The Effects of Dietary Protein Restriction and Blood-Pressure Control on the Progression of Chronic Renal Disease
Saulo Klahr, Andrew S. Levey, Gerald J. Beck, Arlene W. Caggiula, Lawrence Hunsicker, John W. Kusek, Gary Striker, for The Modification of Diet in Renal Disease Study Group
Background Restricting protein intake and controlling hypertensiondelay the progression of renal disease in animals. We testedthese interventions in 840 patients with various chronic renaldiseases.
Methods In study 1, 585 patients with glomerular filtrationrates of 25 to 55 ml per minute per 1.73 m2 of body-surfacearea were randomly assigned to a usual-protein diet or a low-proteindiet (1.3 or 0.58 g of protein per kilogram of body weight perday) and to a usual- or a low-blood-pressure group (mean arterialpressure, 107 or 92 mm Hg). In study 2, 255 patients with glomerularfiltration rates of 13 to 24 ml per minute per 1.73 m2 wererandomly assigned to the low-protein diet (0.58 g per kilogramper day) or a very-low-protein diet (0.28 g per kilogram perday) with a keto acid-amino acid supplement, and a usual- ora low-blood-pressure group (same values as those in study 1).An 18-to-45-month follow-up was planned, with monthly evaluationsof the patients.
Results The mean follow-up was 2.2 years. In study 1, the projectedmean decline in the glomerular filtration rate at three yearsdid not differ significantly between the diet groups or betweenthe blood-pressure groups. As compared with the usual-proteingroup and the usual-blood-pressure group, the low-protein groupand the low-blood-pressure group had a more rapid decline inthe glomerular filtration rate during the first four monthsafter randomization and a slower decline thereafter. In study2, the very-low-protein group had a marginally slower declinein the glomerular filtration rate than did the low-protein group(P = 0.07). There was no delay in the time to the occurrenceof end-stage renal disease or death. In both studies, patientsin the low-blood-pressure group who had more pronounced proteinuriaat base line had a significantly slower rate of decline in theglomerular filtration rate.
Conclusions Among patients with moderate renal insufficiency,the slower decline in renal function that started four monthsafter the introduction of a low-protein diet suggests a smallbenefit of this dietary intervention. Among patients with moresevere renal insufficiency, a very-low-protein diet, as comparedwith a low-protein diet, did not significantly slow the progressionof renal disease.
Protein restriction and control of blood pressure delay theprogression of renal disease in laboratory animals1,2,3. Moststudies in humans4,5,6,7,8,9,10 have suggested that a restrictionof dietary protein is beneficial, especially in patients withadvanced renal disease,4,10 but some of these studies were inconclusivebecause of deficiencies in their design or because changes inrenal function were assessed only by measurements of serum creatinine,which may be affected by diet. Furthermore, few previous studiesof renal disease have examined the effect on renal functionof a reduction in blood pressure to a level below that currentlyrecommended for the prevention and treatment of cardiovasculardisease11.
We describe the results of the intention-to-treat analyses ofthe Modification of Diet in Renal Disease (MDRD) Study, whichincluded two randomized, multicenter trials involving a totalof 840 patients with various chronic renal diseases. The studytested the hypotheses that two interventions -- a reductionin dietary protein and phosphorus intake and the maintenanceof blood pressure at a level below that usually recommended11-- retard the progression of renal disease and that these interventionsare safe and acceptable to patients for long-term use12,13,14.
Methods
The organization, design, and methods of the MDRD Study havebeen reported in detail previously12,13,14,15,16,17,18,19,20,21,22.The study was approved by the institutional review committeeat each participating center, and all patients gave writteninformed consent.
Recruitment, Screening, and Base-Line Period
The recruitment procedures have been described elsewhere21.The following enrollment criteria were used: an age of 18 to70 years, a serum creatinine concentration of 1.2 to 7.0 mgper deciliter (106 to 619 µmol per liter) in women and1.4 to 7.0 mg per deciliter (124 to 619 µmol per liter)in men or a creatinine clearance of less than 70 ml per minuteper 1.73 m2 of body-surface area, and a mean arterial pressure(calculated as two thirds of the diastolic plus one third ofthe systolic blood pressure) of 125 mm Hg or less. Normotensivepatients were included in the study, and evidence of a progressivedecline in the glomerular filtration rate was not required forenrollment. Patients were excluded for the following reasons:pregnancy, a body weight under 80 percent or over 160 percentof standard body weight,23 diabetes mellitus requiring insulintherapy, urinary protein excretion exceeding 10 g per day, ahistory of renal transplantation or chronic medical conditions,or doubts about compliance13. Patients were eligible for study1 or 2 on the basis of their glomerular filtration rate. Ineach study, we assessed the effects of two dietary and two blood-pressureinterventions. The planned duration of follow-up was 18 to 45months.
During a three-month base-line period, patients were deemedeligible for study 1 if their glomerular filtration rate was25 to 55 ml per minute per 1.73 m2, their dietary protein intakewas 0.9 g per kilogram of body weight per day, and their meanarterial pressure was 125 mm Hg. Patients were eligible forstudy 2 if their glomerular filtration rate was 13 to 24 mlper minute per 1.73 m2 and their mean arterial pressure was 125 mm Hg, irrespective of protein intake. Blood pressure,creatinine clearance, and urinary protein excretion were measuredinitially and then every month during the base-line period (atotal of four measurements). During this period, patients wereinstructed about the study procedures, dietary protein intake,and control of blood pressure.
Randomization and Intervention
For randomization, patients were stratified according to theclinical center and the average base-line blood pressure (inboth studies) and according to the rate of change in the serumcreatinine concentration during the screening period (in study1 only)13. After randomization, the patients were instructedto modify their intake of protein and phosphorus to achievethe goals of the diet to which they had been assigned. Dietarysodium intake was not restricted.
We used pharmacologic and nonpharmacologic therapies to achievethe desired blood-pressure values in the usual- and low-pressuregroups. The recommended antihypertensive regimen was an angiotensin-converting-enzymeinhibitor with or without a diuretic agent; a calcium-channelblocker and other medications were added as needed. Hyperphosphatemiawas treated with calcium carbonate as needed.
Follow-up Procedures and Measurements
Protein intake was assessed monthly on the basis of 24-hoururinary excretion of urea nitrogen24. Nitrogen in the prescribedketo acid-amino acid supplement was subtracted from urinaryurea nitrogen. The intake of protein, calories, and other nutrientswas assessed every two months on the basis of three-day dietaryrecords. Blood pressure was measured monthly, and when necessary,adjustments in therapy were made monthly or more often. Theglomerular filtration rate was measured at two months, at fourmonths, and every four months thereafter on the basis of therenal clearance of [125I]iothalamate (Isotex Diagnostics, Friendswood,Tex.)17. Anthropometric measurements were obtained every fourmonths16,23.
Definition and Ascertainment of End Points
The rate of change in the glomerular filtration rate (the slope)was the primary outcome measure. Slopes were calculated on thebasis of the final base-line glomerular filtration rate andall follow-up rates without adjustment for the body-surfacearea. Slopes were not calculated for 11 patients for whom welacked measurements after the base-line period.
Conditions requiring withdrawal from the study (stopping points)included malnutrition (weight loss to a level below 75 percentof standard body weight or a serum albumin concentration under3.0 g per deciliter despite corrective measures), a rapid declinein the glomerular filtration rate in study 1 only (to a value<50 percent of the base-line rate, if that value was 40ml per minute per 1.73 m2, or to a value of 20 ml per minuteper 1.73 m2, if the base-line rate was >40 ml per minuteper 1.73 m2), end-stage renal disease requiring dialysis ortransplantation, and the development of other serious medicalconditions.
Statistical Analysis
Using an intention-to-treat approach, we related follow-up measurementsof the patients' glomerular filtration rates to the prescribedinterventions. Although the protocol called for testing theeffects of diet and blood pressure on the decline in the glomerularfiltration rate with the use of a single-slope linear model,the possibility of a nonlinear decline was also considered13.In study 1, patients assigned to either the low-protein dietor the low-blood-pressure group had a faster initial declinein the glomerular filtration rate (from base line to four months)and a slower subsequent decline than those assigned to the usual-proteindiet or the usual-blood-pressure group. Therefore, the primaryanalysis used a two-slope spline model in which each patientwas assumed to have an initial slope from base line to fourmonths and a different slope subsequently. The mean initialand subsequent slopes were estimated for each group by the methodof maximum likelihood in a mixed-effects model,25 with the stratificationfactors used at randomization included as covariates. The effectsof the dietary and blood-pressure interventions were testedon the initial and subsequent slopes and on the mean projectedchange in the glomerular filtration rate from base line to threeyears.
In study 2, a single-slope linear model was used. Because ofthe large number of stopping points due to end-stage renal disease,however, we obtained maximum-likelihood estimates of the interceptand slope using an informative censoring model,26 which tookinto account the time to the occurrence of end-stage renal diseaseor death.
In both studies, the interaction between the diet and blood-pressureinterventions was tested for significance before the effectsof individual interventions were evaluated. To assess the uniformityof the effects of diet and blood pressure, we compared theireffects in subgroups defined initially by age, sex, renal diagnosis,base-line glomerular filtration rate, and urinary protein excretion.Subsequently, other base-line factors were also examined, includingrace, the presence or absence of hypertension, blood pressure,protein intake, the serum cholesterol concentration, and therate of change in the serum creatinine concentration duringscreening.
Time-to-event analyses were conducted with the use of the Kaplan-Meiermethod to estimate cumulative-incidence curves27 and with stratifiedlog-rank tests to compare the diet and blood-pressure groups.The data from these analyses were censored at the date of thefinal follow-up visit in study 1 and on June 15, 1993, approximatelyfive months after the final follow-up visit, in study 2. Whentesting for the effect of one intervention, we stratified theanalysis according to the other intervention and the randomizationstrata. All statistical analyses were performed with two-tailedtests.
Results
Recruitment and Follow-up
A total of 840 patients were enrolled in the study and randomlyassigned to the various diet and blood-pressure interventions(Table 1). The mean follow-up was 2.2 years (range, 0 to 3.7).Eleven of the 585 patients in study 1 (1.9 percent) and 3 ofthe 255 in study 2 (1.2 percent) were lost to follow-up.
Table 1. Assignment of Patients to Diet and Blood-Pressure Groups in Studies 1 and 2.
Base-Line Characteristics
The clinical characteristics of the patients in each diet andblood-pressure group are shown in Table 222. Sixty percent ofthe patients were men, 85 percent were white, and the averageage was 52 years. The most common renal diagnoses were glomerulardiseases (25 percent) and polycystic kidney disease (24 percent);3 percent of the patients had non-insulin-dependent diabetes.
Table 2. Clinical Characteristics of the Study Population at the Time of Randomization.
Adherence
Differences in protein intake between the diet groups were achievedby the fourth month of follow-up and remained relatively constantthroughout the follow-up period (Figure 1). On the basis ofpill counts, the median amount of prescribed keto acid-aminoacid supplements taken was 92 percent.
Figure 1. Estimated Protein Intake and Mean Arterial Pressure in Patients with Renal Disease Enrolled in Studies 1 and 2.
Protein intake was estimated from urinary excretion of urea nitrogen. The two diets in study 2 were designed to provide the same amount of nitrogen, but the nitrogen contained in the keto acid-amino acid mixture was subtracted from the urinary urea nitrogen in the very-low-protein group. The median values at each base-line (B) and follow-up (F) visit are given for the patients on the usual-protein diet (dashed line), the low-protein diet (solid line), and the very-low-protein diet (dashed-and-dotted line) and for those with usual blood pressure (dashed line) and low blood pressure (solid line). The bars show the 25th and 75th percentiles. The numbers of patients with estimated protein intake and blood-pressure measurements at each visit are shown below the panels. Urea nitrogen values are shown at selected times; mean arterial pressure is shown at selected visits when the glomerular filtration rate was not measured.
The difference in mean blood pressure between the usual-pressureand the low-pressure groups during the follow-up period was4.7 mm Hg (P<0.001) in studies 1 and 2 (Figure 1). Antihypertensive(including diuretic) drugs were taken for more than half thefollow-up period by 80 percent and 90 percent of the patientsin the usual- and low-pressure groups, respectively, in study1 and by 85 and 98 percent in study 2. In study 1, angiotensin-converting-enzymeinhibitors were taken alone or in combination for more thanhalf the follow-up period by 34 and 54 percent of the patientsin the usual- and low-pressure groups, respectively, and by44 percent of those in each diet group. In study 2, angiotensin-converting-enzymeinhibitors were used by 27 and 43 percent of the patients inthe usual- and low-pressure groups, respectively, and by 39and 32 percent of the patients in the low- and very-low-proteingroups, respectively.
Renal Function
There were no significant interactions between the dietary orblood-pressure interventions and the rate of decline in theglomerular filtration rate in either study 1 or study 2; thatis, the effects of the dietary interventions were similar inthe two blood-pressure groups, and the effects of the blood-pressureinterventions were similar in the two diet groups. Thus, theeffects of the dietary interventions were tested by comparingall patients in the two diet groups (including those in bothblood-pressure groups; right column, Table 3 and Table 4), andthe effects of the blood-pressure interventions were testedby comparing all patients in the two blood-pressure groups (includingthose in both diet groups; bottom row, Table 3 and Table 4).
Table 4. Mean Rate of Decline in the Glomerular Filtration Rate from Base Line to the End of the Study in Study 2.
Study 1
The effects of diet and blood pressure on the initial and subsequentrates of decline in the glomerular filtration rate and on theprojected change in the glomerular filtration rate from baseline to three years, according to the two-slope model, are shownin Figure 2 and Figure Figure Table 3. During the first fourmonths, both the low-protein and the low-blood-pressure interventionswere associated with significantly steeper rates of declinein the glomerular filtration rate than were the usual-proteinand usual-blood-pressure interventions (P = 0.004 and P = 0.01,respectively). The mean decline in the glomerular filtrationrate during the first four months was 2.6 ml per minute per1.73 m2 in all groups combined. The change in the glomerularfiltration rate during this interval correlated with the changesin dietary protein intake and blood pressure (data not shown).Subsequently, the rate of decline in the glomerular filtrationrate was 28 percent less in the low-protein group than in theusual-protein group (P = 0.009) and 29 percent less in the low-pressuregroup than in the usual-pressure group (P = 0.006). The averagerate of decline after four months was 3.3 ml per minute peryear in all groups combined.
Figure 2. Estimated Mean (±SE) Decline in the Glomerular Filtration Rate from Base Line (B) to Selected Follow-up Times (F) in Study 1.
The upper panel compares the patients assigned to the usual-protein diet (dashed line) with those assigned to the low-protein diet (solid line). The lower panel compares the patients assigned to the usual-blood-pressure group (dashed line) with those assigned to the low-blood-pressure group (solid line). To correct for any bias introduced by stopping points, the mean declines were estimated by the maximum-likelihood method with a two-slope model for the covariance matrix of the serial measurements of the glomerular filtration rate.
The projected decline in the glomerular filtration rate at threeyears did not differ significantly between the diet groups orthe blood-pressure groups and averaged 11.5 ml per minute forall groups combined (Table 3). The mean decline was 1.2 ml perminute less (95 percent confidence interval, -1.1 to 3.6) inthe low-protein group (P = 0.30) and 1.6 ml per minute less(95 percent confidence interval, -0.8 to 3.9) in the low-pressuregroup (P = 0.18).
The effect of the dietary interventions was not related to age,sex, renal diagnosis, base-line glomerular filtration rate,or urinary protein excretion. However, there was a significantinfluence of the prescribed blood pressure and the degree ofproteinuria during the base-line period (considered on the logscale) on the rate of decline in the glomerular filtration ratebeginning at four months (P = 0.006) and on the projected declinein the rate from base line to three years (P = 0.02). Amongthe 578 patients in study 1 with follow-up measurements of theglomerular filtration rate, the benefit of low blood pressurewas greatest in the 54 patients with urinary protein excretionthat exceeded 3 g per day at base line, the benefit was moderatein the 104 patients with urinary protein excretion of 1 to 3g per day, and there was no benefit in the 420 patients withurinary protein excretion under 1 g per day (Figure 3).
Figure 3. Decline in the Glomerular Filtration Rate (GFR) According to Base-Line Urinary Protein Excretion and Blood-Pressure Group in Studies 1 and 2.
The projected mean (±SE) rate of decline per year in the glomerular filtration rate from base line to three years, based on the two-slope model, is shown for study 1. The mean rate of decline in the glomerular filtration rate per year, estimated from the single-slope informative censoring model, is shown for study 2. The solid and open circles designate the patients with usual and low blood pressure, respectively. The number at the bottom of each panel indicates the total number of patients with follow-up glomerular filtration rate measurements in the two blood-pressure groups combined. A higher level of base-line urinary protein excretion was associated with a more rapid mean decline in the glomerular filtration rate and a larger difference in the mean rate of decline in the glomerular filtration rate between the two blood-pressure groups.
The 53 black patients had a more rapid projected mean declinein the glomerular filtration rate (19 ml per minute over threeyears) than the 525 other patients (11 ml per minute over threeyears, P = 0.02). The projected decline in the glomerular filtrationrate in the black patients assigned to the low-blood-pressuregroup was approximately half that in the black patients in theusual-blood-pressure group (14 vs. 25 ml per minute over threeyears, P = 0.11). The patients with polycystic kidney diseasehad a faster projected decline in the glomerular filtrationrate than the patients with other renal diseases (17 vs. 10ml per minute over three years, P<0.001). However, therewas no benefit of prescribed low blood pressure in the patientswith polycystic kidney disease.
Study 2
The average rate of decline in the glomerular filtration ratedid not differ significantly between the two diet groups orbetween the two blood-pressure groups. When the linear (one-slope)model was used, the overall mean rate of decline in the glomerularfiltration rate was 4.0 ml per minute per year (Table 4). Themean rate of decline was 0.8 ml per minute per year less (95percent confidence interval, -0.1 to 1.8) in the patients onthe very-low-protein diet than in those on the low-protein diet(P = 0.07) and 0.5 ml per minute per year less (95 percent confidenceinterval, -0.4 to 1.4) in the patients with low blood pressurethan in those with usual blood pressure (P = 0.28), representingdecrements in the glomerular filtration rate of 19 percent and12 percent, respectively. There were no significant interactionsbetween base-line demographic characteristics and diet interventions,but there was a significant interaction between base-line urinaryprotein excretion and the blood-pressure interventions (P =0.01) (Figure 3).
Adverse Events
There were no significant differences in the number or causesof deaths or stopping points between the diet and blood-pressuregroups in either study. There were 30 deaths: 15 in study 1(3 percent) and 15 in study 2 (6 percent). Cardiovascular diseasesand cancer accounted for 18 and 5 deaths, respectively. Moststopping points in study 1 were due to a rapidly declining glomerularfiltration rate (60 patients, 10 percent) or end-stage renaldisease (12 patients, 2 percent). In study 2, end-stage renaldisease developed in 94 patients (37 percent). The time to theoccurrence of a rapid decline in the glomerular filtration rate(a stopping point in study 1 only) or end-stage renal diseaseor death (stopping points in studies 1 and 2) did not differsignificantly between the diet groups or the blood-pressuregroups. The cumulative percentage of patients in study 2 whohad end-stage renal disease or died is shown in Figure 4.
Figure 4. The Occurrence of End-Stage Renal Disease (ESRD) or Death in Patients in Study 2.
The upper panel compares the patients assigned to the low-protein diet (solid line) with those assigned to the very-low-protein diet (dashed-and-dotted line) (P = 0.62). The lower panel compares the patients in the usual-blood-pressure group (dashed line) and those in the low-blood-pressure group (solid line) (P = 0.33). The numbers below each panel indicate the total number of patients in the two groups being compared at each base-line (B) or follow-up (F) visit. The relative risk of ESRD or death was 0.93 (95 percent confidence interval, 0.65 to 1.33) for the patients assigned to the very-low-protein diet, as compared with those assigned to the low-protein diet and 0.85 (95 percent confidence interval, 0.60 to 1.22) for the patients in the low-blood-pressure group, as compared with those in the usual-blood-pressure group.
There were small but significant differences between the dietgroups in changes in weight and serum concentrations of albumin,transferrin, and cholesterol (data not shown). Two patients(one from each diet group in study 2) reached a stopping pointbecause of malnutrition related to weight loss. In 10 patients(2 percent) in study 1 and 7 patients (3 percent) in study 2,the blood pressure had to be raised because of persistent symptomsof hypotension. No patient reached a stopping point becauseof complications of hypotension.
Discussion
Two previous studies have examined the effects of a low-proteindiet in nondiabetic patients with glomerular filtration ratesin the range specified for study 15,28. In one study, only serumcreatinine concentrations were reported,5 and in the other,the difference in protein intake between the two diet groupswas small, and there was no beneficial effect28. Study 1 overcomesthese limitations. However, the interpretation of the resultsis complicated by the fact that the rate of decline in the glomerularfiltration rate was slower than expected and not constant.
The glomerular filtration rate has been measured serially innondiabetic patients in a few previous studies. We found thatthe rate declined more rapidly in patients with a higher degreeof proteinuria, in those with polycystic kidney disease, andin blacks. However, the majority of patients had other conditionsand a slower mean decline in the glomerular filtration rate.Given the slow overall rate of decline in our study, a longerfollow-up might have detected a difference in the glomerularfiltration rate between the treatment groups at a later date.
The reason for the differential effect of the low-protein dieton the initial and subsequent rates of decline in the glomerularfiltration rate in study 1 is not known. Similar effects havenot been reported previously in humans and were not observedin our feasibility study14. The steeper initial decline probablyreflects a hemodynamic response to the reduction in proteinintake and blood pressure rather than a progression of renaldisease,29 because the initial decline correlated with the lowerprotein intake and lower blood pressure. The less steep subsequentslopes associated with the low-protein diet in study 1 are consistentwith a small beneficial effect of this intervention on the progressionof renal disease.
For patients with glomerular filtration rates in the range ofthe values specified for study 2 (13 to 24 ml per minute per1.73 m2), most4,5,6,7,10 but not all28 previous studies havesuggested that a low-protein diet is beneficial. Since we didnot include a group of patients on a usual-protein diet, wecannot confirm or refute this conclusion. There was a nonsignificanttrend toward a slower decline in the glomerular filtration ratein the patients on the very-low-protein diet, which is consistentwith a moderate effect of very low protein intake or of theketo acid-amino acid mixture10. Nonetheless, there was no significantdifference between the diet groups in the time to the occurrenceof end-stage renal disease or death.
Few studies have examined the effect of lower-than-usual bloodpressure on the progression of renal disease. Like the low-proteindiet, low blood pressure had different effects on the initialand subsequent rates of decline in the glomerular filtrationrate in study 1. In both studies, patients with a higher degreeof proteinuria had a more rapid decline in the glomerular filtrationrate, and a significant benefit of low blood pressure was apparentat three years (Figure 3). The greater benefit of low bloodpressure in the patients whose urinary protein exceeded 1 gper day suggests that the mechanism of progression is specificto the disease and that different diseases may respond differentlyto the same treatment.
In summary, the dietary and blood-pressure interventions weprescribed were well tolerated. No significant benefit of theseinterventions was demonstrated at the end of follow-up in eitherstudy group, when patients with diverse renal diseases wereconsidered together. However, certain findings may affect thetreatment of some patients with chronic renal disease. Theseinclude a benefit of low blood pressure in patients with urinaryprotein excretion exceeding 1 g per day, a trend toward a greaterbenefit of low blood pressure in blacks with moderate renalinsufficiency (study 1), and a more rapid mean decline in theglomerular filtration rate in patients with polycystic kidneydisease. Because renal diseases can vary in their rate of progressionand their response to treatments, future studies should be performedin patients with specific renal diseases and more rapid declinein the glomerular filtration rate.
Supported by the National Institute of Diabetes and Digestiveand Kidney Diseases and the Health Care Financing Administration.
We are indebted to the patients who participated in the MDRDStudy, to Marion Merrell Dow (Kansas City, Mo.) for the diltiazemand calcium carbonate used in the study, and to Merck and Company(West Point, Pa.) for the enalapril used in the study.
Source Information
From the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Md. (J.W.K., G.S.); Washington University Medical Center, St. Louis (S.K.); New England Medical Center, Boston (A.S.L.); the Cleveland Clinic Foundation, Cleveland (G.J.B.); the University of Pittsburgh, Pittsburgh (A.W.C.); and the University of Iowa Hospitals and Clinics, Iowa City (L.H.). The institutions and investigators participating in the study group are listed in the Appendix.
Address reprint requests to the MDRD Study Data Coordinating Center, Department of Biostatistics and Epidemiology, P88, Cleveland Clinic Foundation, 9500 Euclid Ave., Cleveland, OH 44195.
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Appendix
The following institutions and investigators participated inthe MDRD Study: Bowman Gray School of Medicine -- V. Buckalew,J. Burkart, C. Furberg, J. Felts, M. Moore, M. Rocco, T. Dolecek,S. Warren, B. Bearden, C. Starkey, J. Harvey, D. Poole, S. Dahlquist,L. Doroshenko, K. Bradham, D. West, J. Agostino, L. Cole, B.Baker, K. Hairston, and S. Burgoyne; Brigham and Women's Hospitaland Beth Israel Hospital -- J. Lazarus, T. Steinman, J. Seifter,M. Desmond, M. Fiorenzo, A. Chiavacci, T. Metalides, D. Korzec-Ramirez,S. Gould, and V. Pickett; Brookdale Hospital Medical Center-- J. Porush, P. Faubert, S. Spitalewitz, J. Faubert, G. Zimmer,D. Saum, M. Block, J. Woel, and M. Rose; Duke University Schoolof Medicine -- V. Dennis, S. Schwab, S. Minda, S. Condon, B.Jenks, L. Eckard, and G. Gedon; Emory University -- W. Mitch,B. Maroni, B. England, J. Soucie, M. Pedersen, L. Akpele, P.Callahan, B. Hall, and S. Shelton; George Washington University-- J. Bosch, V. Habwe, B. Culbertson, M. Stack-Dunne, M. Hankey,S. O'Neill, K. Witzmann, C. Goldman, T. Jones, D. Boyle, andL. Salmon; Harbor-UCLA Medical Center -- J. Kopple, S. Adler,R. Hirschberg, J. DiChiro, K. Snider, W. Devine, S. McKay, J.McDonald, J. Carter, and W. Nelson; New England Medical Centerand Massachusetts General Hospital -- A. Levey, C. Coggins,J. Dwyer, M. McLaughlin, J. Gronich, A. King, C. Stollar, D.Raizman, L. Castaldo, D. DeSimone, A. Efstathion, K. Yonker,J. Fine, N. Saul, N. Huggins, A. Martin, S. Baldi, C. Moleske,K. Sheehan, and D. Furlong; Ohio State University -- L. Hebert,N. Nahman, V. Driver, M. Cosio, J. Hartman, C. Levy, D. Londergan,M. Gilligan, T. Beckman, E. Smith, and D. Zachrich; Universityof Florida -- C. Tisher, J. Peterson, C. Wingo, R. Finlay, E.Parris, G. Ivey, P. Gregory, R. Hoffinger, D. Garcia, and C.Preston; University of Iowa Hospitals and Clinics -- L. Hunsicker,J. Bertolatus, V. Lim, L. Snetselaar, B. Welch, L. Brooks, D.Hollinger, I. Lichty, D. Mueller, S. Eastin, A. Tanna, J. Steele,and K. Rieck; University of Miami and Jackson Memorial HospitalMedical Center -- J. Bourgoignie, D. Roth, D. Green, C. Butcher,D. Merrill, A. de Velasco, M. Garcon, C. Rojas, M. Zaragoza,and S. Barton; University of Southern California -- S. Massry,M. Akmal, G. Fadda, M. Smorgorzerski, S. Kiefer, S. Rauch, M.Eyerman, L. Kigawa, and A. Richardson; University of Texas HealthScience Center at San Antonio -- M. Lifschitz, R. Kunau, C.Nolan, S. Gouge, G. Bakris, C. Hura, E. Young, C. Armes, C.Warner, A. Tansey, M. Flores, and C. Delea; Vanderbilt UniversityMedical Center -- P. Teschan, R. Hakim, J. Breyer, G. Schulman,N. Rogers, S. Powers, S. McLeroy, S. Fischer, M. Deere, andE. Cutler; National Institute of Diabetes and Digestive andKidney Diseases -- G. Striker, J. Kusek, and L. Agodoa; HealthCare Financing Administration -- A. Anderson; Steering CommitteeOffice -- S. Klahr and A. Levey; Data Coordinating Center (ClevelandClinic Foundation) -- G. Beck, G. Williams, J. Gassman, T. Greene,M. Schluchter, R. Berg, M. Brown, L. Chu, M. Drabik, K. Fatica,T. Knuth, K. Lambdin, J. Leatherman, J. McPherson, V. Midcalf,B. Moore, L. Paranandi, G. Pearce, D. Swinderman, S. Wang, L.Webb, and K. Yanchar; Nutrition Coordinating Center (Universityof Pittsburgh) -- A. Caggiula, N. Milas, M. Yamamoto, W. Amoroso,F. Averbach, T. Coyne, B. Gillis, F. Jones, E. Maurer, R. Meehan,J. Naujelis, M. Olson, L. Scherch, and E. Stano; Central AminoAcid Laboratory (University of Iowa) -- L. Stegink, M. Brummel,and B. Ludwig; Central Biochemistry Laboratory (Cleveland ClinicFoundation) -- F. Van Lente, J. Waletzky, L. Erdei, C. South,C. Spagnola, and C. O'Laughlin; Central ElectrocardiographyLaboratory (Cleveland Clinic Foundation) -- W. Proudfit andD. Underwood; Central Glomerular Filtration Rate Laboratory(Cleveland Clinic Foundation) -- P. Hall, H. Rolin, and D. Pexa;Drug Distribution Center (Cleveland Clinic Foundation) -- E.Jones and M. Basch; Consultants -- R. Byington, W. Chumlea,G. Dolliff, R. Kaplan, and R. Wing; Executive Advisory Committee-- G. D'Amico, J. Dirks, J. Grantham, A. Harper, K. Peters,J. Stein, E. Pellegrino, and C. van Ypersele; and External MonitoringCommittee -- R. Bain, J. Grizzle, C. Hawkins, M. Holliday, R.Luke, B. Myers, D. Rudman, P. Whelton, D. Young, and V. Young.
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Brosius, F. C. III, Hostetter, T. H., Kelepouris, E., Mitsnefes, M. M., Moe, S. M., Moore, M. A., Pennathur, S., Smith, G. L., Wilson, P. W.F.
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D.C., K., D.F., L., J., W., D., H., X, Y., J., T., K., B., M., S., P., D., R., L., K.H., S., F.C., L., K.-U., E., K.F, H., J., B., S.A., G.
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Berl, T., Hunsicker, L. G., Lewis, J. B., Pfeffer, M. A., Porush, J. G., Rouleau, J.-L., Drury, P. L., Esmatjes, E., Hricik, D., Pohl, M., Raz, I., Vanhille, P., Wiegmann, T. B., Wolfe, B. M., Locatelli, F., Goldhaber, S. Z., Lewis, E. J., for the Collaborative Study Group,
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Zhang, Z., Shahinfar, S., Keane, W. F., Ramjit, D., Dickson, T. Z., Gleim, G. W., Mogensen, C. E., de Zeeuw, D., Brenner, B. M., Snapinn, S. M.
(2005). Importance of Baseline Distribution of Proteinuria in Renal Outcomes Trials: Lessons from the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) Study. J. Am. Soc. Nephrol.
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Rahman, M., Pressel, S., Davis, B. R., Nwachuku, C., Wright, J. T. Jr, Whelton, P. K., Barzilay, J., Batuman, V., Eckfeldt, J. H., Farber, M., Henriquez, M., Kopyt, N., Louis, G. T., Saklayen, M., Stanford, C., Walworth, C., Ward, H., Wiegmann, T., for the ALLHAT Collaborative Research Group,
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Lewis, J., Greene, T., Appel, L., Contreras, G., Douglas, J., Lash, J., Toto, R., Van Lente, F., Wang, X., Wright, J. T. Jr., for the AASK Study Group,
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Jafar, T. H., Stark, P. C., Schmid, C. H., Landa, M., Maschio, G., de Jong, P. E., de Zeeuw, D., Shahinfar, S., Toto, R., Levey, A. S., for the AIPRD Study Group*,
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