CKD affects about 1 in 10 adults and is associated with increased risks of cardiovascular disease, ESRD, and death.1 Only a minority of patients with CKD will progress to ESRD (because most patients will die first), but the substantially elevated risks of morbidity and mortality associated with ESRD,2 together with its effects on quality of life3 and cost to health care systems,4 make its prevention highly desirable. Although inhibition of the renin-angiotensin system does slow progression of proteinuric nephropathies,5,6 there is a need for additional therapies that safely retard the progression of CKD.
Experimental studies have suggested that lipids may contribute to the progression of kidney disease.7 Previous meta-analyses of randomized trials (which included patients without CKD and with mild reductions in eGFR) have indicated that lowering LDL cholesterol might reduce the rate of loss of glomerular filtration by about 1 ml/min per year.8,9 However, those trials did not include patients with advanced CKD (i.e., stage 3B and higher), who typically progress at a faster rate than those patients at earlier stages, among whom a similar proportional effect might yield a worthwhile delay in ESRD.
The Study of Heart and Renal Protection (SHARP) showed that lowering LDL cholesterol with simvastatin (20 mg) plus ezetimibe (10 mg) daily in patients with CKD safely reduces the incidence of major atherosclerotic events10 and provides an opportunity to assess the effects of lowering LDL cholesterol on the progression of kidney disease.
Results
In total, 6245 participants were not on dialysis at the point at which they were randomized to simvastatin plus ezetimibe versus placebo (Figure 1). This group included 10 patients (5 patients allocated simvastatin plus ezetimibe, and 5 patients allocated placebo) who were initially randomized to simvastatin only and received a kidney transplant before rerandomization to simvastatin plus ezetimibe versus placebo (but excludes 2 patients who were identified, after publication of the main trial results,10 as being on dialysis before rerandomization). Among all 6245 patients, baseline characteristics were well balanced between randomized treatments (Table 1, Supplemental Table 1). Among 6027 (97%) patients with centrally measured creatinine, the mean eGFR was 27 (SD=13) ml/min per 1.73 m2, with 3784 (63%) patients having stages 4 or 5 CKD (i.e., eGFR<30 ml/min per 1.73 m2). Among 5572 (89%) patients with a centrally measured urinary albumin-to-creatinine ratio (ACR), 2357 (42%) patients had macroalbuminuria (ACR>34 mg/mmol). The most common causes of kidney disease were hypertensive nephropathy or renovascular disease (22%), GN (18%), diabetic nephropathy (15%), and cystic kidney disease (11%).
Figure 1: Trial profile and participant flow diagram.
Table 1: Baseline characteristics by treatment allocation among 6245 patients not on dialysis at randomization
Among surviving patients, the median duration of follow-up was 4.8 years. Compliance was defined as at least 80% of the scheduled simvastatin plus ezetimibe or placebo tablets having been taken since the previous follow-up. At the study midpoint, 2038 (73%) patients allocated simvastatin plus ezetimibe remained compliant or were taking a nonstudy statin, whereas 215 (8%) patients allocated placebo were taking a nonstudy statin (Table 2). Hence, the average difference between the two randomized arms in the proportion taking simvastatin plus ezetimibe or nonstudy statin was 65%. The average LDL cholesterol difference at the same point was 0.96 (SEM=0.02) mmol/L.
Table 2: Average use of study simvastatin plus ezetimibe or nonstudy statin among 6245 patients not on dialysis at randomization and average change in plasma LDL cholesterol from baseline by period of follow-up
During the follow-up period, 1057 (33.9%) participants allocated simvastatin plus ezetimibe reached ESRD compared with 1084 (34.6%) patients allocated placebo (rate ratio [RR], 0.97; 95% confidence interval [95% CI], 0.89 to 1.05; P=0.41) (Figure 2). Allocation to simvastatin plus ezetimibe was not associated with a significant reduction in the risk of either of the prespecified subsidiary renal outcomes: ESRD or death from any cause (RR, 0.97; 95% CI, 0.90 to 1.04; P=0.34) or ESRD or doubling of baseline creatinine (RR, 0.93; 95% CI, 0.86 to 1.01; P=0.09).
Figure 2: Effects of allocation to simvastatin plus ezetimibe on renal outcomes among 6245 patients not on dialysis at randomization.
SHARP was not expected to have sufficient statistical power to allow reliable estimation of effects of treatment in particular clinical circumstances, and therefore, subgroup analyses were planned only as tertiary assessments.11 There was no evidence that the proportional effect of allocation to simvastatin plus ezetimibe on ESRD (or the other renal outcomes) differed between participants with different stages of CKD (Figure 3, Supplemental Figures 1 and 2) or among subgroups of participants defined by a range of other baseline characteristics after accounting for multiple testing (Supplemental Figures 1–4).
Figure 3: Effects of allocation to simvastatin plus ezetimibe on ESRD by baseline eGFR among 6245 patients not on dialysis at randomization. MDRD, Modification of Diet in Renal Disease.
In total, 5037 (80%) participants had at least three follow-up local creatinine measurements in addition to a centrally measured creatinine at randomization. The 50 (1%) patients with the most extreme mean deviations from their own fitted slopes were excluded (Table 3). Of the remaining 4987 patients, the median number of creatinine measurements per patient was 10 (interquartile range=7–12). Those patients with fewer measurements had lower eGFR at baseline and a faster average rate of decline in eGFR (Supplemental Figure 5, Supplemental Table 2). When participants were subdivided by their number of follow-up measurements, eGFR declined in a clearly linear fashion in every group (Supplemental Figure 5). Overall, allocation to simvastatin plus ezetimibe was not associated with a slower rate of change in eGFR (−1.66 [SEM=0.07] versus −1.83 [SEM=0.07]; absolute difference=0.17 [SEM=0.10] ml/min per 1.73 m2 per year; P=0.10) (Table 3). In sensitivity analyses, the estimated difference in the rate of change in eGFR between treatment arms (and its SEM) was virtually identical when alternative approaches to excluding patients with poorly fitting slopes were used (Table 3). Although those patients with more advanced CKD (whether characterized by lower eGFR or greater albuminuria) had faster rates of progression, there were no trends to suggest any benefit (or hazard) of treatment on the rate of change in eGFR across these subgroups (Figure 4) or any other subgroups (data not shown). In addition, among 3625 patients with centrally analyzed cystatin C at the 2.5-year visit (who had not reached ESRD by that time), there was no significant difference in cystatin C eGFR between patients allocated simvastatin plus ezetimibe and patients allocated placebo.
Table 3: Effect of allocation to simvastatin plus ezetimibe on annual reduction in eGFR among 5037 patients not on dialysis at randomization with at least three follow-up eGFRs
Figure 4: Effect of allocation to simvastatin plus ezetimibe on rate of change in eGFR among 5037 patients not on dialysis at randomization with at least three follow-up eGFRs by baseline (A) eGFR and (B) albuminuria.
Exploratory analyses of effects of treatment on proteinuria and acute-on-chronic renal failure were also undertaken. Among 3022 patients who had not commenced dialysis and had provided a urine sample at the study midpoint, there was no significant difference in geometric mean urinary ACR (simvastatin plus ezetimibe versus placebo: 168 [SEM=8.4] mg/g versus 154 [SEM=7.7] mg/g; P=0.20). Allocation to simvastatin plus ezetimibe was not associated with a reduction in the risk of acute-on-chronic renal failure (209 [6.7%] versus 231 [7.4%]; RR, 0.91; 95% CI, 0.75 to 1.09; P=0.30).
Discussion
Among 6245 participants with CKD not on dialysis at randomization, lowering LDL cholesterol by about 1 mmol/L with simvastatin plus ezetimibe for about 5 years had no significant effect on the progression of kidney disease to ESRD or the subsidiary prespecified outcomes of ESRD or death from any cause, or ESRD or doubling of baseline creatinine. These findings are supported by the absence of a significant effect on the statistically more sensitive rate of decline of eGFR. Subgroup analyses did not identify any particular type of participant who seemed to benefit more (or less) compared with the overall result.
SHARP is the largest trial of LDL lowering in patients with advanced CKD. With over 2000 ESRD events, it had excellent statistical power (>90%) to detect a 15% proportional reduction and good power (>80%) to detect a more moderate 10% reduction in the incidence of ESRD. These data, therefore, are the most robust data available to assess whether lowering LDL cholesterol preserves kidney function. SHARP was not, however, designed to compare the effects of lowering LDL cholesterol with simvastatin with the effects of lowering LDL cholesterol with simvastatin plus ezetimibe (and had insufficient statistical power to do so reliably).
In SHARP, nearly one half of those patients reaching ESRD had an eGFR below 15 ml/min per 1.73 m2 at randomization, and the median time to ESRD for such patients was only about 1 year. Therefore, any effect of LDL cholesterol reduction on the pathophysiology of renal progression would have had little time to manifest among such patients. It is known that the benefits of statins in preventing cardiovascular disease are proportionally lower during the first year of starting treatment,12 and, therefore, if the mechanism of action was similar (as suggested by laboratory experiments7), then many of the ESRD events in SHARP may not have been modifiable by the study treatment. However, there was no significant trend in treatment effect by CKD stage at baseline.
SHARP participants were also recruited from countries with a spectrum of health care provision and, in particular, substantial variation in the incidence of RRT.13 Some participants who died of renal disease might conceivably have been offered RRT if their health care had been managed elsewhere. However, of 6245 patients at risk of ESRD, only 134 (2%) patients died of renal disease before reaching ESRD, and no effect of treatment was shown on the outcome of ESRD or death.
These factors are not likely to have affected statistically more sensitive assessments of the rate of change of eGFR. In SHARP, allocation to simvastatin plus ezetimibe resulted in a nonsignificant 0.17 (SEM=0.10) ml/min per 1.73 m2 per year reduction in the rate of change in eGFR. This result is not consistent with the 1.22 (95% CI, 0.44 to 2.00 ml/min per year) estimate from a previous meta-analysis of much smaller randomized trials9 (but it is compatible with a smaller effect). Although a variety of assays may have been used to measure creatinine at local sites and such assays may have changed during the trial, randomization would have balanced any differences (as well as the myriad factors known to affect the reliability of equations used to estimate GFR), minimizing any resulting bias.14
In clinical practice, an individual’s eGFRs may not change in a linear fashion over time.15 An assessment of the effect of treatment on the average rate of decline in eGFR might be misleading if eGFR varied in a definitely nonlinear fashion. However, there was little evidence of this in SHARP: when patients were stratified by the number of creatinine measurements obtained during the study, strong linear relationships with increasing follow-up were seen for both treatment groups in every group.
SHARP has shown that lowering LDL cholesterol in patients with CKD reduces their substantially elevated cardiovascular risk, and, therefore, there is already a good indication for lowering LDL cholesterol in most patients with CKD (regardless of stage). The lack of a significant benefit on renal progression does not influence this strategy, and the lack of hazard is reassuring. Consequently, LDL cholesterol–lowering therapy is indicated in patients with advanced CKD to prevent atherosclerotic disease but not progression of renal disease.
Concise Methods
Trial Design and Participants
The study objectives, design, and methods have been reported previously.10,11 Patients ages 40 years or older were eligible to participate if they had CKD with more than one previous measurement of serum or plasma creatinine of at least 150 μmol/L (1.7 mg/dl) in men or 130 μmol/L (1.5 mg/dl) in women, regardless of dialysis use. Patients attended a screening visit, at which time medical history and other eligibility criteria were checked and written informed consent was obtained. The study is registered at ClinicalTrials.gov (NCT00125593 and ISRCTN54137607). Ethics approval was obtained at all study sites before enrolment.
After 6 weeks of placebo run-in, eligible participants were randomized in the ratio of 4:4:1 to simvastatin (20 mg) plus ezetimibe (10 mg; as a single tablet) versus matching placebo versus simvastatin (20 mg) alone, and treatment allocation was masked using a double dummy method. Those patients allocated simvastatin alone (who were alive and willing to continue) were rerandomized after 1 year to one of two main comparison arms (Figure 1). After initial randomization, participants were followed up in study clinics at 2 and 6 months and then, every 6 months for at least 4 years. At each of these visits, information on RRT and all serious adverse events was recorded, and blood samples were taken for serum or plasma creatinine measurement in the site’s local routine laboratory. Samples of nonfasting blood (and urine from those patients not on dialysis) for central laboratory measurement were also collected from all participants at randomization and 2.5 years and about 10% of participants attending study visits at 1 and 4 years after the initial randomization. These blood samples were cooled, spun, and separated before being stored locally at −40°C. Samples were then shipped on dry ice to the central laboratory in Oxford, United Kingdom, where assays of lipids, creatinine, cystatin C, and urinary ACR were conducted. Creatinine, albumin, and lipids were measured using a Synchron LX20 or DXC800 analyzer (Beckman Coulter), whereas cystatin C was measured by immunonephelometry using a Dade Behring BNII nephelometer (Siemens AG). Creatinine was assayed using a kinetic alkaline picrate method and calibrated using material traceable to National Institute of Standards and Technology Standard Reference Material 914a, with a mean expanded uncertainty of 13.4% (7.3% excluding biologic variation).
Statistical Analyses
The main prespecified renal outcome was ESRD, defined as the initiation of maintenance dialysis or kidney transplantation.11 Prespecified subsidiary renal outcomes included the composite outcomes ESRD or death from any cause and ESRD or doubling of baseline creatinine. It was also prespecified that the effect of simvastatin plus ezetimibe on the rate of change in eGFR would be explored. Acute-on-chronic renal failure was reported by investigators as a serious adverse event and not a prespecified outcome.
Analyses were from time of randomization to initiation of simvastatin plus ezetimibe or placebo, such that for those patients initially allocated simvastatin (20 mg) daily, events occurring before rerandomization were used only to update baseline characteristics. All analyses were done according to the intention to treat principle.
eGFR was calculated using the four-variable Modification of Diet in Renal Disease study equation.16 For each patient, linear regression was used to estimate the rate of change in eGFR from the locally measured creatinine values (ignoring measurements after ESRD). The validity of making such a linearity assumption was assessed graphically. Because the reliability of such estimated progression rates is affected by the number of available creatinine measurements (with fewer creatinine measurements resulting in less reliable estimates of the true progression rate), participants with fewer than three follow-up creatinine measurements were excluded. In addition, participants with the mean deviation from their own fitted slope in the top 1% of the distribution (of mean deviations across all participants) were also excluded. The mean rate of change in eGFR was then compared between participants allocated simvastatin plus ezetimibe and participants allocated placebo (both overall and in particular patient subgroups). Sensitivity analyses were conducted to assess the extent that the results varied if different criteria were used for exclusion of estimated eGFR slopes and separately using the Chronic Kidney Disease Epidemiology Collaboration equation.17 Analyses were performed using SAS version 9 (Cary Institute) and R version 2.11.1 (www.R-project.org).
Disclosures
The Study of Heart and Renal Protection (SHARP) was initiated, conducted, and interpreted independently of the principal study funder (Merck/Schering-Plough Pharmaceuticals). The Clinical Trial Service Unit and Epidemiological Studies Unit, which are part of the University of Oxford, have a staff policy of not accepting honoraria or consultancy fees.
The most important acknowledgement is to the participants in the Study of Heart and Renal Protection (SHARP) and the local clinical centre staff, regional and national coordinators, steering committee, and data monitoring committee.
The study was funded by Merck/Schering-Plough Pharmaceuticals, with additional support from the Australian National Health and Medical Research Council, the British Heart Foundation, and the UK Medical Research Council.
The main funding source (Merck/Schering-Plough Pharmaceuticals) participated in initial discussions about trial design, contributed two nonvoting observers to the steering committee, and had a right to comment on (but not require changes to) study reports. It had no involvement in data collection, analysis, interpretation, report writing, or decision to submit for publication, and it has not received an unmasked copy of the trial database. The writing committee accepts full responsibility for the content of this paper. All members contributed to the collection and analysis of the data and the preparation of the manuscript. All collaborators had an opportunity to contribute to the interpretation of the results and the drafting of the manuscript.
The SHARP Steering Committee is Colin Baigent (University of Oxford), Martin J. Landray (University of Oxford), Christina Reith (University of Oxford), Jonathan Emberson (University of Oxford), David C. Wheeler (University College London), Charles Tomson (North Bristol NHS Trust), Christoph Wanner (University of Wuerzburg), Vera Krane (University of Wuerzburg), Alan Cass (Charles Darwin University), Jonathan Craig (University of Sydney), Bruce Neal (University of Sydney), Lixin Jiang (Chinese Academy of Medical Sciences and Peking Union Medical College), Lai Seong Hooi (Sultanah Aminah Hospital), Adeera Levin (University of British Columbia), Lawrence Agodoa (National Institutes of Health), Mike Gaziano (Harvard Medical School), Bertram Kasiske (University of Minnesota), Rob Walker (University of Otago), Ziad A. Massy (University of Picardie Jules Verne), Bo Feldt-Rasmussen (University of Copenhagen), Udom Krairittichai (Rajavithi Hospital), Vuddidhej Ophascharoensuk (Chiang Mai University), Bengt Fellström (University Hospital), Hallvard Holdaas (Oslo University Hospital), Vladimir Tesar (Charles University), Andrzej Wiecek (Medical University of Silesia), Diederick Grobbee (University Medical Center Utrecht), Dick de Zeeuw (University Medical Centre Groningen), Carola Grönhagen-Riska (Helsinki University Hospital), Tanaji Dasgupta (Oxford University Hospitals NHS Trust), David Lewis (University of Oxford), Will Herrington (University of Oxford), Marion Mafham (University of Oxford), William Majoni (Royal Darwin Hospital), Karl Wallendszus (University of Oxford), Richard Grimm (University of Minnesota), Terje Pedersen (Oslo University Hospital Ulleval), Jonathan Tobert (Tobert Medical Consulting LLC), Jane Armitage (University of Oxford), Alex Baxter (University of Oxford), Christopher Bray (University of Oxford), Yiping Chen (University of Oxford), Zhengming Chen (University of Oxford), Michael Hill (University of Oxford), Carol Knott (University of Oxford), Sarah Parish (University of Oxford), David Simpson (University of Oxford), Peter Sleight (University of Oxford), Alan Young (University of Oxford), and Rory Collins (University of Oxford).
Published online ahead of print. Publication date available at www.jasn.org.
This article contains supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2013090965/-/DCSupplemental.
References
1. Levey AS, Coresh J: Chronic kidney disease. Lancet 379: 165–180, 2012
2. Foley RN, Parfrey PS, Sarnak MJ: Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis 32[Suppl 3]: S112–S119, 1998
3. Evans RW, Manninen DL, Garrison LP Jr., Hart LG, Blagg CR, Gutman RA, Hull AR, Lowrie EG: The quality of life of patients with end-stage renal disease. N Engl J Med 312: 553–559, 1985
4. US Renal Data System: 2010 Annual Data Report: Atlas of Chronic Kidney Disease. Costs of End-Stage Renal Disease, 2010. Available at:
http://www.usrds.org/2010/pdf/v2_11.pdf. Accessed June 18, 2013
5. Jafar TH, Schmid CH, Landa M, Giatras I, Toto R, Remuzzi G, Maschio G, Brenner BM, Kamper A, Zucchelli P, Becker G, Himmelmann A, Bannister K, Landais P, Shahinfar S, de Jong PE, de Zeeuw D, Lau J, Levey AS: Angiotensin-converting enzyme inhibitors and progression of nondiabetic renal disease. A meta-analysis of patient-level data. Ann Intern Med 135: 73–87, 2001
6. Lewis EJ, Hunsicker LG, Clarke WR, Berl T, Pohl MA, Lewis JB, Ritz E, Atkins RC, Rohde R, Raz ICollaborative Study Group: Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 345: 851–860, 2001
7. Moorhead JF, Chan MK, El-Nahas M, Varghese Z: Lipid nephrotoxicity in chronic progressive glomerular and tubulo-interstitial disease. Lancet 2: 1309–1311, 1982
8. Tonelli M, Isles C, Craven T, Tonkin A, Pfeffer MA, Shepherd J, Sacks FM, Furberg C, Cobbe SM, Simes J, West M, Packard C, Curhan GC: Effect of pravastatin on rate of kidney function loss in people with or at risk for coronary disease. Circulation 112: 171–178, 2005
9. Sandhu S, Wiebe N, Fried LF, Tonelli M: Statins for improving renal outcomes: A meta-analysis. J Am Soc Nephrol 17: 2006–2016, 2006
10. Baigent C, Landray MJ, Reith C, Emberson J, Wheeler DC, Tomson C, Wanner C, Krane V, Cass A, Craig J, Neal B, Jiang L, Hooi LS, Levin A, Agodoa L, Gaziano M, Kasiske B, Walker R, Massy ZA, Feldt-Rasmussen B, Krairittichai U, Ophascharoensuk V, Fellström B, Holdaas H, Tesar V, Wiecek A, Grobbee D, de Zeeuw D, Grönhagen-Riska C, Dasgupta T, Lewis D, Herrington W, Mafham M, Majoni W, Wallendszus K, Grimm R, Pedersen T, Tobert J, Armitage J, Baxter A, Bray C, Chen Y, Chen Z, Hill M, Knott C, Parish S, Simpson D, Sleight P, Young A, Collins RSHARP Investigators: The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): A randomised placebo-controlled trial. Lancet 377: 2181–2192, 2011
11. Sharp Collaborative Group: Study of Heart and Renal Protection (SHARP): Randomized trial to assess the effects of lowering low-density lipoprotein cholesterol among 9,438 patients with chronic kidney disease. Am Heart J 160: 785–794, e10, 2010
12. Baigent C, Blackwell L, Emberson J, Holland LE, Reith C, Bhala N, Peto R, Barnes EH, Keech A, Simes J, Collins RCholesterol Treatment Trialists’ (CTT) Collaboration: Efficacy and safety of more intensive lowering of LDL cholesterol: A meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet 376: 1670–1681, 2010
13. Jha V, Garcia-Garcia G, Iseki K, Li Z, Naicker S, Plattner B, Saran R, Wang AY, Yang CW: Chronic kidney disease: Global dimension and perspectives. Lancet 382: 260–272, 2013
14. Stevens LA, Coresh J, Greene T, Levey AS: Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 354: 2473–2483, 2006
15. Li L, Astor BC, Lewis J, Hu B, Appel LJ, Lipkowitz MS, Toto RD, Wang X, Wright JT Jr., Greene TH: Longitudinal progression trajectory of GFR among patients with CKD. Am J Kidney Dis 59: 504–512, 2012
16. Levey AS, Greene T, Kusek JW, Beck GJMDRD Study Group: A simplified equation to predict glomerular filtration rate from serum creatinine [Abstract]. J Am Soc Nephrol 11: 155A, 2000
17. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh JCKD-EPI (Chronic Kidney Disease Epidemiology Collaboration): A new equation to estimate glomerular filtration rate. Ann Intern Med 150: 604–612, 2009