Artigo

Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients

Beverly Shea, Gordon Guyatt, Pablo Perel, Per Olav Vandvik, Paul Glasziou, Holger Schunemann, Alfonso Iorio, Frederick A Spencer, Carolina Alba, Bernard Burnand, Jill Hayden, MAICON FALAVIGNA, Eddie Lang, Tom McGinn, Katrina Williams

British Medical Journal, v. 350, n. 0, p. 870-0, 2015.

Motivo: Produção Colaborador HMV

Setor HMV: Iep Unidade Pesquisa Em Saude

Área da saúde: Epidemiologia

Resumo: Summary points Main concepts The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach defines quality of evidence as confidence in effect estimates; this conceptualization can readily be applied to bodies of evidence estimating the risk of future of events (that is, prognosis) in broadly defined populations In the field of prognosis, a body of observational evidence (including single arms of randomized controlled trials) begins as high quality evidence The five domains GRADE considers in rating down confidence in estimates of treatment effect—that is, risk of bias, imprecision, inconsistency, indirectness, and publication bias—as well as the GRADE criteria for rating up quality, also apply to estimates of the risk of future of events from a body of prognostic studies Applying these concepts to systematic reviews of prognostic studies provides a useful approach to determine confidence in estimates of overall prognosis in broad populations Lay summary The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to rating confidence in the results of research studies was initially developed for therapeutic questions The GRADE approach considers study design (randomized trials versus non-randomized designs), risk of bias, inconsistency, imprecision, indirectness, and publication bias; size and trend in the effect are also considered Observational studies looking at patients’ prognosis may provide robust estimates of the likelihood of undesirable or desirable outcomes in both treated and untreated patients Patients will often find this information helpful in understanding the likely course of their disease, in planning their future, and in engaging in shared decision making with their healthcare providers In a previous article, we examined factors that affect confidence in estimates of baseline risk (the risk of bad outcomes in untreated patients), providing examples of how this might influence the confidence in estimates of absolute treatment effect This paper provides guidance for the use of the GRADE approach to determine confidence in estimates of future events in systematic reviews of prognostic studies in broad categories of patients

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