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GRADE guidelines: 8. Rating the quality of evidence - Indirectness

  • Gordon H. Guyatt
  • , Andrew D. Oxman
  • , Regina Kunz
  • , James Woodcock
  • , Jan Brozek
  • , Mark Helfand
  • , Pablo Alonso-Coello
  • , Yngve Falck-Ytter
  • , Roman Jaeschke
  • , Gunn Vist
  • , Elie A. Akl
  • , Piet N. Post
  • , Susan Norris
  • , Joerg Meerpohl
  • , Vijay K. Shukla
  • , Mona Nasser
  • , Holger J. Schünemann
  • McMaster University
  • Norwegian Institute of Public Health
  • University of Basel
  • London School of Hygiene and Tropical Medicine
  • Oregon Health and Science University
  • Autonomous University of Barcelona
  • Case Western Reserve University
  • University of Oxford
  • SUNY Buffalo
  • Dutch Institute for Healthcare Improvement CBO
  • University of Freiburg
  • Canadian Agency for Drugs and Technologies in Health
  • Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen

Research output: Contribution to journalArticlepeer-review

1550 Scopus citations

Abstract

Direct evidence comes from research that directly compares the interventions in which we are interested when applied to the populations in which we are interested and measures outcomes important to patients. Evidence can be indirect in one of four ways. First, patients may differ from those of interest (the term applicability is often used for this form of indirectness). Secondly, the intervention tested may differ from the intervention of interest. Decisions regarding indirectness of patients and interventions depend on an understanding of whether biological or social factors are sufficiently different that one might expect substantial differences in the magnitude of effect. Thirdly, outcomes may differ from those of primary interest - for instance, surrogate outcomes that are not themselves important, but measured in the presumption that changes in the surrogate reflect changes in an outcome important to patients. A fourth type of indirectness, conceptually different from the first three, occurs when clinicians must choose between interventions that have not been tested in head-to-head comparisons. Making comparisons between treatments under these circumstances requires specific statistical methods and will be rated down in quality one or two levels depending on the extent of differences between the patient populations, co-interventions, measurements of the outcome, and the methods of the trials of the candidate interventions.

Original languageEnglish
Pages (from-to)1303-1310
Number of pages8
JournalJournal of Clinical Epidemiology
Volume64
Issue number12
DOIs
StatePublished - Dec 2011

Keywords

  • Applicability
  • GRADE
  • Generalizability
  • Indirect comparisons
  • Indirectness
  • Quality of evidence

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