Elizabeth Colantuoni1, Ximin Li2, Mohamed D Hashem3, Timothy D Girard4, Daniel O Scharfstein5, Dale M Needham6. 1. Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA; Outcomes After Critical Illness and Surgery (OACIS) Group, Johns Hopkins University, Baltimore, Maryland, USA. Electronic address: ejohnso2@jhmi.edu. 2. Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. 3. Department of Medicine, Marshfield Clinic, Marshfield, Wisconsin, USA. 4. Clinical Research, Investigation, and Systems Modeling of Acute illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA. 5. Division of Biostatistics, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA. 6. Outcomes After Critical Illness and Surgery (OACIS) Group, Johns Hopkins University, Baltimore, Maryland, USA; Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Abstract
OBJECTIVE: This structured methodology review evaluated statistical approaches used in randomized controlled trials (RCTs) enrolling patients at high risk of death and makes recommendations for reporting future RCTs. STUDY DESIGN AND SETTING: Using PubMed, we searched for RCTs published in five general medicine journals from January 2014 to August 2019 wherein mortality was ≥10% in at least one randomized group. We abstracted primary and secondary outcomes, statistical analysis methods, and patient samples evaluated (all randomized patients vs. "survivors only"). RESULTS: Of 1947 RCTs identified, 434 met eligibility criteria. Of the eligible RCTs, 91 (21%) and 351 (81%) had a primary or secondary functional outcome, respectively, of which 36 (40%) and 263 (75%) evaluated treatment effects among "survivors only". In RCTs that analyzed all randomized patients, the most common methods included use of ordinal outcomes (e.g., modified Rankin Scale) or creating composite outcomes (primary: 41 of 91 [45%]; secondary: 57 of 351 [16%]). CONCLUSION: In RCTs enrolling patients at high risk of death, statistical analyses of functional outcomes are frequently conducted among "survivors only," for which conclusions might be misleading. Given the growing number of RCTs conducted among patients hospitalized with COVID-19 and other critical illnesses, standards for reporting should be created.
OBJECTIVE: This structured methodology review evaluated statistical approaches used in randomized controlled trials (RCTs) enrolling patients at high risk of death and makes recommendations for reporting future RCTs. STUDY DESIGN AND SETTING: Using PubMed, we searched for RCTs published in five general medicine journals from January 2014 to August 2019 wherein mortality was ≥10% in at least one randomized group. We abstracted primary and secondary outcomes, statistical analysis methods, and patient samples evaluated (all randomized patients vs. "survivors only"). RESULTS: Of 1947 RCTs identified, 434 met eligibility criteria. Of the eligible RCTs, 91 (21%) and 351 (81%) had a primary or secondary functional outcome, respectively, of which 36 (40%) and 263 (75%) evaluated treatment effects among "survivors only". In RCTs that analyzed all randomized patients, the most common methods included use of ordinal outcomes (e.g., modified Rankin Scale) or creating composite outcomes (primary: 41 of 91 [45%]; secondary: 57 of 351 [16%]). CONCLUSION: In RCTs enrolling patients at high risk of death, statistical analyses of functional outcomes are frequently conducted among "survivors only," for which conclusions might be misleading. Given the growing number of RCTs conducted among patients hospitalized with COVID-19 and other critical illnesses, standards for reporting should be created.
Authors: Safiya Richardson; Jamie S Hirsch; Mangala Narasimhan; James M Crawford; Thomas McGinn; Karina W Davidson; Douglas P Barnaby; Lance B Becker; John D Chelico; Stuart L Cohen; Jennifer Cookingham; Kevin Coppa; Michael A Diefenbach; Andrew J Dominello; Joan Duer-Hefele; Louise Falzon; Jordan Gitlin; Negin Hajizadeh; Tiffany G Harvin; David A Hirschwerk; Eun Ji Kim; Zachary M Kozel; Lyndonna M Marrast; Jazmin N Mogavero; Gabrielle A Osorio; Michael Qiu; Theodoros P Zanos Journal: JAMA Date: 2020-05-26 Impact factor: 56.272
Authors: Alison E Turnbull; Anahita Rabiee; Wesley E Davis; Mohamed Farhan Nasser; Venkat Reddy Venna; Rohini Lolitha; Ramona O Hopkins; O Joseph Bienvenu; Karen A Robinson; Dale M Needham Journal: Crit Care Med Date: 2016-07 Impact factor: 7.598