title: [GRADE guidelines: 8. Rating the quality of evidence - indirectness].
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). Second, 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. Third, 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, which is 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 by 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 against some other comparator.
authors.affiliation: Wissenschaftliches Institut der AOK (WIdO), Berlin. andrej.rasch@wido.bv.aok.de
authors.forename: Andrej
authors.initials: A
authors.lastname: Rasch
authors.forename: Matthias
authors.initials: M
authors.lastname: Perleth
authors.forename: Gero
authors.initials: G
authors.lastname: Langer
authors.forename: Joerg J
authors.initials: JJ
authors.lastname: Meerpohl
authors.forename: Gerald
authors.initials: G
authors.lastname: Gartlehner
authors.forename: Angela
authors.initials: A
authors.lastname: Kaminski-Hartenthaler
authors.forename: Holger J
authors.initials: HJ
authors.lastname: Schünemann
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D015987:Effect Modifier, Epidemiologic; D023381:Endpoint Determination / Q000592:standards* / Q000706:statistics & numerical data*; D019317:Evidence-Based Medicine / Q000592:standards* / Q000706:statistics & numerical data*; D005858:Germany; D006801:Humans; D017410:Practice Guidelines as Topic / Q000592:standards*; D011785:Quality Assurance, Health Care / Q000592:standards* / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic / Q000592:standards / Q000706:statistics & numerical data; D012106:Research / Q000592:standards / Q000706:statistics & numerical data; D012196:Review Literature as Topic; D016896:Treatment Outcome