Molecular diagnostics clinical utility strategy: a six-part framework

Abstract

The clinical utility of a molecular test rises proportional to a favorable regulatory risk/benefit assessment, and clinical utility is the driver of payer coverage decisions. Although a great deal has been written about clinical utility, debates still center on its ‘definition.’ We argue that the definition (an impact on clinical outcomes) is self-evident, and improved communications should focus on sequential steps in building and proving an adequate level of confidence for the diagnostic test’s clinical value proposition. We propose a six-part framework to facilitate communications between test developers and health technology evaluators, relevant to both regulatory and payer decisions.

Keywords::

• clinical utility
• combination diagnostics
• guidelines
• health technology assessment
• molecular diagnostics
• payers
• regulatory approval

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

Key issues

• The boom in molecular biology is coming to fruition with a rapid increase in the potential number of biomarkers and clinical molecular diagnostics relevant to medical practice.

• Technology developers become highly frustrated when communications about the value (or lack of value) of new diagnostic modalities reach an impasse, with high but poorly articulated levels of disagreement between developers and evaluators.

• Current frameworks, such as reference to levels-of-evidence hierarchies or to the simple triad of ‘analytical validity, clinical validity, clinical utility,’ do not provide adequate guidance to developers nor are they providing a clear framework for evaluators.

• We emphasize the logical connection between improved test performance (clinical validity) and improved outcomes (clinical utility). The development and presentation of test benefits should focus clearly on the comparative advances in both validity and utility, and how the former drives the latter.

• Some types of improved test performance, such as superior prognostic value, are abstract and the conventional statistical metrics (such as p-value, r-value, area under the curve) do not help visualize the tangible benefits of the improved test. When the gain in clinical validity is not tangibly understood, the causal impact between the test’s information to the patient’s improved clinical utility is likely to be unconvincing.

• A six-part framework is proposed, relevant to both combination diagnostics and to new molecular tests not directly linked to a single drug or therapy. The same six questions can also be applied to imaging tests, such as β-amyloid scans for dementia diagnosis.