Real-world data and evidence in pain research: a qualitative systematic review of methods in current practice
Jan Vollert,
Bethea A. Kleykamp,
John T. Farrar,
Ian Gilron,
David Hohenschurz-Schmidt,
Robert D. Kerns,
Sean Mackey,
John D. Markman,
Michael P. McDermott,
Andrew S.C. Rice,
Dennis C. Turk,
Ajay D. Wasan,
Robert H. Dworkin
Affiliations
Jan Vollert
a Pain Research, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
Bethea A. Kleykamp
e BAK and Associates, LLC, Baltimore, MD, USA
John T. Farrar
f Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
Ian Gilron
g Departments of Anesthesiology & Perioperative Medicine, Biomedical & Molecular, Sciences, Centre for Neuroscience Studies, and School of Policy Studies, Queen's University and Kingston Health Sciences Centre, Kingston, ON, Canada
David Hohenschurz-Schmidt
a Pain Research, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
Robert D. Kerns
h Departments of Psychiatry, Neurology and Psychology, Yale University, New Haven, CT, USA
Sean Mackey
i Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
John D. Markman
j Department of Neurosurgery, University of Rochester, Rochester, NY, USA
Michael P. McDermott
k Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA
Andrew S.C. Rice
a Pain Research, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
Dennis C. Turk
l Chair of Anesthesiology & Pain Research, UW Medicine, Department of Anesthesiology & Pain Medicine, University of Washington, WA, USA
Ajay D. Wasan
m Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
Robert H. Dworkin
n Departments of Anesthesiology and Perioperative Medicine, Neurology, and Psychiatry, University of Rochester, Rochester, NY, USA
Abstract. The use of routinely collected health data (real-world data, RWD) to generate real-world evidence (RWE) for research purposes is a growing field. Computerized search methods, large electronic databases, and the development of novel statistical methods allow for valid analysis of data outside its primary clinical purpose. Here, we systematically reviewed the methodology used for RWE studies in pain research. We searched 3 databases (PubMed, EMBASE, and Web of Science) for studies using retrospective data sources comparing multiple groups or treatments. The protocol was registered under the DOI:10.17605/OSF.IO/KGVRM. A total of 65 studies were included. Of those, only 4 compared pharmacological interventions, whereas 49 investigated differences in surgical procedures, with the remaining studying alternative or psychological interventions or epidemiological factors. Most 39 studies reported significant results in their primary comparison, and an additional 12 reported comparable effectiveness. Fifty-eight studies used propensity scores to account for group differences, 38 of them using 1:1 case:control matching. Only 17 of 65 studies provided sensitivity analyses to show robustness of their findings, and only 4 studies provided links to publicly accessible protocols. RWE is a relevant construct that can provide evidence complementary to randomized controlled trials (RCTs), especially in scenarios where RCTs are difficult to conduct. The high proportion of studies reporting significant differences between groups or comparable effectiveness could imply a relevant degree of publication bias. RWD provides a potentially important resource to expand high-quality evidence beyond clinical trials, but rigorous quality standards need to be set to maximize the validity of RWE studies.
