BACKGROUND: The completion of the Human Genome Project has increased the pace of discovery of genetic markers for disease. Despite tremendous efforts in fundamental research, clinical applications still lag behind expectations, partly due to the lack of effective tools to systematically search for and summarize published data relative to the clinical assessment of new diagnostic molecular tests. METHODS: Through a collaborative process using published tools and an expert panel, we developed a detailed checklist of the evidence that needs to be collected or produced to evaluate the potential usefulness of a new molecular diagnostic test. This tool is called GETT, for Genetic testing Evidence Tracking Tool. RESULTS: GETT allows 1) researchers to summarize the current evidence and to identify knowledge gaps for further research and; 2) stakeholders to collect data related to a given molecular test and improve their decision-making process. GETT comprises 72 clearly defined items/questions, grouped into 10 categories and 26 sub-themes, including an overview of disease epidemiology and genetics, the available diagnostic tools, and their analytical and clinical performances, availability of quality control programs, laboratory and clinical best practice guidelines, clinical utility, and impact on health care and psycho-social, ethical and legal implications. It also includes a summary of the evidence available and attempts to prioritise knowledge gaps related to the testing. We also compare GETT to other existing frameworks. CONCLUSIONS: This systematic evidence-based tracking tool, which is more detailed than existing frameworks and provides clear definition for each item, will help streamline collection of the available evidence to appraise the potential for clinical application of new molecular diagnostic tests and prioritize research to produce the evidence-base relative to the clinical implementation of molecular diagnostic tests.
BACKGROUND: The completion of the Human Genome Project has increased the pace of discovery of genetic markers for disease. Despite tremendous efforts in fundamental research, clinical applications still lag behind expectations, partly due to the lack of effective tools to systematically search for and summarize published data relative to the clinical assessment of new diagnostic molecular tests. METHODS: Through a collaborative process using published tools and an expert panel, we developed a detailed checklist of the evidence that needs to be collected or produced to evaluate the potential usefulness of a new molecular diagnostic test. This tool is called GETT, for Genetic testing Evidence Tracking Tool. RESULTS: GETT allows 1) researchers to summarize the current evidence and to identify knowledge gaps for further research and; 2) stakeholders to collect data related to a given molecular test and improve their decision-making process. GETT comprises 72 clearly defined items/questions, grouped into 10 categories and 26 sub-themes, including an overview of disease epidemiology and genetics, the available diagnostic tools, and their analytical and clinical performances, availability of quality control programs, laboratory and clinical best practice guidelines, clinical utility, and impact on health care and psycho-social, ethical and legal implications. It also includes a summary of the evidence available and attempts to prioritise knowledge gaps related to the testing. We also compare GETT to other existing frameworks. CONCLUSIONS: This systematic evidence-based tracking tool, which is more detailed than existing frameworks and provides clear definition for each item, will help streamline collection of the available evidence to appraise the potential for clinical application of new molecular diagnostic tests and prioritize research to produce the evidence-base relative to the clinical implementation of molecular diagnostic tests.
Authors: Fiona M Walter; Matthew J Thompson; Ian Wellwood; Gary A Abel; William Hamilton; Margaret Johnson; Georgios Lyratzopoulos; Michael P Messenger; Richard D Neal; Greg Rubin; Hardeep Singh; Anne Spencer; Stephen Sutton; Peter Vedsted; Jon D Emery Journal: BMC Cancer Date: 2019-06-14 Impact factor: 4.430
Authors: Jennifer S Lin; Matthew Thompson; Katrina A B Goddard; Margaret A Piper; Carl Heneghan; Evelyn P Whitlock Journal: BMC Med Inform Decis Mak Date: 2012-10-19 Impact factor: 2.796
Authors: Ilda Hoxhaj; Laurenz Govaerts; Steven Simoens; Walter Van Dyck; Isabelle Huys; Iñaki Gutiérrez-Ibarluzea; Stefania Boccia Journal: Int J Environ Res Public Health Date: 2020-10-30 Impact factor: 3.390