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This project pursued four objectives related to genetic testing: (1) assess the feasibility of clarifying a set of evaluation frameworks for common testing scenarios; (2) recommend a systematic approach to literature search for evaluating analytic validity; (3) assess the feasibility of clarifying an optimal quality rating instrument for analytic validity studies; and (4) identify existing gaps in evidence on analytic validity and recommend approaches to fill the gaps.
The main approach to meet these objectives was to organize an expert Workgroup to seek input and build consensus on key issues. These experts represented major stakeholders and were engaged through meetings and teleconferences. To facilitate the discussions among the experts, targeted reviews of pertinent literature were performed to identify current literature search strategies, quality-rating schemas, and evaluation frameworks. The project used case-studies of selected tests to focus discussion in the Workgroup meetings. The Workgroup experts served as sources of information, reviewed the preliminary findings of the targeted reviews, reached consensus on key issues, and helped to shape the report.
This study found that different stakeholders are likely to use different frameworks for evaluating genetic tests. However, the Workgroup agreed that starting from the patient's perspective made sense for most situations, with adaptations as necessary. Consequently, a set of analytic frameworks for common genetic testing scenarios (diagnosis, screening, prognosis assessment, treatment monitoring, pharmacogenetics, risk/susceptibility assessment, and testing involving germline mutations) was developed.
This study also suggested a systematic approach to literature searches for identifying analytic validity studies of genetic tests and further proposed an instrument for assessing the quality of the studies identified. The instrument is a checklist of key quality domains relevant to analytic validity studies, including internal validity, reporting quality, and other factors potentially causing bias. Significant gaps were identified in evidence on genetic testing variability. These gaps were caused by multiple factors, such as the unique technical challenges in validating genetic tests and lack of access to currently existing data.
This exploratory study revealed that it is feasible to clarify a set of evaluation frameworks, at least from patients' perspectives, and clarify an instrument for assessing analytic validity studies for evaluating genetic tests. Future effort is required to test these frameworks, validate the instrument, and fill the gaps in evidence on analytic validity for genetic testing.