This article describes a genomic test assessment framework for evaluating, interpreting, and reporting genomic data. The framework contains 5 components, the first of which requires that the medical disorder be specified, along with the test(s) used for detecting the disorder and the clinical setting in which testing is to be offered. Then, 4 aspects of test performance are examined: Analytic validity, Clinical validity, Clinical utility, and Ethical, legal, and social issues (abbreviated as ACCE). Each section contains specific questions that can be applied to a wide variety of genomic screening and diagnostic tests, including those that might be used for estimating risks for future health disorders. Assessing such tests systematically is especially important at present, because definitive studies are often unavailable to determine whether knowledge of specified genotypes will be more effective in improving health than knowledge gained from existing practice. Often, for example, a genotype that is shown to be a valid risk factor for a common problem such as heart disease will mistakenly be considered to have clinical utility when converted into a screening test. Understanding the performance characteristics of a genomic test is of special concern when it is advocated for widespread application, such as population-based screening, because of the potential for generating false expectations and wasting resources that might be better invested elsewhere. Although initially designed to provide policymakers with up-to-date and reliable information for decision making, the ACCE framework is user-friendly to individual health professionals, who can apply the questions to any test being promoted in their field to assess clinical validity and utility. Subsequent to preliminary applications in a feasibility study, aspects of this assessment framework have been incorporated into the methods of the Evaluation of Genomic Applications in Practice and Prevention Working Group, established by the Office of Public Health Genomics at the Centers for Disease Control and Prevention. The Evaluation of Genomic Applications in Practice and Prevention Working Group issues recommendations about the suitability of new genetic tests for use in everyday practice, based on commissioned evidence reviews, and serves as an added resource to health professionals
Genetic tests have their strengths, but some have problems
James E. Haddow, MD, is a research professor in the Department of Pathology and Laboratory Medicine at the Alpert Medical School of Brown University. His interest in assessing screening and diagnostic tests began in the late 1970s, in conjunction with developing and introducing a statewide prenatal screening program for spina bifida and Down syndrome. That interest subsequently expanded to include genomic tests and led to development of the Analytic validity, Clinical validity, Clinical utility, and Ethical, legal, and social issues (ACCE) process (along with Glenn E. Palomaki). As a member of the Evaluation of Genetic Applications in Practice and Prevention (EGAPP) Working Group, sponsored by the Centers for Disease Control and Prevention, Dr Haddow participates in developing recommendations for appropriate use of genomic tests.
Glenn E. Palomaki, PhD, is an associate professor in the Department of Pathology and Laboratory Medicine at the Alpert Medical School of Brown University. In the 1990s, his expertise (as a biostatistician) in analyzing prenatal screening test performance resulted in his being appointed to the College of American Pathologists Resource Committee, which is responsible for laboratory proficiency testing throughout the United States. More recently, he developed the ACCE process (along with James E. Haddow) and has taken a lead role in applying that process to a variety of genomic tests, as a consultant to the EGAPP Working Group.
Disclosure: The authors have no funding or conflicts of interest to disclose.
Correspondence: James E. Haddow, MD, Women & Infants Hospital/Alpert Medical School of Brown University, 2nd Floor, 70 Elm St, Providence, RI 02903 (email@example.com).