Generating and evaluating evidence of the clinical utility of molecular diagnostic tests in oncology

Abstract

Purpose: Enthusiasm for molecular diagnostic (MDx) testing in oncology is constrained by the gaps in required evidence regarding its impact on patient outcomes (clinical utility (CU)). This effectiveness guidance document proposes recommendations for the design and evaluation of studies intended to reflect the evidence expectations of payers, while also reflecting information needs of patients and clinicians.Methods: Our process included literature reviews and key informant interviews followed by iterative virtual and in-person consultation with an expert technical working group and an advisory group comprising life-sciences industry experts, public and private payers, patients, clinicians, regulators, researchers, and other stakeholders.Results: Treatment decisions in oncology represent high-risk clinical decision making, and therefore the recommendations give preference to randomized controlled trials (RCTs) for demonstrating CU.The guidance also describes circumstances under which alternatives to RCTs could be considered, specifying conditions under which test developers could use prospective-retrospective studies with banked biospecimens, single-arm studies, prospective observational studies, or decision-analytic modeling techniques that make a reasonable case for CU. Conclusion:Using a process driven by multiple stakeholders, we developed a common framework for designing and evaluating studies of the clinical validity and CU of MDx tests, achieving a balance between internal validity of the studies and the relevance, feasibility, and timeliness of generating the desired evidence.

Impact of Biomarker-based Design Strategies on the Risk of False-Positive Findings in Targeted Therapy Evaluation

“…Other concerns could be raised over the fact that CVASD includes biomarker-negative patients, which might be unethical in practice. In fact, the question of whether we need to include or not biomarker-negative patients in targeted therapy evaluation is a complex and debated question (24,25). This depends on the confidence in the absence of effect in the biomarker-negative patients based on biological rationale, knowledge of the drug's mechanism, preclinical data, the seriousness of the disease treated (i.e., delaying approval for biomarker-positive patients is often considered as not acceptable), etc.…”

Payer decision making for next-generation sequencing–based genetic tests: insights from cell-free DNA prenatal screening

“…The only evidence regarding health outcomes associated with cfDNA screening in either high risk or average risk pregnancies was developed from decision analytic models, suggesting that in certain circumstances, a well-conducted model can influence payer decision-making. 27 Whether decision analytic models are sufficient evidence of clinical utility in other complex genetic tests is undetermined. 27,28 …”

“…27 Whether decision analytic models are sufficient evidence of clinical utility in other complex genetic tests is undetermined. 27,28 …”

Clinical Integration of Next Generation Sequencing: Coverage and Reimbursement Challenges

“…There remain many unanswered questions among governmental and private payers as what constitutes an appropriate level of evidence to demonstrate clinical utility for clinical applications where NGS is likely to be used. 115 …”