Could the Data Be Combined?
Sometimes data cannot be combined, because the studies they came from were not comparable. This is called heterogeneity, which can be tested for statistically. If present and not readily explicable, it renders any combination of the data (meta-analysis) suspect. In the paper by Smucny and colleagues, differences in the administration of the b-agonist (oral or inhaled), age group (children, adults), and previous illness (most, but not all, were free of previous wheeze or abnormal respiratory function tests) suggested that no data combinations were permissible other than for cough symptoms scores. The paper by Scholten and coworkers found heterogeneity of the results, and this was not easily explicable by any of the factors—study quality, setting, spectrum of disease, prevalence, and year of publication—included in the meta-regressions. Thus, they rightly express caution about interpreting this analysis.
What Did the Results Show? What Does This Mean for Clinical Practice?
Of the 7 trials of acceptable quality in the paper by Smucny and colleagues, neither of the 2 studies of children showed any benefit from b-agonists, but did find an increase in side effects (shakiness). Among the adult studies, 4 of 5 showed benefits for the b-agonists, but at the cost of increased shakiness or tremor in 3 of them. Looking at the size of the benefit, the standardized mean difference (this is the mean difference adjusted by the variance and is a way to combine different measurement scales, eg, measures of cough severity scaled from 0 to 4, 0 to 7, and 0 to 10) of the cough score was slightly worse for children in the b-agonist group than the control group. For adults, at least it was in the direction of benefits for those using b-agonists, but the standardized mean improvement in cough score on successive days varied between 0.05 to 0.17. This is less than the “small” attached to a standardized mean difference of 0.2, with 0.5 being “moderate” and 0.8 being “large.” Since the 95% confidence intervals for all changes cross 0, this is not clinically or statistically significant. Combining the data (Table 4 in that article) does not improve the power sufficiently to reach statistical significance. It is difficult to convert these standardized mean differences into clinically interpretable meaning, but it certainly appears that even if the changes were statistically significant, they would not be clinically significant. Therefore it seems reasonable to conclude that research to date does not support the use of b-agonists for acute cough of upper respiratory infections or acute bronchitis. Perhaps the different trends in children rather than adults were because the adults were more likely to have chronic chest disease (eg, more smokers, more had evidence of reversible airway obstruction).
Were there weaknesses of the paper? First, there was mixed use of oral (5 trials) and inhaled (2 trials) b-agonist. This might be expected to increase the rate of side effects relative to any benefits. Second, there is some suggestion that people who might have chronic chest disease, including asthma, do respond. This is not surprising.
The study by Scholten and coworkers is more complicated. The ability of clinicians to accurately detect a damaged meniscus by evaluating joint effusion, the McMurray test, joint line tenderness, and the Apley compression test is disappointingly poor (Table 2 of that article). These results have been combined where possible and are best understood using Figure 2. Imagine a patient coming in with a knee injury. Based on the history and before doing the McMurray test, you estimate the chance of this patient having meniscus damage is 50%. Reading up from 50% of the “prior probability” of meniscus damage on the x-axis, if the McMurray test result is positive, the probability moves only to 70% (read off the y-axis); if negative, it drops only to 35%. In this situation, none of these tests will satisfactorily rule-in or rule-out the chance of meniscus lesions.
It must be remembered that these studies were all conducted in specialist clinics. This might have 2 effects: (1) the physicians there may be better at interpreting the clinical examination (being more specialized); and (2) there are more patients with meniscus damage. To get a feel for this, imagine you are a family physician with a person with a sore knee. The chance there is meniscus damage might be only 10%; a positive McMurray test result will increase that probability to 27%, while a negative result will decrease it to 3%. A positive result is not very useful, but a negative one might support a decision to delay further testing and take a more conservative approach to the evaluation, since the likelihood of meniscal lesion is so small.