Clinical Trials

❘❙❚■ Chapter 26 | Confoundingfor a potential confounder in the analysis and find that the adjusted andunadjusted estimates of the treatment effect differ, this suggests that theunadjusted estimate is confounded by the factor under consideration. In the HRTexample, the unadjusted odds ratio was 1.66, but this became 1.00 afterstratification by socioeconomic status, suggesting that socioeconomic statusis a positive confounder.Positive and negative confoundingPositive confounding is said to occur when the effect of a confounder is to makethe observed treatment effect appear stronger (ie, to move the odds ratio furtheraway from 1 when the confounder is unaccounted for) [1], as in the HRT example.Confounding can also work in the opposite direction – known as negativeconfounding – where it can result in the treatment effect appearing to be weakerthan it really is after adjusting for the confounder [1].Controlling confounding through study designThe effect of confounding can be prevented at different stages in a clinical trial,but the most effective method is to restrict it at the design stage. In general,randomization – a cornerstone of clinical trials – is the most effective way ofpreventing confounding. The purpose of randomization is to ensure that eachsubject has an equal chance of being assigned to each treatment group, andthat the treatment assignment cannot be predicted in advance [4,5]. Ideally,randomization should result in the balanced distribution of all potentialconfounders, whether known or unknown, across all treatment groups at baseline.For a large trial, a simple randomization scheme should achieve this. However, insmaller trials it is possible for an imbalance in one or more baseline characteristicsto occur, which could result in confounding, even if this imbalance might not besufficient to reach statistical significance. Therefore, attention should be paid toidentifying potential confounders – which can be adjusted for at the analysis stageif necessary – especially when the sample size of a clinical trial is small.When designing clinical trials, if we know from previous studies that somecharacteristics are important prognostic factors, we can limit their potential forconfounding by means of a stratified randomization method [4,5]. Stratifiedrandomization is used to ensure a reasonable balance between treatment groupsof one or more potential confounding factors, such as age, gender, presence ofdiabetes, severity of illness, geographical location, and socioeconomic status(see Chapter 7).300