Paul E. de Jong

Angiotensin-Converting Enzyme Inhibitors and Progression of Nondiabetic Renal Disease: A Meta-Analysis of Patient-Level Data

Chronic renal disease is a major public health problem in the United States. According to the 1999 Annual Data Report of the U.S. Renal Data System, more than 357 000 people have end-stage renal disease (ESRD), and the annual cost of treatment with dialysis and renal transplantation exceeds

The Antiproteinuric Effect of Angiotensin-Converting-Enzyme Inhibitors in Human Renal Disease

15.6 billion (1). Patients undergoing dialysis have reduced quality of life, a high morbidity rate, and an annual mortality rate of 20% to 25% (1). Identification of therapies to prevent ESRD is an important public health goal. Angiotensin-converting enzyme (ACE) inhibitors are highly effective in slowing the progression of renal disease due to type 1 diabetes (26), and evidence of their efficacy in type 2 diabetes is growing (712). However, although 14 randomized, controlled trials have been completed (1325; Brenner BM; Toto R. Personal communications), no consensus exists on the use of ACE inhibitors in nondiabetic renal disease (2628). In a previous meta-analysis of 11 randomized, controlled trials, we found that therapy with ACE inhibitors slowed the progression of nondiabetic renal disease (29). Since our meta-analysis was performed on group data rather than individual-patient data, we could not fully assess the relationship between the effect of ACE inhibitors and blood pressure, urinary protein excretion, or other patient characteristics (30). Thus, we could not determine whether an equal reduction in blood pressure or urinary protein excretion by using other antihypertensive agents would be as effective in slowing the progression of renal disease. Nor could we determine whether the baseline blood pressure, urinary protein excretion, or other patient characteristics modified the response to treatment. In the current report, we used pooled analysis of individual-patient data to answer these questions. We reasoned that the large number of patients in the pooled analysis would provide sufficient statistical power to detect relationships between patient characteristics and risk for progression of renal disease and interactions of patient characteristics with treatment effect. In principle, strong and consistent results from analysis of this large database would clarify the effects of ACE inhibitors for treatment of nondiabetic renal disease. Methods Study Design We obtained individual-patient data from nine published (1322) and two unpublished (Brenner BM; Toto R. Personal communications) randomized, controlled trials assessing the effects of ACE inhibitors on renal disease progression in predominantly nondiabetic patients. Search strategies used to identify clinical trials have been described elsewhere and are reviewed in Appendix 2. We included 11 randomized trials on progression of renal disease that compared the effects of antihypertensive regimens including ACE inhibitors to the effects of regimens without ACE inhibitors, with a follow-up of at least 1 year. In these studies, the institutional review board at each participating center approved the study, and all patients gave informed consent. Patients underwent randomization between March 1986 and April 1996. Hypertension or decreased renal function was required for entry into all studies. Exclusion criteria common to all studies were acute renal failure, treatment with immunosuppressive medications, clinically significant congestive heart failure, obstructive uropathy, renal artery stenosis, active systemic disease, insulin-dependent diabetes mellitus, history of transplantation, history of allergy to ACE inhibitors, and pregnancy. Table 1 shows characteristics of the patients in each study. Table 1. Study and Patient Characteristics in the Randomized, Controlled Trials Included in the Pooled Analysis Before randomization, patients already taking an ACE inhibitor were switched to alternative medications for at least 3 weeks. After randomization, the ACE inhibitor groups received enalapril in seven studies (1419; Brenner BM; Toto R. Personal communications) and captopril (13), benazepril (20), cilazapril (18), and ramipril (21, 22) in one study each. The control groups received placebo in five studies (1922; Brenner BM; Toto R. Personal communications), a specified medication in five studies (nifedipine in two studies [13, 17] and atenolol or acebutolol in three studies [15, 16, 18]), and no specified medication in one study (14). Other antihypertensive medications were used in both groups to reach the target blood pressure, which was less than 140/90 mm Hg in all studies. All patients were followed at least once every 6 months for the first year and at least once yearly thereafter. Blood pressure and laboratory variables were measured at each visit. Table 1 shows outcomes of each study. We pooled the 11 clinical trials on the basis of similarity of study designs and patient characteristics. In addition, the presence of preexisting hypertension and use of antihypertensive agents in most patients in the control groups in each clinical trial justified pooling data from placebo-controlled and active-controlled trials. Thus, the pooled analysis addresses the clinically relevant question of whether antihypertensive regimens including ACE inhibitors are more effective than anti-hypertensive regimens not including ACE inhibitors in slowing the progression of nondiabetic renal disease. Outcomes Two primary outcomes were defined: ESRD, defined as the initiation of long-term dialysis therapy, and a combined outcome of a twofold increase in serum creatinine concentration from baseline values or ESRD. Because ESRD is a clinically important outcome, we believed that definitive results of analyses using this outcome would be clinically relevant. However, because most chronic renal diseases progress slowly, few patients might reach this outcome during the relatively brief follow-up of these clinical trials, resulting in relatively low statistical power for these analyses. Doubling of baseline serum creatinine is a well-accepted surrogate outcome for progression of renal disease in studies of antihypertensive agents (2, 20) and would be expected to occur more frequently than ESRD, providing higher statistical power for analyses using this outcome. Doubling of baseline serum creatinine concentration was confirmed by repeated evaluation in only one study, which used this variable as the primary outcome. Therefore, we did not require confirmation of doubling for our analysis. Other outcomes included death and a composite outcome of ESRD and death. Withdrawal was defined as discontinuation of follow-up before the occurrence of an outcome or study end. Reasons for withdrawal were 1) nonfatal side effects possibly due to ACE inhibitors, including hyperkalemia, cough, angioedema, acute renal failure, or hypotension; 2) nonfatal cardiovascular disease events, including myo-cardial infarction, congestive heart failure, stroke, transient ischemic attack, or claudication; 3) other nonfatal events, such as malignant disease, pneumonia, cellulitis, headache, or gastrointestinal disturbance; and 4) other reasons, including loss to follow-up, protocol violation, or unknown. Statistical Analysis Five investigators participated in data cleaning. Summary tables were compiled from the individual-patient data from each study and checked against tables in published and unpublished reports. Discrepancies were resolved by contacting investigators at the clinical or data coordinating centers whenever possible. Because the studies followed different protocols, we had to standardize the variable definitions, follow-up intervals, and run-in periods; details of our approach are provided in Appendix 2. S-Plus (MathSoft, Inc., Seattle, Washington) and SAS (SAS Institute, Inc., Cary, North Carolina) software programs were used for all statistical analyses (31, 32). Univariate analysis was performed to detect associations between the covariates and outcomes. Baseline patient characteristics were treatment assignment (ACE inhibitor vs. control), age (logarithmic transformation), sex, ethnicity, systolic blood pressure, diastolic blood pressure, mean arterial pressure, serum creatinine concentration (reciprocal transformation), and urinary protein excretion. Study characteristics were blinding, type of antihypertensive regimen in the control group, planned duration of follow-up, whether dietary protein or sodium was restricted, and year of publication. Baseline patient characteristics and study characteristics were introduced as fixed covariates. Since renal biopsy was not performed in most cases and since criteria for classification of cause of renal disease were not defined, the cause of renal disease was not included as a variable in the analysis. Follow-up patient characteristics (blood pressure and urinary protein excretion) were adjusted as time-dependent covariates; the value recorded at the beginning of each time segment was used for that segment. This convention was used so that each outcome would be determined only by previous exposure. The intention-to-treat principle was followed for comparison of randomized groups. Cox proportional-hazards regression models were used to determine the effect of assignment to ACE inhibitors (treatment effect) and other covariates on risk for ESRD and the combined outcome (33, 34). Multivariable models were built by using candidate predictors that were associated with the outcome (P<0.2) in the univariate analysis. Each model was adjusted for study, but since some studies had no events, we could not include a dummy variable for each study. Rather, we adjusted models for studies that differed significantly from the rest (studies 2 [14], 5 [15], 10 [20], and 11 [21, 22]). We also performed tests for interactions between all covariates and treatment effect. All P values were based on two-sided tests, and significance was set at a P value less than 0.05. Results are expressed as relative risks with 95% CIs. Residual diagnostics were performed on these final models (33, 34)

How to Attain Optimal Antiproteinuric Dose of Losartan in Non-Diabetic Patients with Nephrotic Range Proteinuria

Many renal diseases are accompanied by an excess loss of plasma proteins in the urinary space. As such proteinuria has been successfully used as a tool both to detect the presence of renal disease and to evaluate the success of therapeutic interventions on disease activity. The quantity and quality of the urinary protein leakage may in some cases distinguish between the different underlying causes of renal disease. In case of minimalchange disease, protein is usually excreted in considerable quantities, largely confined to albumin, whereas in case of specific renal tubular diseases proteinuria is rather small consisting mainly of low-molecular-weight proteins. However, in general, proteinuria does not differentiate between the multiple causes of renal insults, suggesting a more or less common cause and pathway of urinary protein loss. Indeed, such a common cause may be a loss of the discriminating properties of the glomerular filtration barrier for different macromolecules. In health, this barrier prevents the leakage of plasma proteins to the urinary space by at least two selective mechanisms. Firstly, the filtration pores are of limited size, hindering passage of macromolecules larger than ≈55 Angstrom (size selectivity). Secondly, negative charges embedded in the filtration barrier prevent leakage of the main negatively-charged plasma protein, albumin (charge selectivity). Furthermore, proximal tubular protein reabsorption prevents urinary protein leakage of those proteins that escape these restrictive filtration properties.

Proteinuria as a modifiable risk factor for the progression of non-diabetic renal disease

Although the antiproteinuric response to antihypertensive treatment is the main predictor of renoprotective efficacy in long-term renal disease, dose finding studies of antihypertensives have only been based on blood pressure so far. The present study aimed to find the optimal antiproteinuric dose of the angiotensin II antagonist losartan. An open-label dose-response study using subsequent six-week treatment periods was performed in ten non-diabetic patients with proteinuria (Uprot) of 5.8 ± 0.8 g/d and a mean arterial pressure (MAP) of 103 ± 3.7 mmHg without antihypertensive medication. All patients had a normal to moderately impaired renal function. After the baseline period, five periods followed with respectively a daily losartan dose of 50 mg, 100 mg, 150 mg, again 50 mg, and a recovery without losartan. At the end of each period, Uprot and MAP were measured. The consecutive doses of losartan had a similar antihypertensive response (−11.3 f 2.8% at the 100 mg dose). The optimal antiproteinuric response was reached at 100 mg losartan (−30 ± 8%). The 50 mg dose (−13 ± 7%) was less effective and the 150 mg dose (−28 ± 8%) was not more effective. We conclude that 100 mg losartan is the optimal dose for reduction of proteinuria in non-diabetic patients with nephroticrange proteinuria.