Evaluating genomic tests from bench to bedside: a practical framework

BMC Medical Informatics and Decision Making

Correspondence

Margaret A Piper¹  Katrina AB Goddard²  Evelyn P Whitlock²  Jennifer S Lin²  Matthew Thompson³  Carl Heneghan⁴ 

[1] Blue Cross and Blue Shield Association Technology Evaluation Center, 60601, Chicago, IL, USA;Center for Health Research, Kaiser Permanente Northwest, 3800 N. Interstate Ave, 97227, Portland, OR, USA;Center for Health Research, Kaiser Permanente Northwest, 3800 N. Interstate Ave, 97227, Portland, OR, USA;Department of Primary Care Health Sciences, University of Oxford, OX1 2ET, Oxford, UK;Department of Primary Care Health Sciences, University of Oxford, OX1 2ET, Oxford, UK;

关键词: Genetic/genomic;    Test development;    Diagnostic test;    Prognostic test;    Evaluation framework;    Evidence-based decision making;   

DOI  :  10.1186/1472-6947-12-117

 received in 2012-04-13, accepted in 2012-10-15,  发布年份 2012

来源: Springer

【 摘 要 】

The development of genomic tests is one of the most significant technological advances in medical testing in recent decades. As these tests become increasingly available, so does the need for a pragmatic framework to evaluate the evidence base and evidence gaps in order to facilitate informed decision-making. In this article we describe such a framework that can provide a common language and benchmarks for different stakeholders of genomic testing. Each stakeholder can use this framework to specify their respective thresholds for decision-making, depending on their perspective and particular needs. This framework is applicable across a broad range of test applications and can be helpful in the application and communication of a regulatory science for genomic testing. Our framework builds upon existing work and incorporates principles familiar to researchers involved in medical testing (both diagnostic and prognostic) generally, as well as those involved in genomic testing. This framework is organized around six phases in the development of genomic tests beginning with marker identification and ending with population impact, and highlights the important knowledge gaps that need to be filled in establishing the clinical relevance of a test. Our framework focuses on the clinical appropriateness of the four main dimensions of test research questions (population/setting, intervention/index test, comparators/reference test, and outcomes) rather than prescribing a hierarchy of study designs that should be used to address each phase.

【 授权许可】

CC BY   
© Lin et al.; licensee BioMed Central Ltd. 2012