Clinical Trials

❘❙❚■ Chapter 37 | Critical Appraisal of a ReportFor example, one patient might have many adverse events during a study. The finalstatistical results for the study can then be based on a count of all the events, thepatient’s first event, or the worst event the patient suffered. The latter is importantbecause some outcomes, eg, death, are more important than others, eg, an increasein the dose/number of medicines used to control symptoms. If all events are beingmeasured, care must be taken to understand this, otherwise it can lead to amisunderstanding that generally the trial had high rates of adverse events.When reviewing the results, it is important to ensure there are no hiddendetrimental effects or other outcomes that might outweigh the benefits of theintervention under investigation. For example, authors often present the rates ofdeath and then a combined rate of death or myocardial infarction (MI). If there isa 2% decrease in the death rate for the new treatment but only a 1% decrease forthe combined endpoint, then it is important to consider the fact that there weremore MIs with the new treatment. This is not necessarily at odds with the newtreatment being beneficial, since if substantially fewer patients die then the patientsliving longer might have an increase in nonfatal complications, such as MI.More commonly the situation is reversed in studies, with disease-specificoutcomes being improved, but with (albeit nonsignificant) mortality rates forpatients in the new treatment arm increasing. In meta-analyses combining theresults of many such trials, two outcomes (such as death and relief of symptoms)can go in opposite directions, making the value of such therapies doubtful. It isalso important that side-effects and their frequencies are presented – such asbleeding, weight gain, or drug interactions. These measures can easily sabotagean otherwise beneficial treatment.Another way to tip results in favor of a new therapy is to only present the resultsfrom patients who were fully compliant with the new treatment protocol (perprotocol analysis). However, excluding information from patients withdrawingfrom the study, perhaps because of side-effects, can favor the therapy that is morelikely to cause side-effects. This is because the remaining patients are oftenyounger and healthier, and they are able to continue taking medications despitemild side-effects, unlike more elderly patients or those with coexisting illnesses.If the new therapy caused more side-effects, then in a per protocol-based analysisthat group might have a somewhat healthier profile and hence less adverseoutcomes from the disease process. The ideal report would include all patients inthe analysis after they are randomized, regardless of what happens later (intentionto-treatanalysis) – such as not being prescribed the treatment, being switched tothe other treatment group, or only being partially compliant with the treatment.434