Various reports showcase conflicting results regarding the benefit of cardiac glycosides. Observational studies and secondary analyses of randomized clinical trials have reported increases, decreases, and neutral effects on mortality. These analyses compare patients treated with those not treated with cardiac glycosides and use statistical models to adjust for differences in characteristics of the respective populations. The Digitalis Investigation Group (DIG) trial, the only large randomized clinical trial evaluating the efficacy of digoxin in patients with heart failure, as evidenced by a recent Cochrane Review reported a neutral effect on mortality and a significant reduction in heart failure hospitalizations.
A recent review argued that increases in mortality in patients treated with digoxin in observational data are most likely driven by ‘prescription bias’ which is clinical deterioration leads the treating physician to prescribe an additional drug and consequently sicker patients are more likely treated than healthier patients. The conclusions of the aforementioned observational studies thus rely on the assumption that adjustment for baseline covariates appropriately addresses these prognostic differences.
This report on the DIG trial demonstrates that this assumption does not necessarily hold true: the existence of prescription bias after adjustment for baseline covariates in a situation where the ‘true treatment effect’ in the same data is known to be neutral for mortality and beneficial regarding heart failure hospitalizations.
The primary interpretation of this analysis is to check whether an adjustment in an observational analysis can lead to the same treatment effect estimate as to the randomization-based analysis of the DIG trial.
The design and primary results of the DIG trial have been previously published, out of which 44% of the 6800 study patients had been treated with digoxin prior to study start and were randomized to either continue digoxin or receive a placebo treatment instead (randomized withdrawal). Knowing that digoxin had no effect on overall mortality in the randomized trial. Later the comparison among these patients previously treated with digoxin with the outcome among those who were not treated with digoxin before the start of the study was observed. For more accuracy, there was a repeat in the analysis (i) in patients randomized to digoxin and (ii) in patients randomized to placebo.
In both subpopulations (i) and (ii), pre-treated and not pre-treated patients were identically treated during the trial. Therefore, observed differences between patients previously treated and those newly treated with digoxin or placebo cannot be due to digoxin unless a potential withdrawal or add-on effect is present. These comparisons are ‘observational’ in that, they are not based on the randomization in the trial.
Baseline variables were well balanced between the two randomized treatment groups, but patients previously treated with digoxin systematically differed from patients not previously treated regarding many important baseline variables, especially for heart failure. In contrast, patients previously treated with digoxin had more frequent markers of advanced heart failure than those not previously treated with digoxin.
The DIG trial was conducted several years ago and both diagnosis and treatment of heart failure have changed. Well planned clinical trials document those variables that are needed to describe the patients expected to benefit from treatment and this may depend on the drug but also on the current understanding of the disease. In more recent data, information on biomarkers such as N-terminal prohormone of brain natriuretic peptide may allow better adjustment and obviously the treatment effect at the time the DIG-trial has been conducted may be different from what would be observed today. Nonetheless, data from the DIG trial is of high quality, and ‘residual bias’ is substantial.