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Selecting appropriate endpoints for assessing treatment effects in comparative clinical studies for COVID-19.
McCaw, Zachary R; Tian, Lu; Sheth, Kevin N; Hsu, Wan-Ting; Kimberly, W Taylor; Wei, Lee-Jen.
  • McCaw ZR; Google, Mountain View, CA, United States of America.
  • Tian L; Department of Biomedical Data Science, Stanford University, Stanford, CA, United States of America.
  • Sheth KN; Division of Neurocritical Care and Emergency Neurology, Yale School of Medicine, New Haven, CT, United States of America.
  • Hsu WT; Medical Wizdom, LLC, Brookline, MA, United States of America.
  • Kimberly WT; Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States of America.
  • Wei LJ; Harvard T.H. Chan School of Public Health, Boston, MA, United States of America. Electronic address: wei@hsph.harvard.edu.
Contemp Clin Trials ; 97: 106145, 2020 10.
Article in English | MEDLINE | ID: covidwho-753827
ABSTRACT
To evaluate the efficacy and safety of a new treatment for COVID-19 vs. standard care, certain key endpoints are related to the duration of a specific event, such as hospitalization, ICU stay, or receipt of supplemental oxygen. However, since patients may die in the hospital during study follow-up, using, for example, the duration of hospitalization to assess treatment efficacy can be misleading. If the treatment tends to prolong patients' survival compared with standard care, patients in the new treatment group may spend more time in hospital. This can lead to a "survival bias" issue, where a treatment that is effective for preventing death appears to prolong an undesirable outcome. On the other hand, by using hospital-free survival time as the endpoint, we can circumvent the survival bias issue. In this article, we use reconstructed data from a recent, large clinical trial for COVID-19 to illustrate the advantages of this approach. For the analysis of ICU stay or oxygen usage, where the initiating event is potentially an outcome of treatment, standard survival analysis techniques may not be appropriate. We also discuss issues with analyzing the durations of such events.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Patient Care Management / Survival Analysis / Clinical Trials as Topic / Duration of Therapy / COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Systematic review/Meta Analysis Limits: Humans Language: English Journal: Contemp Clin Trials Journal subject: Medicine / Therapeutics Year: 2020 Document Type: Article Affiliation country: J.cct.2020.106145

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Patient Care Management / Survival Analysis / Clinical Trials as Topic / Duration of Therapy / COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Systematic review/Meta Analysis Limits: Humans Language: English Journal: Contemp Clin Trials Journal subject: Medicine / Therapeutics Year: 2020 Document Type: Article Affiliation country: J.cct.2020.106145