Secondary Logo

Journal Logo

Doubling of Serum Creatinine in Clinical Trials, Cost-Effectiveness Studies, and Individual Patients: Adequate Use in Renal Transplantation

Gatault, Philippe1,2; Al-Najjar, Azmi1; Barbet, Christelle1; Roland, Mélanie1; Laouad, Inass1; Buchler, Matthias1,2; Marlière, Jean-Frédéric1; Métais, Pierre Emmanuel3; Clément, Alice3; Nivet, Hubert1,2; Lebranchu, Yvon1,2; Halimi, Jean-Michel1,2,4

doi: 10.1097/TP.0b013e31823015e4
Clinical and Translational Research
Free

Background. The predictive value of doubling of serum creatinine (DSC) has never been assessed in renal transplantation. We evaluated it in terms of its use for clinical trials, cost-effectiveness studies, and individual patients.

Methods. Retrospective longitudinal study in 896 renal transplant recipients.

Results. Death-censored graft loss occurred in 133 patients, during follow-up (up to 21 years). DSC was a risk factor for graft loss; however, the relative risk was different in patients with glomerular filtration rate less than 40 vs. more than or equal to 40 mL/min (hazard ratio: 14.5 [95% confidence interval: 7.4–28.4] vs. 47.8 [28.4–80.6], P=0.0051). Parameters influencing creatinine value (weight, age, sex) did not modify DSC's predictive value. The use of the composite endpoint DSC or death-censored graft loss instead of death-censored graft loss alone in clinical trials would reduce sample size by 7.1% to 9.0%. The annual probability of DSC to graft loss transition decreased from 76% (follow-up <1 year) to 5% (follow-up ≥10 years). Median graft half-life after DSC was 10 months [95% confidence interval: 6–18] but varied with increasing time to DSC (<1 year: 1 month [0.5–6]; 3–4.9 years: 15 months 5/67) and reference creatinine (<130 μmol/L: 3 months 2/6); ≥130 μmol/L: 25 months 15/37).

Conclusions. DSC may be adequately used to refine the risk of death-censored graft loss for individual patients. However, the use of DSC as an endpoint in clinical trials marginally affects sample size, and the probability of DSC to graft loss transition is not constant, which limits the use of DSC in cost-effectiveness analyses of renal transplantation.

1 Service de Néphrologie-Immunologie Clinique, Hôpital Bretonneau, CHRU Tours, France.

2 EA 4245, François Rabelais University, Tours, France.

3 Pharmacie, Hôpital Bretonneau, CHRU Tours, France.

The authors declare no funding or conflicts of interest.

4 Address correspondence to: Jean-Michel Halimi, M.D., Ph.D., Service de Néphrologie-Immunologie Clinique, Hôpital Bretonneau, 2, Bd Tonnellé 37044 Tours Cedex, France.

E-mail: halimi@med.univ-tours.fr

G.P., A.-N.A., B.C., L.I., M.J.-F., M.P.E., and C.A. reviewed the patients' files manually. G.P., H.J.-M., R.M., B.M., N.H., and L.Y. participated in data analysis. G.P. and H.J.-M. participated in the writing of the manuscript.

Received 11 April 2011. Revision requested 28 April 2011.

Accepted 27 July 2011.

Doubling of serum creatinine (DSC) is one of the most popular surrogate markers of end-stage renal disease (ESRD) in clinical trials of nephrology, diabetes mellitus, and cardiovascular diseases (1–4). Clinical trials involving DSC are attractive because they are smaller, shorter, and less expensive than studies with hard endpoints (5). Cost-effectiveness studies involving DSC are based on the calculation of the long-term ESRD risk by Markov's models, assuming that the long-term annual probability of DSC to ESRD transition is constant and can be estimated by data from short-term clinical trials (6–8).

DSC is now increasingly used in clinical trials and epidemiological studies of renal transplantation (9–14). However, DSC has not been formally validated as a surrogate marker of death-censored graft loss in renal transplantation. First, the sample size reduction with the use of DSC in addition to death-censored graft loss (as compared with death-censored graft loss alone) should be quantified as an endpoint in clinical trials. Second, whether the long-term annual probability of DSC to graft loss transition is fixed should be verified; if it is not verified, DSC should not be used for cost-effectiveness analyses of renal transplantation. Third, and most importantly, whether DSC can be used for individual patients is unclear: patients wish to obtain quantitative information about the survival of their graft after DSC, but this information may depend on various parameters and so far is lacking. Therefore, how graft survival is modified by DSC must be determined to refine the risk of graft loss and prepare the patient with failing grafts for dialysis or retransplantation.

In the present large, long-term retrospective study of renal transplant recipients, we assessed sample size reduction with the use of DSC in clinical trials, and the long-term annual probability of DSC to death-censored graft loss transition for cost-effectiveness analysis, and provide practical information regarding DSC for patients and physicians.

Back to Top | Article Outline

RESULTS

Baseline Characteristics

As shown in Table 1, the mean patient age was 45.8±13.4 years, 61.1% of patients were male and almost all were whites. The graft was the first for 89.1% of patients. Donor age was 42.2±15.4 years, and the cause of death was cardiovascular in 53.4%.

TABLE 1

TABLE 1

At 3 months after transplantation, serum creatinine value (used as the reference value) was 132.1±46.4 μmol/L, estimated glomerular filtration rate (eGFR) level was 40±19 mL/min/1.73 m2 and mean proteinuria was 0.3±0.9 g/day. Acute rejection occurred in 28.8% of patients.

The median follow-up was 6.3 years (range, 0.3–21.2 years; total observation period: 6656 patient-years). Among the 896 patients with a functioning graft at 3 months, the death-censored renal survival was 91.3%, 82.1%, and 63.2% at 5, 10, and 20 years, respectively.

Back to Top | Article Outline

DSC as a Surrogate Marker of Graft Loss

Global Analysis

Death-censored graft loss occurred in 133 patients during follow-up. The cause of graft loss was chronic allograft rejection in most patients. Among these 133 patients, graft loss was preceded by DSC in 105 patients (79%). Overall, 79 patients died during follow-up.

As shown in Table 2, the sensitivity of DSC was low, even when follow-up was long. These findings remained unchanged when the 12-month serum creatinine value was chosen as the reference value (instead of the 3-month serum creatinine value) (Table 2). As expected, specificity was excellent, regardless of duration of follow-up.

TABLE 2

TABLE 2

Unsurprisingly, DSC was a potent predictor of death-censored graft loss (hazard ratio [HR] of DSC vs. no DSC during follow-up): 25.5 [95% confidence interval {CI}: 16.8–38.8], P<0.0001). DSC remained a risk factor of death- censored graft loss even when the 3-month serum creatinine value (HR: 31.6 [20.2–49.4], P<0.0001 vs. no DSC), the change in serum creatinine from 3 to 12 months (HR: 25.4 [15.9–40.6], P<0.0001 vs. no DSC) or acute rejection (HR: 25.4 [15.9–40.6], P<0.0001 vs. no DSC) were included in the models.

Of note, the relative risk of death-censored graft loss associated with DSC was qualitatively unchanged after adjustment for variables influencing creatinine level such as body mass index (HR for DSC vs. no DSC: 28.4 [17.5–46.2]), age (27.1 [17.7–41.4]), and sex (25.6 [16.8–38.9]).

When the 12-month serum creatinine value was chosen as the reference value (instead of the 3-month serum creatinine value), the relative risk of graft loss was elevated (HR: 18.0 [12.1–26.6], P<0.0001 vs. no DSC). Of note, in the 879 patients with a functioning graft at 12 months, serum creatinine was comparable at 3 months and 12 months after transplantation (130±42 vs. 129±44 μmol/L, respectively; difference: −1±33 μmol/L, P=0.4580).

Back to Top | Article Outline

DSC Predictive Value: Influence of Time From Transplantation to the Date of DSC (Time to DSC) and Baseline Renal Function

Among patients in whom DSC occurred, the median time from transplantation to DSC was 4.7 years (range, 0.3–18.4 years).

The predictive value of DSC varied by time to DSC. When DSC occurred 3 months to 1 year after transplantation, the HR was 65.8 ([35.7–121.4], P<0.0001) and 14.6 [8.5–25.2] when DSC occurred within 3 to 4.9 years after transplantation (Table 3). The relative risk of death-censored graft loss associated with DSC was lower for patients with baseline eGFR level less than 40 mL/min/1.73 m2 than in those with eGFR level more than or equal to 40 mL/min/1.73 m2 (HR for DSC vs. no DSC: 14.5 [7.4–28.4] vs. 47.8 [28.4–80.6], difference in HR: P=0.0051). The results were qualitatively unchanged when renal function was expressed in terms of serum creatinine level (Table 3).

TABLE 3

TABLE 3

DSC is a surrogate endpoint of death-censored graft loss, not a surrogate endpoint of death; however, as shown in Table 3, DSC remained a risk factor for death-uncensored graft loss in our population.

When the 12-month serum creatinine value was chosen as the reference value, the relative risk of death-censored graft loss associated with DSC was 27.7 [15.0–51.1] (P<0.0001 vs. no DSC) among patients with creatinine less than or equal to 130 μmol/L, and 11.6 [6.9–19.6] (P<0.0001 vs. no DSC) among those with creatinine more than 130 μmol/L.

Back to Top | Article Outline

DSC as an Endpoint in Clinical Trials: Impact on Sample Size Calculation

From the observed incidence of graft loss and DSC in our cohort of patients with functioning grafts at 3 months after transplantation, we calculated the sample size that would be needed for studies of renal transplantation (with alpha error=0.05, beta error: 0.20; effect of intervention: −30%) using DSC or graft loss as the endpoint (as compared with graft loss alone) (Table 4). The number of patients to include would be reduced by only 7.1% with DSC or death-censored graft loss used as an endpoint instead of death- censored graft loss alone in 5-year trials. The sample size reduction would be similar in shorter or longer trials, and it would be smaller using death-uncensored graft loss (Table 4).

TABLE 4

TABLE 4

Back to Top | Article Outline

Transition Probability From DSC to Death-Censored Graft Loss

The annual probability of DSC to graft loss transition diminished sharply with increasing time to DSC, from 0.76 (time to DSC <1 year), 0.29 (1–2.9 years), 0.13 (3–4.9 years), 0.09 (5–9.9) to 0.05 (≥10 years): graft loss occurred each year in 76% of patients when DSC was observed during the first year after transplantation but only in 5% of patients when DSC occurred 10 years or more after transplantation. So, the long-term transition probability cannot be extrapolated from short-term studies of renal transplantation.

Back to Top | Article Outline

Renal Outcome After DSC: Practical Information

Overall, the median graft half-life after DSC was 10 months (95% CI: 6–18 months) (Table 5). However, the duration of graft survival after DSC was extremely long for some patients. In effect, median graft half-life varied, from 1 month (0.5–6 months) if DSC occurred within the first year after transplantation, to 23 months (13–48 months) if DSC occurred 5 to 9.9 years after transplantation. Graft survival after DSC also depended on initial renal function (from 3 [2–6] months after DSC with serum creatinine level <130 μmol/L to 25 [15–37] months otherwise) (Table 5).

TABLE 5

TABLE 5

Back to Top | Article Outline

DISCUSSION

DSC is increasingly used in clinical trials and cost- effectiveness and epidemiological studies of renal transplant recipients but has not been formally validated as a surrogate marker of death-censored graft loss in renal transplantation. In the present study, we assessed the predictive value of DSC in renal transplantation. The sensitivity of DSC to predict ESRD was poor even with a long follow-up, and its positive predictive value was profoundly modified by time to DSC (i.e., duration of follow-up) and reference renal function. Using the composite endpoint, DSC or graft loss would marginally reduce the sample size in clinical trials of renal transplantation. The annual probability of DSC to graft loss transition diminished sharply with increasing duration of follow-up. Graft half-life was 1 month when DSC occurred early after transplantation but was much longer later on; it also depended on initial renal function.

The sensitivity of DSC was poor, even with up to 5 years' follow-up. Unfortunately, the duration of most clinical trials involving DSC was less than 3 years in 11 clinical trials included in a meta-analysis focused on the rate of progression of renal disease in nontransplanted patients; it can be as short as 2 years or even 1 year in some studies (15–18). The sensitivity of DSC in such trials is probably low. However, we observed that the relative risk of graft loss decreased with increasing time to DSC, so the relationship between DSC and graft loss is less strong with a long follow-up. Our results strongly suggest that the results of clinical trials involving DSC should be interpreted with caution, regardless of the duration of follow-up. Of note, duration of follow-up was less than 5 years in some clinical trials of renal transplantation involving DSC (10).

The annual probability of DSC to graft loss transition diminished sharply with increasing duration of follow-up: ESRD was 15 times less likely to occur with time to DSC more than or equal to 10 years than with time to DSC less than 1 year. Interestingly, most (6–8) if not all (19) cost-effectiveness studies are based on the calculation of the long-term ESRD risk, assuming that the long-term annual probability of DSC to ESRD transition can be estimated from short-term clinical trials (12–14). Authors of cost-effectiveness studies chose “to use the observed in-trial median time from DSC to ESRD and a constant hazard rate function to project yearly transition probabilities from DSC to ESRD” to address this issue (6). From our results, the annual probability from DSC to graft loss transition cannot be adequately extrapolated from short-term clinical trials of renal transplantation.

Baseline renal function profoundly affected the predictive performance of DSC in our study. Thus, groups of patients with different baseline renal function should not be compared when DSC is used in epidemiological studies and clinical trials. Unfortunately, this situation occurs in many studies. For instance, results of a recent clinical trial described the incidence of the primary endpoint (DSC, ESRD, or death) in nontransplanted patients with different baseline renal function (20). Austin et al. (21) compared renal outcome using DSC of two groups of patients with lupus nephritis but with different baseline renal function. Jacobi et al. (22) compared the incidence of combined endpoints including DSC in groups of kidney transplant recipients with different renal function. According to our data, such analyses must be interpreted with caution.

The exact relationship between DSC and graft loss has never been assessed in renal transplantation. The aim of our analysis was to assess the limits and drawbacks of DSC in kidney transplantation, not to demonstrate that DSC is superior to other biomarkers. DSC is obviously a marker of deleterious renal outcome in all renal populations, but quantitative information was lacking, so we wanted to give practical information to patients and physicians. We observed the median graft half-life after DSC to be 9 months but depended on time to DSC and initial renal function. Graft half-life could be as short as 1 month (time to DSC <1 year) or 3 months (initial serum creatinine level <130 μmol/L) or as long as 18 months (time to DSC 5.5–9.9 years or initial serum creatinine level ≥130 μmol/L). We believe that this practical information is useful for physicians and patients, especially when renal function decline is poorly understood by the patient. Providing this information to patients may help them more easily prepare for dialysis or retransplantation.

Our study has some limitations. It is a retrospective study, and our results should be duplicated in other cohorts of transplanted and nontransplanted patients. However, our study was carefully designed: we included chronic deterioration of renal function, and files of individual patients were reviewed. In addition, the results of our study were similar when the 12-month serum creatinine value (instead of the 3-month serum creatinine value) was used as the baseline renal function to calculate DSC. We believe that our results are applicable to renal transplant recipients. There is no theoretical basis to think that similar studies in patients with other causes of renal diseases may lead to different findings: the qualitative results of our study could be generalized to the situation for all chronic progressive nephropathies.

In conclusion, we found the sensitivity of DSC to predict graft loss poor with up to 5 years' follow-up, and its predictive value is diminished with longer follow-up. DSC must be used with caution in epidemiology studies. Use of DSC in addition to graft loss as a composite endpoint would lead to only a small sample size reduction in trials of renal transplantation. The long-term annual probability of DSC to graft loss transition depends on the duration of follow-up and cannot be extrapolated from short-term studies of renal transplantation. Results of half-life graft survival after DSC derived from our analyses can be useful information for patients and physicians to predict graft loss and to prepare patients for dialysis or retransplantation.

Back to Top | Article Outline

MATERIALS AND METHODS

Selection of the Population

In total, 1013 consecutive patients received a renal transplant between October 1985 and June 2006 in our center (23). We excluded pediatric patients (age <15 years, n=49), patients with no data at 3 months because of early graft loss or death (n=57) and those with inadequate follow-up (n=11). Finally, 896 patients were included in the present retrospective analysis. We reviewed the individual files for these 896 patients.

Initial immunosuppression included methylprednisolone, 250 mg pre- and postoperatively; antithymocyte antibodies (Thymoglobuline; Genzyme, Lyon, France); or anti-Il2 receptor antibodies (Basiliximab, Simulect; Novartis, Rueil-Malmaison, France) at day 0 and day 4. Maintenance immunosuppressive regimen included prednisone with a gradual tapering and mycophenolate mofetil or azathioprine. Patients received cyclosporine, tacrolimus, or sirolimus. For patients with low immunologic risk, steroids were usually withdrawn during the first year (24).

Visits in our ward were organized as follows: three visits per week during the first 2 weeks, two visits per week until day 60, weekly visits until day 120; monthly visits during the first year, one visit every other month during the second year, and three visits per year thereafter until death or graft loss (i.e., dialysis or retransplantation).

Back to Top | Article Outline

Variables Studied

At the time of transplantation, the following variables were recorded: type of donor (living or deceased), donor age, age and sex of recipient, cause of renal failure, immunosuppressive induction treatment and delayed graft function.

At the 3-month visit after transplantation, the following variables were recorded: body weight and body mass index, systolic and diastolic arterial pressure, acute rejection episodes, serum creatinine level (measured by the Jaffe method), level of eGFR (measured by the Modification of Diet in Renal Disease formula (25), immunosuppressive regimen, and proteinuria (on a 24-hr urine collection, measured by the pyrogallol method (26). Serum creatinine testing was performed in the same laboratory, and values were recorded until death, end of follow-up or graft loss, which allowed us to define the time from transplantation to DSC (time to DSC) and graft survival after DSC.

For calculating time to DSC, the reference serum creatinine level was defined as the 3-month serum creatinine value for all patients, and only chronic progressive degradation of renal function was considered (but not reversible increases of serum creatinine values). We used DSC as it is presently used in epidemiological studies and clinical trials, with a close follow-up of serum creatinine. Specifically, when dialysis for graft failure occurred, we retrieved the last serum creatinine value before dialysis, allowing us to verify whether DSC had occurred before dialysis; when a graft with previously good stable function suddenly failed and required chronic dialysis, we retrieved the last known serum creatinine value and verified whether DSC had occurred; we did not exclude patients had with poor function at 3 months from the analysis, because these patients are not excluded from the analysis in epidemiological studies and clinical trials.

Back to Top | Article Outline

Statistical Analyses

Results are expressed as percentages or as mean±standard deviation. Median is presented when the distribution of the parameters was not normal. We assessed the relative risk of death-censored graft loss in patients with DSC expressed as HRs, 95% CIs and P values estimated from Cox models.

We aimed to identify covariates that could modify the predictive value of DSC using multivariate Cox models. When possible, we compared the HR using unpaired t tests (after HR log transformation) in subgroup analyses. We calculated the incidence of DSC and graft loss after 5 years of follow-up and from the results, calculated the number of patients to theoretically include in clinical trials of DSC and graft loss (as compared with the use of graft loss alone) to define how DSC could affect sample size. We calculated the observed annual probability of DSC to graft loss transition and the time to graft loss after DSC to assess whether DSC could be adequately used in cost-effectiveness studies (12–14). We present half-life graft survival data for patients with DSC to provide practical information for patients and physicians. Patients were censored at their date of death, graft loss, or date of last visit. Analyses involved use of SAS version 9.1 (SAS Institute, Cary, NC). A P less than 0.05 was considered statistically significant.

Back to Top | Article Outline

REFERENCES

1.Patel A, MacMahon S, Chalmers J, et al. Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes mellitus. N Engl J Med 2008; 358: 2560.
2.Yusuf S, Teo KK, Pogue J, et al. Telmisartan, ramipril or both in patients at high risk for vascular events. N Engl J Med 2008; 358: 1547.
3.Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Eng J Med 2001; 345: 861.
4.Lewis EJ, Hunsicker LG, Clarke WR, et al. Renoprotective effect of angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 2001; 345: 851.
5.Rossing P. Doubling of serum creatinine: It is sensitive and relevant? Nephrol Dial Transplant 1998; 13: 244.
6.Palmer AJ, Annemans L, Rose S, et al. Cost-effectiveness of early irbesartan treatment vs control (standard antihypertensive medications excluding ACE inhibitors, other angiotensin-2 receptor antagonists, and dihydropyridine calcium channel blockers) or late irbesartan treatment in patients with type 2 diabetes, hypertension, and renal disease. Diabetes Care 2004; 27: 1897.
7.Rodby RA, Chiou CF, Borenstein J, et al. The cost-effectiveness of irbesartan in the treatment of hypertensive patients with type 2 diabetes mellitus. Clin Ther 2003; 7: 2102.
8.Delea TE, Sofrygin O, Palmer JL, et al. Cost-effectiveness of aliskiren in type 2 diabetes mellitus. J Am Soc Nephrol 2009; 20: 2205.
9.Fellstrom B, Holdaas H, Jardine AG, et al. Risk factors for reaching renal endpoints in the assessment of lescol in renal transplantation (ALERT) trial. Transplantation 2005; 79: 205.
10.Knoll GA, Cantarovitch M, Cole E, et al. The Canadian ACE-inhibitor trial to improve renal outcomes and patients survival in kidney transplantation. Nephrol Dial Transplant 2008; 23: 354.
11.Blach A, Franek E, Witula A, et al. The influence of chronic periodontitis on serum TNF-alpha, IL-6 and hs-CRP concentrations, and function of graft and survival of kidney transplant recipients. Clin Transplant 2009; 23: 213.
12.Yuen SK, Mak YF, Tang HL, et al. Renal allograft C4d deposition in Chinese: Hong Kong perspective. Nephrology 2008; 13: 256.
13.Chow KM, Szeto CC, Leung CB, et al. Body mass index as a predictive factor for long-term renal transplant outcomes in Asians. Clin Transplant 2006; 20: 582.
14.Canales M, Youssef P, Spong R, et al. Predictors of chronic kidney disease in long-term survivors of lung and heart-lung transplantation. Am J Transplant 2006; 6: 2157.
15.Jafar TH, Schmid CH, Stark PC, et al. The rate of progression of renal disease may not be slower in women compared with men: A patient-level meta-analysis. Nephrol Dial Transplant 2003; 18: 2047.
16.Coggins C, Breyer Lewis J, Caggiula AW, et al. Differences between women and men with chronic renal disease. Nephrol Dial Transplant 1998; 13: 1430.
17.Ruggenenti P, Perna A, Zoccali C, et al. Chronic proteinuric nephropathies. II. Outcomes and response to treatment in a prospective cohort of 352 patients: Differences between women and men in relation to the ACE gene polymorphism. Gruppo Italiano di Studi Epidemologici in Nefrologia (Gisen). J Am Soc Nephrol 2000; 11: 88.
18.Li PK, Ho KK, Szeto CC, et al. Prognostic indicators of IgA nephropathy in the Chinese—Clinical and pathological perspectives. Nephrol Dial Transplant 2002; 17: 64.
19.Gerth WC, Remuzzi G, Viberti G, et al. Losartan reduces the burden and cost of ESRD: Public health implications from the RENAAL study for the European Union. Kidney Int Suppl 2002; 62: S68.
20.Hou FF, Zhang X, Zhang GH, et al. Efficacy and safety of benazepril for advanced chronic renal insufficiency. N Engl J Med 2006; 354: 131.
21.Austin HA III, Boumpas DT, Vaughan EM, et al. Predicting renal outcomes in severe lupus nephritis: Contributions of clinical and histologic data. Kidney Int 1994; 45: 544.
22.Jacobi J, Rockstroh J, John S, et al. Prospective analysis of the value of 24-hour ambulatory blood pressure on renal function after kidney transplantation. Transplantation 2000; 70: 819.
23.Halimi JM, Laouad I, Buchler M, et al. Early low-grade proteinuria: Causes, short-term evolution and long-term consequences in renal transplantation. Am J Transplant 2005; 5: 2281.
24.Laouad I, Halimi JM, Buchler M, et al. Recipient age and mycophenolate mofetil as the main determinants of outcome after steroid withdrawal: Analysis of long-term follow-up in renal transplantation. Transplantation 2005; 80: 872.
25.Levey AS, Bosch JP, Lewis JB, et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999; 130: 461.
26.Halimi JM, Buchler M, Al-Najjar A, et al. Urinary albumin excretion and the risk of graft loss and death in proteinuric and non-proteinuric renal transplant recipients. Am J Transplant 2007; 7: 618.
Keywords:

Doubling of serum creatinine; Epidemiology; Clinical trials; Cost-effectiveness studies; Surrogate endpoint; Renal transplantation

© 2011 Lippincott Williams & Wilkins, Inc.