportunities involved in expedited evaluation. According to the PBD, for a biomarker-based test to be considered for population screening, 1) test sensitivity in a prospective screening setting must be adequate, 2) the shift to early curable stages must be meaningful, and 3) any stage shift must translate into clinically significant mortality benefit. In the past, determining mortality benefit has required lengthy randomized screening trials, but interest is growing in expedited trial designs with shorter-term endpoints. Whether and how best to use such endpoints in a manner that retains the rigor of the PBD remains to be determined. We discuss how computational disease modeling can be harnessed to learn about screening impact and meet the needs of the moment.

Pancreatic Cancer Health Disparity: Pharmacologic Anthropology

Pancreatic cancer (PCa) remains a formidable global health challenge, with high mortality rates and limited treatment options. While advancements in pharmacology have led to improved outcomes for various cancers, PCa continues to exhibit significant health disparities, disproportionately affecting certain populations. This paper explores the intersection of pharmacology and anthropology in understanding the health disparities associated with PCa. By considering the socio-cultural, economic, and behavioral factors that influence the development, diagnosis, treatment, and outcomes of PCa, pharmacologic anthropology provides a comprehensive framework to address these disparities and improve patient care.

Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.