What is clinical utility?
Clinical utility defines the likelihood of the test’s results to inform and support clinical decisions that improve patient outcomes, which is reflected by the definition in the dictionary of the National Cancer Institute (NCI): “A term that refers to the likelihood that a test will, by prompting an intervention, result in an improved health outcome” . Clinical utility depends on many factors, including the intended use of the test, the patient group, and the existing standard of care (SOC). However, there is no consensus on an exact definition of clinical utility, and it can include different aspects depending on various stakeholder perspectives. The laboratory, the physician, the payer, and the patient may all consider different endpoints important for the assessment of clinical utility. Besides clinical outcomes, clinical utility endpoints can cover clinical decision making, clinical workflow, and costs. In fact, a more expanded definition of clinical utility can include emotional, social, cognitive, and behavioral endpoints, which can all have a direct impact on the patient’s wellbeing. For example, tests can have clinical utility in the absence of an effective clinical treatment by providing clarity and helping patients and their families cope with the associated prognosis .
Why does clinical utility matter?
Clinical utility describes the impacts of a test towards improved health outcomes, helping stakeholders with the decision on test implementation. Clinical utility is required by the Centers for Medicare and Medicaid services (CMS) and other payers for coverage and reimbursement decisions.
The concept of clinical utility is therefore a key component in frameworks evaluating the value and efficacy of diagnostic tests. In 1992, Fryback and Thornbury proposed a hierarchical model (known as “FT model”) that included efficacies covering the concept of analytical and clinical validity, and clinical utility . The FT model was initially proposed to determine the efficacy of diagnostic imaging, but its foundation has since been applied to cover diagnostic tests more broadly .
The analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications (ACCE) project , established and supported by the Centers for Disease Control and Prevention (CDC) from 2000 to 2004, defines clinical utility with the tests impact on patient outcome improvements and value added to the clinical decision-making process . The ACCE model separates clinical utility and the assessment of the ethical, legal, and social implications (ELSI), while others propose a more expansive concept of clinical utility (2,4). The ACCE model is widely applied, and CMS has instructed the MolDX program to apply the ACCE criteria towards technical passements of MDx . The MolDX program, which is administered by Palmetto GBA, identifies, and establishes coverage and reimbursement for MDx.
The Association for Molecular Pathology (AMP) proposes a definition of clinical utility based on a modified ACCE model. AMP supports patient-centered definitions of clinical utility that focuses on the ability of test results to “diagnose, monitor, prognosticate, or predict disease progression, and to inform treatment and reproductive decisions”. Although the report focuses on inherited conditions and cancer, the recommendation can be extended to other applicable areas of molecular testing .
A workgroup supported by the American Society for Microbiology (ASM) recently published their views on “Clinical Utility of Advanced Microbiology Testing Tools” . The group outlines considerations and concepts for the development of clinical utility. Diagnostic tests must show improved efficiency in one or more of the following four categories: clinical decision making, streamlined clinical workflow, better patient outcomes, and cost offsets or avoidance.
In 2019, the Medical Device Innovation Consortium (MDIC) published the framework “Developing Clinical Evidence for Regulatory and Coverage Assessments in In Vitro Diagnostics (IVDs)” to provide insights on establishing analytical and clinical validity, and clinical utility . The publication assesses the evidence needed to show clinical utility for covered tests from a payer’s perspective. A self-assessment framework to help IVD developers determine the clinical utility and market viability of their tests is included, followed by an overview of applicable study concepts.
How does clinical utility relate to analytical and clinical validity?
Analytic validity focuses on the technical efficacy and determines how accurately and reliably the test quantitative or qualitative detects the targeted analyte(s). Evidence demonstrating analytical validity can include repeatability and reproducibility (precision), analytical accuracy, specificity, and sensitivity. Clinical validity confirms that a test is clinically meaningful by determining how accurately and reliable the test predicts the patient’s clinical status. Clinical validity can be expressed by determining clinical sensitivity, clinical specificity, predictive values, and likelihood ratios.
Clinical utility is directly connected to the analytical and clinical validity of a test. A test that does not have the required analytical performance may show suboptimal clinical validity as the test may report false positive or false negative outcomes. This in turn could impact the diagnosis and treatment decision, greatly interfering with patient’s health outcome and therefore clinical utility.
To ensure the safety and efficacy of these tests, validating acceptable performance is crucial. Analytical validity is required by the United States Food and Drug Administration (FDA) for in vitro diagnostics tests (IVDs) and covered under the Clinical Laboratory Improvement Amendments (CLIA) for laboratory-developed tests (LDTs). While the FDA does require clinical validity, it is not specifically addressed under CLIA . Clinical utility is required by the Centers for Medicare and Medicaid services (CMS) and other payers for coverage and reimbursement decisions and impacts provider adoption.
Clinical utility and cost-benefits
The FT model includes cost–benefit and cost-effectiveness as its own hierarchy under “societal efficacy” , while the ACCE model incorporates the economic aspect directly into clinical utility . The MDIC framework on the other hand differentiates between clinical and economic utility but acknowledges that new tests with increased costs may require significant improvements to be viable on the market . A cost-benefit evaluation can help with adoption. Newer molecular diagnostics (MDx) may have a higher cost of testing, which in return could be offset by more efficient use of downstream resources .
As we gain a better understanding of the human body and underlaying causes of diseases, new technologies and tests are being developed. Analytical validity, clinical validity and clinical utility will remain key characteristics to evaluate the performance and value of diagnostic tests. Given the multidimensional concept of clinical utility, key stakeholders must work closely together to align endpoints needed to demonstrate and communicate the benefits of new technologies for individual and communal health.
Learn more about the clinical value of molecular testing.