12.2.2  Factors that decrease the quality level of a body of evidence

We now describe in more detail the five reasons for downgrading the quality of a body of evidence for a specific outcome (Table 12.2.b).  In each case, if a reason is found for downgrading the evidence, it should be classified as ‘serious’ (downgrading the quality rating by one level) or ‘very serious’ (downgrading the quality grade by two levels).

 

1.   Limitations in the design and implementation: Our confidence in an estimate of effect decreases if studies suffer from major limitations that are likely to result in a biased assessment of the intervention effect. For randomized trials, these methodological limitations include lack of allocation concealment, lack of blinding (particularly with subjective outcomes highly susceptible to biased assessment), a large loss to follow-up, randomized trials stopped early for benefit or selective reporting of outcomes.  Chapter 8 provides a detailed discussion of study-level assessments of risk of bias in the context of a Cochrane review, and proposes an approach to assessing the risk of bias for an outcome across studies as ‘low risk of bias’, ‘unclear risk of bias’ and ‘high risk of bias’ (Chapter 8, Section 8.7).  These assessments should feed directly into this factor. In particular, ‘low risk of bias’ would indicate ‘no limitation’; ‘unclear risk of bias’ would indicate either ‘no limitation’ or ‘serious limitation’; and ‘high risk of bias’ would indicate either ‘serious limitation’ or ‘very serious limitation’. Authors must use their judgement to decide between alternative categories, depending on the likely magnitude of the potential biases.

Every study addressing a particular outcome will differ, to some degree, in the risk of bias.  Review authors must make an overall judgement on whether the quality of evidence for an outcome warrants downgrading on the basis of study limitations. The assessment of study limitations should apply to the studies contributing to the results in the ‘Summary of findings’ table, rather than to all studies that could potentially be included in the analysis. We have argued in Chapter 8 (Section 8.8.3) that the primary analysis should be restricted to studies at low (or low and unclear) risk of bias.

Table 12.2.d presents the judgements that must be made in going from assessments of the risk of bias to judgements about study limitations for each outcome included in a ‘Summary of findings’ table. A rating of high quality evidence can be achieved only when most evidence comes from studies that met the criteria for low risk of bias. For example, of the 22 trials addressing the impact of beta blockers on mortality in patients with heart failure, most probably or certainly used concealed allocation, all blinded at least some key groups and follow-up of randomized patients was almost complete (Brophy 2001). The quality of evidence might be downgraded by one level when most of the evidence comes from individual studies either with a crucial limitation for one criterion, or with some limitations for multiple criteria. For example, we cannot be confident that, in patients with falciparum malaria, amodiaquine and sulfadoxine-pyrimethamine together reduce treatment failures compared with sulfadoxine-pyrimethamine, because the apparent advantage of sulfadoxine-pyrimethamine was sensitive to assumptions regarding the event rate in those lost to follow-up (>20% loss to follow up in two of three studies) (McIntosh 2005). An example of very serious limitations, warranting downgrading by two levels, is provided by evidence on surgery versus conservative treatment in the management of patients with lumbar disc prolapse (Gibson 2007).  We are uncertain of the benefit of surgery in reducing symptoms after one year or longer, because the one trial included in the analysis had inadequate concealment of allocation and the outcome was assessed using a crude rating by the surgeon without blinding.

2.       Indirectness of evidence.  Two types of indirectness are relevant. First, a review comparing the effectiveness of alternative interventions (say A and B) may find that randomized trials are available, but they have compared A with placebo and B with placebo.  Thus, the evidence is restricted to indirect comparisons between A and B.  
Second, a review may find randomized trials that meet eligibility criteria but which address a restricted version of the main review question in terms of population, intervention, comparator or outcomes. For example, suppose that in a review addressing an intervention for secondary prevention of coronary heart disease, the majority of identified studies happened to be in people who also had diabetes. Then the evidence may be regarded as indirect in relation to the broader question of interest because the population is restricted to people with diabetes. The opposite scenario can equally apply: a review addressing the effect of a preventative strategy for coronary heart disease in people with diabetes may consider trials in people without diabetes to provide relevant, albeit indirect, evidence.  This would be particularly likely if investigators had conducted few if any randomized trials in the target population (e.g. people with diabetes). Other sources of indirectness may arise from interventions studied (e.g. if in all included studies a technical intervention was implemented by expert, highly trained specialists in specialist centres, then evidence on the effects of the intervention outside these centres may be indirect), comparators used (e.g. if the control groups received an intervention that is less effective than standard treatment in most settings) and outcomes assessed (e.g. indirectness due to surrogate outcomes when data on patient-important outcomes are not available, or when investigators sought data on quality of life but only symptoms were reported).  Review authors should make judgements transparent when they believe downgrading is justified based on differences in anticipated effects in the group of primary interest.

3.   Unexplained heterogeneity or inconsistency of results: When studies yield widely differing estimates of effect (heterogeneity or variability in results), investigators should look for robust explanations for that heterogeneity. For instance, drugs may have larger relative effects in sicker populations or when given in larger doses. A detailed discussion of heterogeneity and its investigation is provided in Chapter 9 (Sections 9.5 and 9.6). If an important modifier exists, with strong evidence that important outcomes are different in different subgroups (which would ideally be pre-specified), then a separate ‘Summary of findings’ table may be considered for a separate population. For instance, a separate ‘Summary of findings’ table would be used for carotid endarterectomy in symptomatic patients with high grade stenosis in which the intervention is, in the hands of the right surgeons, beneficial (Cina 2000), and another (if they considered it worth it) for asymptomatic patients with moderate grade stenosis in which surgery is not beneficial (Chambers 2005).  When heterogeneity exists and affects the interpretation of results, but authors fail to identify a plausible explanation, the quality of evidence decreases.

4.       Imprecision of results: When studies include few participants and few events and thus have wide confidence intervals, authors can lower their rating of the quality of the evidence.  The confidence intervals included in the ‘Summary of findings’ table will provide readers with information that allows them to make, to some extent, their own rating of precision. 

5.   High probability of publication bias: The quality of evidence level may be downgraded if investigators fail to report studies (typically those that show no effect: publication bias) or outcomes (typically those that may be harmful or for which no effect was observed: selective outcome reporting bias) on the basis of results.  Selective reporting of outcomes is assessed at the study level as part of the assessment of risk of bias (see Chapter 8, Section 8.14), so for the studies contributing to the outcome in the ‘Summary of findings’ table this is addressed by factor 1 above (limitations in the design and implementation). If a large number of studies included in the review do not contribute to an outcome, or if there is evidence of publication bias, the quality of the evidence may be downgraded. Chapter 10 provides a detailed discussion of reporting biases, including publication bias, and how it may be tackled in a Cochrane review.  A prototypical situation that may elicit suspicion of publication bias is when published evidence includes a number of small trials, all of which are industry funded (Bhandari 2004).  For example, 14 trials of flavanoids in patients with haemorrhoids have shown apparent large benefits, but enrolled a total of only 1432 patients (that is, each trial enrolled relatively few patients) (Alonso-Coello 2006).  The heavy involvement of sponsors in most of these trials raises questions of whether unpublished trials suggesting no benefit exist.  

 

A particular body of evidence can suffer from problems associated with more than one of the five factors above, and the greater the problems, the lower the quality of evidence rating that should result.  One could imagine a situation in which randomized trials were available, but all or virtually all of these limitations would be present, and in serious form.  A very low quality of evidence rating would result.