Closing the Gap Between Observational Research and Randomized Controlled Trials for Prevention of Alzheimer Disease and Dementia

Abstract

Although observational studies have identified modifiable risk factors for Alzheimer’s disease and related dementias (ADRD), randomized controlled trials (RCTs) of risk factor modification for ADRD prevention have been inconsistent or inconclusive. This suggests a need to improve translation between observational studies and RCTs. However, many common features of observational studies reduce their relevance to designing related RCTs. Observational studies routinely differ from RCTs with respect to eligibility criteria, study population, length of follow-up, treatment conditions, outcomes, and effect estimates. Using the motivating example of blood pressure reduction for ADRD prevention, we illustrate the need for a tighter connection between observational studies and RCTs, discuss barriers to using typically-reported observational evidence in developing RCTs, and highlight methods that may be used to make observational research more relevant to clinical trial design. We conclude that the questions asked and answered by observational research can be made more relevant to clinical trial design, and that better use of observational data may increase the likelihood of successful, or at least definitive, trials. While we focus on improving translation of observational studies on risk factors for ADRD to RCTs in ADRD prevention, the overarching themes are broadly applicable to many areas of biomedical research.

Optimising the use of electronic medical records for large scale research in psychiatry

“…Some argue that this delivers evidence lacking generalisability to patients and their presentations in routine clinical care and excludes those patients whose risk formulation excludes them from clinical trials. Therefore, evidence derived from EMR-based research has the potential to complement evidence from controlled trials, especially when considering health equity and reproducibility [5][6][7]. Furthermore, causal inference methods are being introduced to address some of the biases in observational research using EMR data.…”

Representativeness of Participants in the ACCORD Trial Compared to Middle-aged and Older Adults Living with Diabetes in the United States

“…T rial participants are typically highly selected, with large differences between participants and the target populations for whom the trials guide clinical care. [1][2][3] This is a rationale for using observational data for emulating trials, 4 but it is unknown how profound these differences are in specific clinical trials.…”