Year: 2020
Type: article
Abstract: Interpreting randomized clinical trials (RCTs) is crucial to making decisions regarding the use of analgesic treatments in clinical practice. In this article, we report on an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) consensus meeting organized by the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks, the purpose of which was to recommend approaches that facilitate interpretation of analgesic RCTs. We review issues to consider when drawing conclusions from RCTs, as well as common methods for reporting RCT results and the limitations of each method. These issues include the type of trial, study design, statistical analysis methods, magnitude of the estimated beneficial and harmful effects and associated precision, availability of alternative treatments and their benefit-risk profile, clinical importance of the change from baseline both within and between groups, presentation of the outcome data, and the limitations of the approaches used.
Source: Pain
Authors: Shannon M. Smith, Robert H. Dworkin, Dennis C. Turk, Michael P. McDermott, Christopher Eccleston, John T. Farrar, Michael C. Rowbotham, Zubin Bhagwagar, Laurie B. Burke, Penney Cowan, Susan S. Ellenberg, Scott R. Evans, Roy L. Freeman, Louis P. Garrison, Smriti Iyengar, Alejandro Jadad, Mark P. Jensen, Roderick Junor, Cornelia Kamp, Nathaniel P. Katz, James Patrick Kesslak, Ernest A. Kopecky, Dmitri Lissin, John D. Markman, Philip J. Mease, Alec B. O'Connor, Kushang V. Patel, Srinivasa N. Raja, Cristina Sampaio, David Schoenfeld, Jasvinder Singh, Ilona Steigerwald, Vibeke Strand, Leslie A. Tive, Jeffrey Tobias, Ajay D. Wasan, Hilary D. Wilson
Institutions: University of Rochester Medicine, University of Rochester, University of Washington, University of Bath, University of Pennsylvania, Sutter Health, California Pacific Medical Center, Yale University, University of Maryland, Baltimore, American Chronic Pain Association, George Washington University, Harvard University, Eli Lilly (United States), University of Toronto, Eisai (United Kingdom), Tufts University, Revance (United States), Collegium Pharmaceutical (United States), Scilex Pharmaceuticals, Inc. (United States), Swedish Medical Center, Johns Hopkins University, Johns Hopkins Medicine, University of Lisbon, CHDI Foundation, University of Alabama at Birmingham, UAB Medicine, Stanford University, Pfizer (United States), University of Pittsburgh
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Funders: Amgen, Eli Lilly and Company, Pfizer, AstraZeneca, GlaxoSmithKline, Biogen, Alexion Pharmaceuticals, Alnylam Pharmaceuticals, Celgene, Depomed, Washington State University, University of Washington, Novartis Pharmaceuticals Corporation, New York State Stem Cell Science, PTC Therapeutics, ACADIA Pharmaceuticals, aTyr, Voyager Therapeutics, Multiple Sclerosis Society, Astellas Pharma, National Institutes of Health, U.S. Food and Drug Administration, Administration for Community Living, Allergan, National Institute on Aging, National Institute of Allergy and Infectious Diseases, Daiichi Sankyo Europe
Award: G2263150704
OpenAlex ID: W3033940508