| Literature DB >> 28320705 |
M Hassan Murad1, Reem A Mustafa2,3, Holger J Schünemann3, Shahnaz Sultan4, Nancy Santesso3.
Abstract
When studies measure or report outcomes differently, it may not be feasible to pool data across studies to generate a single effect estimate (ie, perform meta-analysis). Instead, only a narrative summary of the effect across different studies might be available. Regardless of whether a single pooled effect estimate is generated or whether data are summarised narratively, decision makers need to know the certainty in the evidence in order to make informed decisions. In this guide, we illustrate how to apply the constructs of the GRADE (Grading of Recommendation, Assessment, Development and Evaluation) approach to assess the certainty in evidence when a meta-analysis has not been performed and data were summarised narratively. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.Entities:
Keywords: EPIDEMIOLOGY; STATISTICS & RESEARCH METHODS
Mesh:
Year: 2017 PMID: 28320705 PMCID: PMC5502230 DOI: 10.1136/ebmed-2017-110668
Source DB: PubMed Journal: Evid Based Med ISSN: 1356-5524
Applying the GRADE approach when evidence for an effect is summarised narratively (a meta-analysis is not available)
| GRADE domain | How to apply the GRADE domain to evidence that has been summarised narratively |
|---|---|
| Methodological limitations of the studies | Make a judgement on the risk of bias across studies for an individual outcome. A sensitivity analysis is not possible to determine if the effect changes when studies at high risk of bias are excluded. It is possible to consider the size of a study, its risk of bias and the impact it would have on the summarised effect. |
| Indirectness | Make a global judgement on how dissimilar the research evidence is to the clinical question at hand (in terms of population, interventions and outcomes across studies). |
| Imprecision | Consider the optimal information size (or the total number of events for binary outcomes and the number of participants in continuous outcomes) across all studies. A threshold of 400 or less is concerning for imprecision. |
| Inconsistency | Judge inconsistency by evaluating the consistency of the direction and primarily the difference in the magnitude of effects across studies (since statistical measures of heterogeneity are not available). Widely differing estimates of the effects indicate inconsistency. |
| Likelihood of publication bias | Publication bias can be suspected when the body of evidence consists of only small positive studies or when studies are reported in trial registries but not published. Statistical evaluation of publication bias is not possible in this case. Publication bias is more likely if the search of the systematic review is not comprehensive. |
| Factors that can raise certainty in evidence:
Large effect Dose–response gradient Plausible confounders or other biases increase the certainty in the effect | If one of the three domains that can increase certainty in a body of evidence (typically from non-randomised studies) is noted, consider rating up the grade of certainty, particularly if it is noted in the majority of studies. |
Illustrative example of rating the certainty in evidence in the absence of a single estimate of effect
| GRADE domain | Judgement | Concerns about certainty domains |
|---|---|---|
| Methodological limitations of the studies | One out of five trials | Serious |
| Indirectness | The patients, intervention and comparators in the studies all provide direct evidence to the clinical question at hand. All interventions included an educational component (with some variation in the direct respiratory therapy component). The type and severity of the symptoms (outcome) was assessed using different scales in different trials. We judged the evidence to have no serious indirectness but noted some variability in the intervention and outcome measure. | Not serious |
| Imprecision | The total number of patients included in all the trials was ∼600. Some trials reported small reductions, and other trials reported ‘non-significant results’ likely because of enrolling a small number of participants which resulted in wide CIs that included meaningful benefits and no effects. We judged the evidence to have borderline imprecision. | Not serious, borderline |
| Inconsistency | The direction and magnitude of effect varied across the different trials. Overall the results showed either small reduction in symptoms or no change. Two trials, | Serious |
| Publication bias | We did not strongly suspect publication bias because both negative and positive trials were published, and the search for studies was comprehensive. | Not suspected |
The outcome of interest is respiratory symptoms. Data are derived from a systematic review of self-management programmes in patients with chronic obstructive pulmonary disease.
Illustrative example of how the summary of findings can be presented to guideline developers
| Outcome | Effect | Number of participants | Certainty in the evidence* |
|---|---|---|---|
| Respiratory symptoms | Most studies showed small reductions in symptoms or no effect. | 623 | LOW†‡ |
The outcome of interest is respiratory symptoms (for which a single pooled effect estimate was not available and only a narrative synthesis of the evidence was provided).
*Commonly used symbols to describe certainty in evidence in evidence profiles: high certainty ⊕⊕⊕⊕, moderate certainty ⊕⊕⊕O, low certainty ⊕⊕OO and very low certainty ⊕OOO.
†Serious risk of bias across studies because of unclear or inadequate blinding, sequence generation and allocation concealment.
‡Serious imprecision and inconsistency were considered together as there were small effects, or ‘no effects’ reported in studies (likely due to wide CIs).