Confounding in Observational Studies Evaluating the Safety and Effectiveness of Medical Treatments

Randomized controlled trials (RCTs) are considered the “gold standard” for establishing the safety and efficacy of medical treatments, such as drugs, devices, and procedures. Patients with kidney disease are often excluded from these studies (1), and it is well established that trial participants tend to be healthier than the broader kidney disease population (2). Furthermore, the number of nephrology-specific trials conducted continues to lag behind other subspecialties (3). In the absence of RCT data, nephrology practitioners may look to population-specific observational evidence to guide therapy selection. Observational studies using real-world data ( e.g. , administrative claims and electronic healthcare record data) to evaluate the safety and effectiveness of medical treatments can provide highly generalizable and valuable information to clinicians (4). However, like nonrandomized prospective cohort studies, these studies may suffer from biases that limit their validity, such as confounding. In this commentary, I describe what confounding is and provide a brief overview of common types of confounding that can arise in observational studies of medical treatments. I then highlight some common strategies for addressing confounding and discuss potential sources of residual confounding. In an observational study, confounding occurs when a risk factor for the outcome also affects the exposure of interest, either directly or indirectly. The resultant bias can strengthen, weaken, or completely reverse the true exposure-outcome association. For a factor to be a confounder, it has to be associated with both the study exposure and the study outcome, and temporally precede the exposure ( i.e. , it cannot be an intermediary factor on the causal pathway between the exposure and the outcome) (5). ### Confounding by Indication and Examples of Other Types of Confounding Confounding by indication (6) is one of the most common forms of bias present in observational studies evaluating the safety and effectiveness of medical treatments. It occurs when the clinical indication for treatment, such as the …