title: Best (but oft-forgotten) practices: sensitivity analyses in randomized controlled trials.
abstract: A randomized controlled clinical trial is the best way to minimize bias in ascertaining treatment effects, but the credibility of the results of a trial depends on the validity of the methods used to analyze the data, and the conditions under which such methods produce valid answers. A sensitivity analysis is a method to determine the robustness of trial findings by examining the extent to which results are affected by changes in methods, models, values of unmeasured variables, or assumptions. The goal of a sensitivity analysis is to identify results that are most dependent on questionable or unsupported assumptions. In this article, we briefly review the current use of sensitivity analyses in a random sample of published nutrition literature and provide a guide on the use of sensitivity analyses in randomized trials as to when to consider them, what to consider when planning them, and different methods of implementing them. We propose an 8-step strategy for improving the approach to conducting and reporting sensitivity analyses in nutrition-based trials.
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences, Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada;
authors.forename: Russell J
authors.initials: RJ
authors.lastname: de Souza
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences.
authors.forename: Rebecca B
authors.initials: RB
authors.lastname: Eisen
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences.
authors.forename: Stefan
authors.initials: S
authors.lastname: Perera
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences.
authors.forename: Bianca
authors.initials: B
authors.lastname: Bantoto
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences.
authors.forename: Monica
authors.initials: M
authors.lastname: Bawor
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences.
authors.forename: Brittany B
authors.initials: BB
authors.lastname: Dennis
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences, Department of Psychiatry and Behavioral Neurosciences, St. Joseph's Healthcare Hamilton and Hamilton Health Sciences Mood Disorders Program, Hamilton, Canada.
authors.forename: Zainab
authors.initials: Z
authors.lastname: Samaan
authors.affiliation: Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences, Center for Evaluation of Medicine, Population Health Research Institute, Hamilton Health Sciences, and System-Linked Research Unit, McMaster University, Hamilton, Canada; and thabanl@mcmaster.ca.
authors.forename: Lehana
authors.initials: L
authors.lastname: Thabane
mesh_terms: D015982:Bias; D006801:Humans; D052756:Nutritional Sciences; D016032:Randomized Controlled Trials as Topic; D012107:Research Design
keywords: analysis; commentary; sensitivity; statistics; tutorial