| 2008 JASN IMPACT FACTOR 7.505 | HOME AUTHOR INFO EDITORIAL BOARD SUBSCRIBE FEEDBACK ALERTS HELP | |||
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Clinical Research |



* Klinik III für Innere Medizin, University of Cologne, Cologne, Germany;
Department of Internal Medicine and CNR Institute of Clinical Physiology, University of Pisa, Pisa, Italy;
Diabetes Division, University of Texas Health Science Center, San Antonio, Texas;
Department of Medicine I, Rudolfstiftung Hospital, Vienna, Austria; and || Takeda Global Research and Development Center, Inc., Deerfield, Illinois
Correspondence: Dr. Christian A. Schneider, Facharzt für Innere Medizin/Kardiologie Klinik III für Innere Medizin, Zimmer 0, C, 329 Universität zu Köln Kerpener Strasse 68, 50937 Köln, Germany. Phone: 0221-4786205; Fax: 0221-4783673; E-mail. christian.schneider{at}uk-koeln.de
Received for publication June 18, 2007. Accepted for publication August 27, 2007.
| Abstract |
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| Introduction |
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The PROspective pioglitAzone Clinical Trial In macroVascular Events (PROactive) was designed to compare the effects of the thiazolidinedione pioglitazone with placebo on cardiovascular outcomes in a large cohort of patients with diabetes and a history of macrovascular disease.8 In this high-risk population with diabetes, pioglitazone treatment reduced the combined main secondary end point of all-cause mortality, myocardial infarction (MI; excluding silent MI), and stroke by 16% (P = 0.027) and the primary composite end point (which also included procedural end points, e.g., leg revascularization) by 10% (P = 0.095).9 In this report, we analyzed the influence of CKD on the rates of the primary and the principal secondary end points from PROactive. We also compared the effect of pioglitazone versus placebo on recurrent cardiovascular events in this population of PROactive patients with CKD at baseline.
| RESULTS |
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60 versus GFR <60 ml/min per 1.73 m2 are shown in Table 1. Patients with CKD were older, had longer duration of diabetes, and had a higher prevalence of hypertension. There were no differences between treatment groups in baseline characteristics in patients with GFR either
60 or <60 ml/min per 1.73 m2 (Table 1).
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60 ml/min per 1.73 m2 (hazard ratio [HR] 1.51; 95% confidence interval [CI] 1.28 to 1.78; P < 0.0001). The incidence of the principal secondary end point was 18.3% in patients with CKD compared with 11.5% in patients with GFR
60 ml/min per 1.73 m2 (HR 1.65; 95% CI 1.35 to 2.03; P < 0.0001). Similarly, a higher proportion of patients with a GFR <60 ml/min per 1.73 m2 died from any cause (n = 65; 10.9%) than those with a GFR
60 ml/min per 1.73 m2 (n = 267; 5.9%; HR 1.86; 95% CI 1.42 to 2.43). Multivariate analysis showed that the presence of CKD was an independent risk factor for the primary composite end point (Table 2). Both serum creatinine and GFR were significant in the absence of the other.
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60 ml/min per 1.73 m2, the incidence of the primary end point was 19.0% with pioglitazone and 20.2% with placebo (HR 0.94; 95% CI 0.83 to 1.07). Similar results were seen for the principal secondary end point (10.9% with pioglitazone and 12.2% with placebo; HR 0.89; 95% CI 0.75 to 1.05). The proportion of patients who had a GFR
60 ml/min per 1.73 m2 and subsequently died from any cause was also similar between groups (n = 137 [6.0%] with pioglitazone versus n = 130 [5.7%] with placebo; HR 1.09; 95% CI 0.87 to 1.38). The interaction between baseline renal function and effect of pioglitazone did not reach statistical significance (P = 0.1923 for the primary end point and P = 0.1781 for the principal secondary end point), indicating that the effect of pioglitazone relative to placebo was similar regardless of GFR. The proportion of patients with a negative Micral test was higher in patients without than with CKD and was slightly lower at final visit than at baseline in both patients with (47.8% at baseline; 42.8% at final visit) and patients without CKD (56.5% at baseline; 54.9% at final visit) at baseline. Multivariate analysis showed that a positive Micral test at baseline was an independent risk factor for the primary composite end point and remained significant when GFR was included in the model (Table 2).
During the mean treatment period of 3 yr, GFR declined by 5.4 and 2.7 ml/min per 1.73 m2 in the pioglitazone and placebo groups, respectively (P < 0.0001). In the patients who had a GFR
60 ml/min per 1.73 m2 at baseline, 467 (20.4%) in the pioglitazone group and 370 (16.3%) in the placebo group developed CKD during the study (P = 0.0004). The decreases in BP in the patients with GFR
60 ml/min per 1.73 m2 at baseline (–4.3 mmHg in systolic and –3.5 mmHg in diastolic BP with pioglitazone versus –2.5 mmHg and –2.9 mmHg, respectively, in the placebo group) were similar to those observed in the total PROactive population. In the group of patients with CKD at baseline, BP decreased to a similar extent in both treatment groups (–3.0 mmHg in systolic and –3.2 mmHg in diastolic BP with pioglitazone versus –3.4 mmHg and –2.9 mmHg, respectively, in the placebo group). There were no significant differences in the changes of concomitant treatment between the GFR groups (data not shown).
| DISCUSSION |
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Several potential mechanisms may explain this increased cardiovascular risk in patients with CKD and diabetes. First, CKD often coexists with other cardiovascular risk factors, including dyslipidemia, hypertension, and smoking.10–13 Second, impaired kidney function is associated with elevated markers of inflammation and other putative risk factors for cardiovascular events,14–18 which contribute to adverse cardiovascular outcomes. Last, patients with renal disease are less likely to receive proven efficacious therapies to prevent CVD.19–22
In the recently published post hoc analysis of Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), a GFR <60 ml/min per 1.73 m2 was associated with an increased incidence for CVD (HR 1.41) in the subgroup of patients with type 2 diabetes.23 Our analysis supports the concept that patients with type 2 diabetes and CKD are at increased risk for recurrent cardiovascular events (HR 1.51 for the primary end point and 1.65 for the principal secondary end point) and highlights the need for intensive therapy in these patients.24
Pioglitazone was more effective than placebo in reducing the rate of both the primary and secondary composite end points in the patients with CKD. There was a nonsignificant 25% risk reduction for pioglitazone relative to placebo for the primary end point (95% CI 0.55 to 1.03) and a significant 34% relative risk reduction for the secondary end point (95% CI 0.45 to 0.98). Likewise, event rates were lowered to a greater degree by pioglitazone relative to placebo among the patients without CKD at baseline, but the difference between treatment groups was not statistically significant. Thus, the effect of pioglitazone relative to placebo seems to be the same regardless of GFR.
The yearly declines in GFR (0.9 ml/min per 1.73 m2 with placebo and 1.8 ml/min per 1.73 m2 with pioglitazone) in our study is considerably lower than the decline of 3 to 4 ml/min per 1.73 m2 observed in patients with diabetes in previous studies25,26 and is more in the range of the GFR decrease found in an aging healthy population (1 ml/min per 1.73 m2/yr).27 This smaller decrease might be explained by the strict treatment algorithm for hyperglycemia and hypertension used in PROactive. The clinical significance of the small difference in GFR decline of 0.8 ml/min per 1.73 m2/yr between placebo and pioglitazone is uncertain considering the suboptimal precision in monitoring the GFR changes using the Modification of Diet in Renal Disease (MDRD) method.28,29 Despite this small change in GFR, our data indicate that treatment with pioglitazone will be of considerable benefit to patients with diabetes and CKD.
A detailed analysis of reported adverse events was not conducted; however, the most critical events, such as cardiovascular events and death, were included in the efficacy parameters. This gives reassurance on the safety profile of pioglitazone in patients with reduced kidney function.
This analysis of PROactive has several limitations. Although the data for this analysis were collected prospectively, the analysis for the presence of CKD was defined and performed retrospectively and treatment randomization was not stratified by CKD. Because this could affect the reliability of the prognostic data, the conclusions about the beneficial effects of pioglitazone in patients with CKD must be viewed with caution until confirmatory data of our findings are provided. It should be emphasized that the participants in PROactive were selected because of their high cardiovascular risk; therefore, caution also should be exercised when extrapolating the estimates of cardiovascular event rates in patients with CKD to those who are at lower cardiovascular risk. Nevertheless, our data suggest strongly that patients with diabetes and high risk identified by CKD can be treated effectively with pioglitazone.
In this retrospective analysis of patients with type 2 diabetes and preexisting macrovascular disease in PROactive, we have shown that CKD identifies a subpopulation of patients who are at even higher risk for CVD and that pioglitazone reduces major cardiovascular end points in these patients.
| CONCISE METHODS |
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All patients provided written informed consent. The study protocol was approved by local and national ethics committees and regulatory agencies and was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines.
Procedures
Patients were randomly assigned to receive pioglitazone (n = 2605) or matching placebo (n = 2633) in addition to their existing guideline-directed glucose-lowering and cardiovascular medications. Pioglitazone was administered as 15 mg/d for the first month, 30 mg/d for the second month, and 45 mg/d thereafter to achieve the maximum tolerated dosage. All patients were followed until the end of the study even when they permanently ceased study medication before the study end. Before the start of therapy, serum creatinine was determined in a central laboratory using the automated Hitachi (Tokyo, Japan) with Roche reagents (Roche Diagnostics, Mannheim, Germany) and standards and controls as recommended by the manufacturer. The central laboratory was certified by a national quality-control program. Urinary albumin concentration was measured locally at the beginning and at the end of the study using the Micral Test strip (Roche Diagnostics, Mannheim, Germany). Blood samples were taken for creatinine determination to examine the natural history of renal disease. GFR was estimated using the simplified MDRD formula: 186.2 x serum creatinine in mg/dl–1.154x age in yr–0.203x 1.212 if black x 0.742 if female.1 Patients with a GFR <60 ml/min per 1.73 m2 were defined as having renal dysfunction (CKD; National Kidney Foundation definition) at baseline. Treatment randomization was not stratified by CKD.
The primary end point in PROactive was time from randomization to the composite end point of all-cause mortality, nonfatal MI (including silent MI), stroke, acute coronary syndrome, coronary/carotid arterial intervention, leg revascularization, or amputation above the ankle. The prespecified principal secondary end point in PROactive was time to the first event of all-cause mortality, MI (excluding silent MI), and stroke, because these represent "hard" end points of greatest concern to patients. Nottingham Clinical Research Group (Nottingham, UK) acted as the coordinating center, providing project management, data management, central randomization services, and statistical analysis. ICON Clinical Research (Southampton, UK) managed and monitored the sites and carried out central laboratory measurements.
Statistical Analyses
Statistical methods used for the sample size calculation and end point analysis for PROactive have been reported previously.9 The data presented here are from the intention-to-treat population. Group comparison was carried out by Mann-Whitney or
2 testing, for continuous variables and proportion, respectively. Time-to-event analyses were performed by fitting a Cox proportional hazards survival model with either treatment or baseline CKD as a covariate. The interaction between CKD and treatment on event rates was tested in a similar model containing both covariates. Multivariate Cox models were used to identify baseline factors prognostic of outcome; variable selection was carried out using a stepwise selection algorithm at a significance level of 0.05.
| DISCLOSURES |
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| Acknowledgments |
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These data were presented as poster presentations at the annual meeting of the American Diabetes Association; June 23, 2007; Chicago, IL.
| Footnotes |
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See related editorial, "Cardiovascular Disease, Chronic Kidney Disease, and Type 2 Diabetes Mellitus: Proceeding with Caution at a Dangerous Intersection," on pages 5–7.
| REFERENCES |
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