Real-world data (RWD) potentially could be used to supplement data from clinical screening studies to support regulatory decision making for multi-cancer early detection (MCED) screening tests, according to a new white paper from the Friends of Cancer Research.
MCED tests are an emerging technology that uses a sample of blood, also called a liquid biopsy, to detect cancer-associated signals in the early stages. One of the challenges for MCED tests is gathering sufficient safety and efficacy data for regulatory approval. With currently approved single-cancer screening tests, validation data have come primarily from prospective and observational studies, with some long-term survival data coming from prospective randomized controlled trials (RCTs) and epidemiological studies in the postmarketing setting. However, there are logistical hurdles to generating evidence of clinical validating and utility for MCED screening tests, which may include rare cancer types.
The white paper explores the endpoints that could be captured by RWD and offers possible ways to use RWD study designs to support generation of MCED screening test safety and effectiveness. It was discussed at a webinar held by the organization on 29 March.
“Within the context of current study designs, [real-world evidence] is likely to serve a supplementary role and be part of the totality of evidence in an initial premarket application. However, as our understanding of these novel tests evolves and the robustness of RWD is better understood, the use of RWD may expand,” the FOCR working group wrote.
NCI, FDA consider MCEDs
The National Cancer Institute (NCI) also is looking at ways to study and evaluate MCED tests, according to NCI Director Ned Sharpless, who spoke at the FOCR webinar. NCI is currently designing clinical trials of MCED tests, as well as other research opportunities, and recently issued a request for information from test developers on their readiness to participate in research initiatives.
“We think these are exciting technologies and could really have an important impact on cancer detection and cancer outcomes at the population level, if applied robustly,” Sharpless said. “But we also have concerns that MCEDs could lead to overdiagnosis and overtreatment, if they were applied incorrectly.”
He added that many questions remain on the regulatory pathways for MCED tests. The US Food and Drug Administration (FDA) also has been considering the evidence necessary to approve MCED tests and the potential for RWD to be part of that evaluation. In March 2020, the agency held a public workshop exploring the key assessment questions needed to evaluate performance characteristics, safety, and clinical outcomes related to MCED tests.
RWD could help to supplement data from clinical studies of MCEDs in an initial approval for high incidence cancers, as well as provide post-marketing data that could assist in the assessment of safety and efficacy for additional indications, according to Wendy Rubinstein of FDA’s Center for Devices and Radiological Health.
“That is an approach that the [FOCR] effort can help us support, to expand this set of indications for authorized tests over time and also maintain authorization where the initial evidence was not as strong,” Rubinstein said during the FOCR webinar.
She noted that few health care systems have invested enough in their IT system to produce fit-for-purpose RWD that could be used for regulatory purposes, but data aggregators have been tackling data interoperability and addressing data relevance and reliability. “We can plan ahead to support harmonized data collection and standards, develop common methodological frameworks, align on key variable definitions to leverage RWD that comes through usual care,” Rubinstein said. “It’s really not too early to plan for the use of RWD in regulatory decision making for MCEDs.”
Potential endpoints
The FOCR working group defined potential endpoints to assess the clinical validity (the ability to accurately identify cancer) and the clinical utility (the likelihood that patients managed based on the test results will have improved outcomes) of MCED tests. They did not address the analytical validity of the tests.
Cancer “stage shift” might be used as a surrogate for the impact of the MCED test on disease mortality, according to the white paper. “There is a concern that increasing the proportion of early-stage cancers may lead to overdiagnosis without any effect on late-stage detection; therefore, a decrease in incidence of late-stage disease is more informative to support an understanding of the likely implications of stage shift,” the working group wrote.
Long-term endpoints include disease-specific mortality, all-cause mortality, and five-year cancer-specific survival, and overall survival. The working group noted that assessing clinical utility by cancer type, as well as by all cancer, will be important.
RWD study designs
RWD evidence can help further define the specific cancer characteristics to aid in assessing MCED tests, including incidence, natural history, and the existence of recommended standard of care screening. For example, RWD may be useful in understanding the benefit-risk profile of MCED tests for cancers with low incidence. RWD allows for an analysis of the performance of MCED screening tests among tens to hundreds of thousands of patients that would be difficult to achieve with traditional clinical screening studies. Conversely, RWD can be used for high-prevalence cancers that would require large number of patients to sufficiently power an analysis.
Additionally, RWD can help to mitigate issues with registrational clinical trials, which do not always reflect real-world medical practices, Girish Putcha of biotech company Freenome said during the webinar. “Adherence to screening can be quite different in the real world, and as many have shown, this can have a very significant impact on the clinical utility of such tests.”
For experimental study designs, such as controlled trials, RWD can be used to determine patient eligibility and outcomes, or by linking RWD to a study cohort. In observational studies, RWD can be used as an external control arm, or as part of a case-control or cohort study. For example, when using RWD as an external control arm, the RWD group would reflect the intended use population but without use of the MCED screening test. This would potentially reduce the cohort size needed to show clinical validating and utility. However, a non-randomized control could introduce bias into the detection rate comparison, according to the white paper.
