The Changing Face of Clinical Trials: Evidence for Health Decision Making — Beyond Randomized, Controlled Trials

New England Journal of Medicine
http://www.nejm.org/toc/nejm/medical-journal
 August 3, 2017  Vol. 377 No. 5

Review Article
The Changing Face of Clinical Trials: Evidence for Health Decision Making — Beyond Randomized, Controlled Trials
T.R. Frieden
[Concluding text]
Moving Forward — Overcoming the “Dark Matter” of Clinical Medicine
For much, and perhaps most, of modern medical practice, RCT-based data are lacking and no RCT is being planned or is likely to be completed to provide evidence for action. This “dark matter” of clinical medicine leaves practitioners with large information gaps for most conditions and increases reliance on past practices and clinical lore.4,69,70 Elevating RCTs at the expense of other potentially highly valuable sources of data is counterproductive. A better approach is to clarify the health outcome being sought and determine whether existing data are available that can be rigorously and objectively evaluated, independently of or in comparison with data from RCTs, or whether new studies (RCT or otherwise) are needed.

New ways of obtaining valuable health data continue to emerge. “Big data,” including information from electronic health records and expanded patient registries, along with increased willingness of patients to participate and share health information, are generating useful data for large interventional studies and providing new opportunities for complementary use of multiple data sources to gain stronger evidence for action.71 For example, although an RCT may show the benefit of a drug, large observational studies can be conducted to refine dosages and identify rare adverse events. In addition, new strategies have been undertaken to increase the efficacy and efficiency of RCTs, including collaborative and adaptive trials to increase enrollment, reduce costs and time to completion, and better identify populations that benefit from treatments.72-74 Advances in genomic science may allow for better understanding of unique characteristics in patients that can affect outcomes of RCTs and other studies and be used to improve the validity of study findings.

There is no single, best approach to the study of health interventions; clinical and public health decisions are almost always made with imperfect data (Table 1Table 1Selected Strengths and Weaknesses of Various Study Designs, along with Examples of Studies with Effects on Policy or Practice.). Promoting transparency in study methods, ensuring standardized data collection for key outcomes, and using new approaches to improve data synthesis are critical steps in the interpretation of findings and in the identification of data for action, and it must be recognized that conclusions may change over time. There will always be an argument for more research and for better data, but waiting for more data is often an implicit decision not to act or to act on the basis of past practice rather than best available evidence. The goal must be actionable data — data that are sufficient for clinical and public health action that have been derived openly and objectively and that enable us to say, “Here’s what we recommend and why.”