Marcia Landa

Progression of Chronic Kidney Disease: The Role of Blood Pressure Control, Proteinuria, and Angiotensin-Converting Enzyme Inhibition: A Patient-Level Meta-Analysis

Context Guidelines recommend a blood pressure of less than 130/80 mm Hg for patients with chronic kidney disease. Contribution This meta-analysis showed that systolic blood pressure and urinary protein excretion were related to the risk for renal disease progression in patients with nondiabetic kidney disease. Systolic pressures of 110 to 129 mm Hg were associated with the lowest risks. Higher risks with higher pressures were marked in patients with protein excretion greater than 1.0 g/d and were not apparent in those with lower urinary protein excretion. Implications In patients with urinary protein excretion greater than 1.0 g/d, systolic blood pressure of 110 to 129 mm Hg is associated with the lowest risk for progression of renal disease. The Editors Chronic kidney disease is a major public health problem in the United States. The prevalence of kidney failure (recorded as end-stage renal disease) has risen steadily since Medicare assumed funding for the condition in 1973. By 2010, it is estimated that the prevalence will be greater than 650 000 (1). The prevalence of earlier stages of chronic kidney disease is even higher. The Third National Health and Nutrition Examination Survey (NHANES III), conducted from 1988 to 1994, estimates that 5.6 million persons 17 years of age or older had decreased kidney function, as defined by an elevated serum creatinine concentration ( 141 mol/L [ 1.6 mg/dL] in men and 124 mol/L [ 1.4 mg/dL] in women) (2). Hypertension and proteinuria occur in most patients with chronic kidney disease and are risk factors for faster progression of kidney disease. Antihypertensive agents reduce blood pressure and urine protein excretion and slow the progression of kidney disease. The sixth report of the Joint National Committee for the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC-VI) recommends a lower blood pressure goal for patients with decreased kidney function (<130/85 mm Hg if urine protein excretion is <1 g/d and <125/75 mm Hg if urine protein excretion is >1 g/d) than for patients without target organ damage (<140/90 mm Hg) (3). It is not known whether even lower blood pressure might provide additional benefit. On the other hand, there is concern about excessive lowering of blood pressure because it may be associated with a higher risk for cardiovascular disease (4, 5). Additional lowering of blood pressure might also have a detrimental effect on kidney disease. The recommendations in JNC-VI are based principally on the results of the Modification of Diet in Renal Disease (MDRD) Study (6, 7), a study of nondiabetic kidney disease that did not evaluate the effect of angiotensin-converting enzyme (ACE) inhibitors or angiotensin-receptor blockers. Since publication of the JNC-VI, other large studies and meta-analyses have shown that antihypertensive regimens containing ACE inhibitors or angiotensin-receptor blockers seem to be more effective than other regimens in slowing the progression of chronic kidney disease (8-17). In some studies, the beneficial effect of these agents seemed to be greater in patients with proteinuria (8-11, 13) and was mediated in part by their effects to lower blood pressure and urine protein excretion (13). Of these studies, only the African American Study of Kidney Disease and Hypertension (AASK) compared two levels of blood pressure in patients treated with an ACE inhibitor (11). In that study of patients with hypertensive nephrosclerosis, a type of kidney disease associated with low levels of proteinuria, a lower blood pressure goal did not reduce the risk for progression of kidney disease when compared with a usual blood pressure goal. However, the AASK does not address the relationships of blood pressure and urine protein excretion with the progression of kidney disease in patients with higher levels of urine protein excretion. We performed a patient-level meta-analysis using data from the ACE Inhibition in Progressive Renal Disease (AIPRD) Study Group database (13) to assess these relationships among patients with nondiabetic kidney disease across a wide range of urine protein excretion values during antihypertensive therapy with and without ACE inhibitors. Methods Study Design The AIPRD Study Group database includes 1860 patients with nondiabetic kidney disease enrolled in 11 randomized, controlled trials of ACE inhibitors to slow the progression of kidney disease. The database contains information on blood pressure, urine protein excretion, serum creatinine concentration, and onset of kidney failure during 22 610 visits. Inclusion and exclusion criteria, search strategies for identifying clinical trials, and details of database formulation have been previously described (13, 18). The AIPRD Study Group was formed in 1997. Briefly, we identified studies by searching the MEDLINE database for English-language reports evaluating the effect of ACE inhibitors or kidney disease in humans between 1977 (when ACE inhibitors were approved for trials in humans) and 1999 (when the database was closed). We included only randomized trials (with a minimum 1-year follow-up) that compared the effects of antihypertensive regimens that included ACE inhibitors with the effects of regimens that did not include ACE inhibitors. Hypertension or decreased kidney function was required for entry into all studies. Exclusion criteria common to all studies were acute kidney failure, treatment with immunosuppressive medications, clinically significant congestive heart failure, obstructive uropathy, renal artery stenosis, active systemic disease, type 1 diabetes mellitus, history of transplantation, history of allergy to ACE inhibitors, and pregnancy. The institutional review board at each participating center approved the study, and all patients gave informed consent. Patients were enrolled between March 1986 and April 1996. All patients were randomly assigned to antihypertensive regimens either with or without ACE inhibitors. The ACE inhibitors included captopril, enalapril, cilazapril, benazepril, and ramipril. Concomitant antihypertensive medications were used in both groups to achieve a target blood pressure less than 140/90 mm Hg in all studies. All patients were followed at least once every 3 months for the first year and at least once every 6 months thereafter. Justification for pooling the 11 clinical trials is based on the similarity of study designs and patient characteristics. Justification for pooling placebo-controlled and active-drugcontrolled trials is based on the presence of preexisting hypertension and the use of antihypertensive agents in most patients in the control groups in each clinical trial. Thus, the pooled analysis addresses the clinically relevant question of the relationship of the level of blood pressure and urine protein excretion with the kidney disease progression during antihypertensive therapy, either with or without ACE inhibitors. Definition and Ascertainment of Blood Pressure and Urine Protein Excretion Clinical trial protocols stipulated measurement of blood pressure more frequently than urine protein excretion. In our database, visit was defined as any contact with patients during which study-related information was recorded or clinical variables were measured. Blood pressure was recorded on the same day as the visit in 94% of the visits and within 3 months before the visit in 99% of the visits. Urine protein excretion was recorded on the same day as the visit in 62% of the visits and within 6 months before the visit in 97% of the visits. Blood pressure and urine protein excretion levels at follow-up visits are defined as the current levels. We used current as well as baseline levels as the variables of interest for these analyses because guidelines for blood pressure target current values (3) and our previous studies have demonstrated that the current level of urine protein excretion is a stronger predictor of kidney disease progression than is the baseline level (19). Blood pressure was measured by using a mercury sphygmomanometer in nine studies (8-10, 20-24; Brenner BM. Personal communication) (93% of visits) and calibrated automatic device in two studies (25, 26). Systolic and diastolic blood pressure were measured after 5 to 10 minutes of rest in the supine position in 10 studies (8-10, 20, 22-26; Brenner BM. Personal communication) and in the sitting position in 1 study (21). Urine protein excretion was reported as total urine protein excretion in a 24-hour urine sample in 10 studies (8-10, 20-22, 24-26; Brenner BM. Personal communication) (95% of visits). One study performed a dipstick assessment in an untimed urine sample and reported quantitative measurement only if the dipstick result was positive (23). For that study, all values of dipstick negative were assigned a value of 0.1 g/d. In all studies, results for urine protein excretion of 0.1 g/d or lower were also assigned a value of 0.1 g/d. Values greater than 0.1 g/d were recorded as the exact values reported in the study and rounded to the nearest 0.1 g/d. Outcomes Serum creatinine concentration was recorded on the same day as the visit in 78% of visits and within 3 months after the visit in 96% of the visits. The primary outcome for the pooled analysis was kidney disease progression, defined as a combined end point of a twofold increase (doubling) in serum creatinine concentration from baseline values or development of kidney failure, defined as the initiation of long-term dialysis therapy. Statistical Analyses We used S-Plus 2000 (Insightful Corp., Seattle, Washington) and SAS software, version 8.2 (SAS Institute, Inc., Cary, North Carolina), software programs for statistical analyses. Cox proportional-hazards regression analysis was performed to detect associations between the covariates and outcomes. Baseline patient characteristics were treatment assignment (ACE inhibitor vs. control, using the intention-to-treat principle), age (logarithmic

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

Progression Risk, Urinary Protein Excretion, and Treatment Effects of Angiotensin-Converting Enzyme Inhibitors in Nondiabetic Kidney 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)

The value of breast lumpectomy margin assessment as a predictor of residual tumor burden in ductal carcinoma in situ of the breast

It is unclear whether patients with nondiabetic kidney disease benefit from angiotensin-converting enzyme inhibitor (ACEI) therapy when they are at low risk for disease progression or when they have low urinary protein excretion. With the use of a combined database from 11 randomized, clinical trials (n = 1860), a Cox proportional hazards model, based on known predictors of risk and the composite outcome kidney failure or creatinine doubling, was developed and used to stratify patients into equal-sized quartiles of risk. Outcome risk and treatment effect were examined across various risk strata. Use of this risk model for targeting ACEI therapy was also compared with a strategy based on urinary protein excretion alone. Control patients in the highest quartile of predicted risk had an annualized outcome rate of 28.7%, whereas control patients in the lowest quartile of predicted risk had an annualized outcome rate of 0.4%. Despite the extreme variation in risk, there was no variation in the degree of benefit of ACEI therapy (P = 0.93 for the treatment x risk interaction). Significant interaction was detected between baseline urine protein and ACEI therapy (P = 0.003). When patients were stratified according to their baseline urinary protein excretion, among the subgroup of patients with proteinuria > or =500 mg/d, significant treatment effect was seen across all patients with a measurable outcome risk, including those at relatively low risk (1.7% annualized risk for progression). However, there was no benefit of ACEI therapy among patients with proteinuria <500 mg/d, even among higher risk patients (control outcome rate 19.7%). Patients with nondiabetic kidney disease vary considerably in their risk for disease progression, but the treatment effect of ACEI does not vary across risk strata. Patients with proteinuria <500 mg/d do not seem to benefit, even when at relatively high risk for progression.

Comorbidity Assessment in Hemodialysis and Peritoneal Dialysis Using the Index of Coexistent Disease

Margin width is considered the most important risk factor for local recurrence in ductal carcinoma in situ (DCIS) of the breast. The purpose of this report is to assess the predictive utility of lumpectomy specimen margin assessment for the presence and extent of residual DCIS.

Margin width as a determinant of local control with and without radiation therapy for ductal carcinoma in situ (DCIS) of the breast.

The purpose of this paper is to describe the ICED, summarize outcomes of prior studies in which it was used, and describe the adaptations that have lead to the present instrument. We will then demonstrate its use in quantifying the burden of comorbid conditions in a sample of hemodialysis and peritoneal dialysis patients from our center, and show the relationship between ICED levels and outcomes in peritoneal dialysis patients.

Constructing a database of individual clinical trials for longitudinal analysis

In order to assess the utility of margin width in relation to other histopathologic features as a determinant of local control in ductal carcinoma in situ (DCIS) of the breast, we retrospectively examined the treatment of 109 breasts treated with (n = 54) or without adjuvant radiotherapy (n = 55). Median follow‐up was 49 and 54 months for patients treated with excision alone (E) or excision plus adjuvant radiotherapy (E+XRT), respectively. Cases treated with E+XRT were significantly larger and had a trend towards closer surgical margins than those treated with E alone. For all cases, margin width ≤1 mm and lesion diameter >15 mm were significantly associated with increased local recurrence. Lesion size ≤15 mm was associated with no cases of local failure regardless of treatment arm. For lesions >15 mm in diameter, there was a significant decrease in 5‐year local failure with E+XRT compared to E alone (21% vs. 36%, P = 0.03). Tumor margin >1 mm was associated with a low rate of 5‐year local failure for either E alone or E+XRT (10.9% vs. 4.6%, P = NS). Tumor margin ≤1 mm had a high rate of local failure that was not significantly decreased by the addition of adjuvant radiotherapy. These results show that large diameter (>15mm) and close surgical margins (≤1 mm) are the dominant risk factors for local recurrence in DCIS. E+XRT significantly decreased local failure risk compared to E alone for large lesions but not for those with close margins.

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

Individual patient data are often required to evaluate how patient-specific factors modify treatment effects. We describe our experience combining individual patient data from 1946 subjects in 11 randomized controlled trials evaluating the effect of angiotensin-enzyme converting (ACE) inhibitors for treating nondiabetic renal disease. We sought to confirm the results of our meta-analysis of group data on the efficacy of ACE inhibitors in slowing the progression of renal disease, as well as to determine whether any study or patient characteristics modified the beneficial effects of treatment. In particular, we wanted to find out if the mechanism of action of ACE inhibitors could be explained by adjusting for follow-up blood pressure and urine protein. Each trial site sent a database of multiple files and multiple records per patient containing longitudinal data of demographic, clinical, and medication variables to the data coordinating center. The databases were constructed in several different languages using different software packages with unique file formats and variable names. Over 4 years, we converted the data into a standardized database of more than 60,000 records. We overcame a variety of problems including inconsistent protocols for measurement of key variables; varying definitions of the baseline time; varying follow-up times and intervals; differing medication-reporting protocols; missing variables; incomplete, missing, and implausible data values; and concealment of key data in text fields. We discovered that it was easier and more informative to request computerized data files and merge them ourselves than to ask the investigators to abstract partial data from their files. Although combining longitudinal data from different trials based on different protocols in different languages is complex, costly, and time-intensive, analyses based on individual patient data are extremely informative. Funding agencies must be encouraged to provide support to collaborative groups combining databases.