Are post-trial observational studies useful?

For more than two centuries, the measurement of urinary proteins has been a standard tool for nephrologists to diagnose kidney disease. Renal disease is characterized by changes in the glomerular filtration barrier leading to increased urinary excretion of proteins, the main protein of which is albumin. This was later called macroalbuminuria and appeared to be associated with an increased risk of progressive renal function loss.1 In the 1980s, novel methods were introduced that enabled the measurement of small quantities of albumin in the urine, called microalbuminuria. The introduction of these techniques encouraged endocrinologists and diabetologists to measure urinary albumin in their patients with diabetes (at that time, this comprised predominantly patients with type 1 diabetes). To note, these small quantities of albumin also predicted the risk of developing progressive renal disease in patients with type 1 diabetes.2 In recent decades, attention on albuminuria as a predictor of renal risk has shifted mainly to patients with type 2 diabetes, likely because of the worldwide increased prevalence of this disease. Studies in populations with type 2 diabetes confirmed the important role of macroalbuminuria in the progression of renal disease, as also found in nondiabetic renal disease.3 In addition, the success of renoprotective interventions was shown to associate with and often depend on the albuminuria-lowering effect: The greater the reduction in albuminuria in the first months of treatment, the greater the subsequent renal risk reduction.4,5 The study by de Boer et al. in this issue of JASN brings the role and importance of macroalbuminuria in the type 1 diabetes population to our attention and provides important insights into the long-term renal outcomes in a contemporary cohort of patients with type 1 diabetes and macroalbuminuria.6 This study analyzed data from the Diabetes Control and Complication Trial (DCCT) and its observational Epidemiology of Diabetes Intervention and Complication (EDIC) follow-up study. The analysis included 159 individuals who developed incident macroalbuminuria over a 25-year followup period. The wealth of data of such long-term follow-up is enormous and a lot can be learned. First, de Boer et al. showed that despite the improvement in treatments over the years, the incidence of progression to macroalbuminuria is still high and is surprisingly similar to that reported in type 2 diabetes. Second, de Boer et al. found that macroalbuminuria is associated with a marked risk of progression in renal disease, as evidenced by an eGFR loss of 25.4 ml/min per 1.73 m per year and a high risk for developing an eGFR,60 ml/min per 1.73 m. Because of the resemblance of such risk data with those data observed in type 2 diabetes, we cannot escape the notion that the treatment of type 1 diabetes should receive more attention, particularly in the prevention of macroalbuminuria. In addition, data on type 2 diabetes in patients with macroalbuminuria and compromised eGFR show an extremely high risk for ESRD (which leads to death in the case of no dialysis or transplantation) or death, which is higher than that of all treated cancers.7 de Boer et al. report that the use of renin-angiotensin-aldosterone system inhibition (RAASi) increased over time, macroalbuminuria regressed, and the risk of renal disease progression decreased. These findings are intuitively compelling and could lead to the conclusion that RAASi may have played a role in either preventing macroalbuminuria or exerting renal protective effects by lowering albuminuria and slowing progression of eGFR decline if macroalbuminuria was present. We should be very careful in drawing such important conclusions from the data presented by de Boer et al.Why? The study design has several limitations that hamper firm conclusions, including the lack of a control group as well as indication bias and selection bias. The study by de Boer et al. combined data from a clinical trial with data from a post-trial observational follow-up study. Their study is thus a mixture of two different study designs. A cohort study is based on data that occur in real life without a particular interference by the investigator, whereas a randomized controlled trial does not follow real life but includes an exposure to an intervention introduced by the investigator. The extension of a clinical trial with an observational period has the advantage of assessing long-term health benefits of the original randomized intervention. After 4 years at the end of the STENO trial, intensive risk factor control did not statistically significantly decrease the risk of mortality. However, the authors performed a post-trial extension period and then discovered that after approximately a 10 year follow-up, intensive risk factor control decreased mortality risk.8 However, the post-trial follow-up period is an observational study that is no longer based on randomized Published online ahead of print. Publication date available at www.jasn.org.