Defining optimal research study design for cardiovascular imaging using computed tomography angiography as a model.
Patients, physicians, and payers are facing a significant increase in cardiovascular (CV) imaging use, resulting in skyrocketing societal costs, without clear improvement in patient outcomes. The need for studies evaluating the effects of CV imaging that assess appropriate end points is critical to address continued concerns over the lack of well-designed clinical studies. Thus, the investigators propose a framework, using computed tomographic angiography as a model, that should be considered in the optimal design of future imaging research and would potentially provide payers with data to make appropriate reimbursement decisions. The inclusion of risk stratification, randomization, multiple-site participation, and multigeography site enrollment are key elements in the construction of such studies. Meaningful end points with regard to operating characteristics, downstream testing, CV event rates, outcomes, and costs are essential to appropriately evaluate any new imaging technology. Only once better level evidence is formed to support CV imaging can the central issues of quality and appropriateness of CV imaging truly be evaluated. If the CV community does not embrace this type of scientific evaluation of CV imaging modalities and fails to adequately identify the value in these techniques, it may ultimately lose the ability to use them to provide optimal care to its patients.
Shah
Bimal R
BR
Duke Clinical Research Institute and Division of Cardiovascular Medicine, Duke University Medical Center, Durham, North Carolina, USA. bimal.shah@duke.edu
Patel
Manesh R
MR
Peterson
Eric D
ED
Douglas
Pamela S
PS
D002318:Cardiovascular Diseases / Q000000981:diagnostic imaging*; D017023:Coronary Angiography; D006801:Humans; D018579:Patient Selection; D012107:Research Design; D014057:Tomography, X-Ray Computed