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Keywords:

  • Diabetes mellitus;
  • kidney transplantation;
  • tacrolimus;
  • mycophenolate mofetil;
  • azathioprine;
  • obesity;
  • African American;
  • Hispanic

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

New onset diabetes is a major complication after kidney transplantation. However, the incidence, risk factors and clinical relevance of post-transplant diabetes mellitus (PTDM) vary among reports from single-center observational studies and clinical trials. Using data from the United Renal Data System we identified 11 659 Medicare beneficiaries who received their first kidney transplant in 1996–2000. The cumulative incidence of PTDM was 9.1% (95% confidence interval = 8.6–9.7%), 16.0% (15.3–16.7%), and 24.0% (23.1–24.9%) at 3, 12, and 36 months post-transplant, respectively. Using Cox's proportional hazards analysis, risk factors for PTDM included age, African American race (relative risk = 1.68, range: 1.52–1.85, p < 0.0001), Hispanic ethnicity (1.35, range: 1.19–1.54, p < 0.0001), male donor (1.12, range: 1.03–1.21, p = 0.0090), increasing HLA mismatches, hepatitis C infection (1.33, range: 1.15–1.55, p < 0.0001), body mass index ≥30 kg/m2 (1.73, range: 1.57–1.90, p < 0.0001), and the use of tacrolimus as the initial maintenance immunosuppressive medication (1.53, range: 1.29–1.81, p < 0.0001). Factors that reduced the risk for PTDM included the use of mycophenolate mofetil, azathioprine, younger recipient age, glomerulonephritis as a cause of kidney failure, and a college education. As a time-dependent covariate in Cox analyses that also included multiple other risk factors, PTDM was associated with increased graft failure (1.63, 1.46–1.84, p < 0.0001), death-censored graft failure (1.46, 1.25–1.70, p < 0.0001), and mortality (1.87, 1.60–2.18, p < 0.0001). We conclude that high incidences of PTDM are associated with the type of initial maintenance immunosuppression, race, ethnicity, obesity and hepatitis C infection. It is a strong, independent predictor of graft failure and mortality. Efforts should be made to minimize the risk of this important complication.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Although new immunosuppressive medications have greatly improved short-term graft survival after kidney transplantation, morbidity and mortality remain high. Recent evidence has suggested that post-transplant diabetes mellitus (PTDM) has become increasingly common after kidney transplantation (1), and PTDM may adversely affect patient (2–4), and graft survival (5,6). A number of risk factors for PTDM have been identified in single-center, retrospective, observational or case-control studies. These include obesity (1,3,7), age (3), race (3), ethnicity (8), family history (9,10), donor source (cadaver vs. living) (3,8), acute rejection (1,5,8–14), the dose of corticosteroids (7,10), and the type of immunosuppressive agents used to prevent and treat rejection (1,5,8–10,12,13,15). Although the best method for determining the incidence of PTDM associated with the use of different immunosuppressive agents is from randomized controlled trials, the results from these trials have been variable (3,16–25). In addition, the patients selected for clinical trials may not resemble those in clinical practice. Therefore, we used a recently validated method for identifying PTDM among Medicare beneficiaries in the United States to examine the incidence and clinical correlates of PTDM after kidney transplantation (26). Results suggest that PTDM is a common, potentially preventable complication that has adverse effects on patient and graft survival.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Patient population

We included patients in the United States Renal Data System who received their first kidney transplant in 1996–2000, and had Medicare as their primary payer. We excluded patients with other organ transplants. Patients without Medicare as their primary payer and patients with employer group health insurance were also excluded, because we would be unable to identify claims that would reliably indicate the presence or absence of diabetes. Patients were also excluded if they had diabetes at the time of transplantation, either because diabetes was the cause of the kidney failure or was listed as a comorbidity at the time of the kidney failure (Center for Medicare and Medicaid Services Medical Evidence Form number 2728) or diabetes was identified using Medicare beneficiary claims.

Post-transplant diabetes mellitus

The presence of PTDM was identified using data from Medicare claims and a previously validated method (26). This method required a minimum of one inpatient claim, or two outpatient or pajt B claims within one year to identify a patient as having diabetes. The date of onset of diabetes was assumed to be the date of the earliest claim.

Patient and transplant characteristics

We examined a number of clinical characteristics to determine whether they were associated with the presence or absence of PTDM. These characteristics included patient age, race, ethnicity (Hispanic vs. non-Hispanic), gender, primary cause of kidney disease (other than diabetes), education (highest level of education achieved at the time of transplantation), employment, hepatitis C antibody status at transplantation, and obesity (defined as body mass index ≥30 kg/m2). Donor characteristics included age, race, gender and type of donor (cadaver or living). We also examined the year of transplantation, whether or not it was performed before dialysis (pre-emptive), the number of human leukocyte antigen mismatches, whether or not the panel reactive antibodies were ≥50%, and the type of maintenance immunosuppressive therapy that was stajted after transplantation (intention-to-treat).

Maintenance immunosuppressive medications

We examined the effects on PTDM of medications that were recorded as maintenance immunosuppression on the United Network for Organ Sharing Kidney Transplant Recipient Registration Form (Table 1). We assumed that the 297 (2.6%) patients who were using only methylprednisolone as maintenance immunosuppression were soon to be switched to oral prednisone. Although it is possible that some of these patients, and some of the remaining 278 (2.4%) who were not receiving either prednisone or methylprednisolone, were treated with steroid-free immunosuppression, we considered that many of these patients might have been receiving corticosteroids despite the fact that it was not recorded. For this reason, and because the number of these patients was very small, we did not attempt to analyze the effect of corticosteroids on PTDM. Similarly, we did not attempt to analyze the effects of medications used by less than 1% of the population, e.g. SangCyA® (Sangstat Medical Corporation, Fremont, CA), deoxyspergualin, methotrexate and cytoxan.

Table 1.  Maintenance immunosuppressive agents
 NumberPercent
Immunosuppressive agents(total=11659)of total
  1. 1 Other includes SangCyA ® (Sangstat Medical Corporation, Fremont, CA), deoxyspergualin, cytoxan, or methotrexate.

Corticosteroids1138197.6%
Mycophenolate mofetil822870.6%
Azathioprine173914.9%
Cyclosporine microemulsion726962.4%
Cyclosporine7476.4%
Tacrolimus278523.9%
Sirolimus5875.0%
Other1540.5%

Some patients received combinations of immunosuppressive medications that more likely resulted from data entry errors than from unusual, experimental regimens. Therefore, we excluded patients who were reported to be receiving (1) azathioprine plus mycophenolate mofetil (MMF), (2) cyclosporine A (CsA, Sandimmune®, Novajtis Pharmaceuticals Corporation, East Hanover, NJ) plus CsA microemulsion (Neoral®, Novajtis Pharmaceuticals Corporation, East Hanover, NJ), (3) CsA plus tacrolimus, or (4) CsA microemulsion plus tacrolimus.

Statistical analysis

Differences between groups were tested with Student's t-test or chi-square. We examined the independent relationship between clinical characteristics and PTDM using Cox's proportional hazards analysis. We also examined the effect of PTDM on outcomes using Cox's proportional hazards analysis with PTDM as a time-dependent covariate. All analyses were carried out using the statistical software package SAS version 8.2 (SAS Institute Inc., Cary, NC). Results were considered statistically significant for p < 0.05[5].

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

After excluding patients with other organ transplants, and patients with diabetes as the primary cause of kidney failure, there were 15 787 first kidney transplants in 1996–2000 with Medicare as the primary payer. The 15 787 first kidney transplants with Medicare as the primary payer, in comparison with the 21 168 patients who did not have Medicare as their primary payer, were more likely (p < 0.0001) to be: older (mean ± SD = 45 ± 16 vs. 41 ± 16 years); African American (32% vs. 18%) compared with Caucasian (62% vs. 76%) or other racial groups (6% vs. 6%); Hispanic (13% vs. 10%); a recipient of a kidney from a male donor (56% vs. 52%); a recipient of a kidney with a greater number of HLA mismatches (3.2 ± 1.7 vs. 2.9 ± 1.7); hepatitis C antibody positive (6% vs. 3%); and educated with less than a college degree (91% vs. 82%). First kidney transplants with Medicare as the primary payer were less likely to have glomerulonephritis (31% vs. 34%) or polycystic kidney disease (9% vs. 14%) as the primary cause of kidney failure (compared with other causes). Although the differences were not great, the first kidney transplant recipients with Medicare as the primary payer were also more likely to have BMI ≥ 30 kg/m2 (18% vs. 17%, p = 0.0185), and to receive MMF as initial maintenance immunosuppression compared with not receiving MMF (71% vs. 70%, p = 0.0177). There were no differences (p > 0.05) between the two populations in the use of other initial immunosuppressive agents, listed in Table 1.

For analysis of risk factors for PTDM we excluded an additional 3782 (24.0%) with pretransplant claims indicating diabetes from the Medicare primary population, leaving 12 005. We also excluded 346 patients who were treated with improbable drug combinations, leaving 11 659 patients for this analysis. The cumulative incidence of PTDM was 9.1% (95% confidence interval = 8.6–9.7%), 16.0% (15.3–16.7%), and 24.0% (23.1–24.9%) at 3, 12, and 36 months post-transplant, respectively (Figure 1). There were several clinical correlates for PTDM (Table 2). However, the only potentially modifiable risk factors for PTDM were obesity (body mass index at the time of transplantation ≥ 30 kg/m2), hepatitis C infection (as indicated by the presence of pretransplant hepatitis C antibodies), and the type of initial maintenance immunosuppressive medication used.

image

Figure 1. Survival free of post-transplant diabetes(solid line), with 95% confidence intervals(dashed lines). The numbers above the X-axis indicate the total number of patients surviving with a functioning graft free of diabetes at that time.

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Table 2.  Independent clinical correlates of post-transplant diabetes
CharacteristicNumber with characteristic (%)Relative risk for diabetes (95% CI)p-value
  1. Results of the Cox proportional hazards analysis, where numbers greater or less than 1.00 indicate an increased or reduced risk of developing post-transplant diabetes, respectively. Each characteristic was adjusted for all other characteristics shown in the table, including those with p>0.05 (transplant year, donor age, donor source, donor race, recipient gender, cold ischemia time, panel reactive antibody status, employability, pre-emptive transplantation, and other immunosuppressive agents; data not shown).

  2. CI=confidence interval.

0–17years551 (4.7%)0.39 (0.28–0.56)<0.0001
18–44years5378 (46.1%)1.00=reference
45–59years3618 (31.0%)1.90 (1.73–2.09)<0.0001
60+years2112 (18.1%)2.60 (2.32–2.92)<0.0001
African American3646 (31.3%)1.68 (1.52–1.85)<0.0001
Other/unknown677 (5.8%)1.51 (1.26–1.81)<0.0001
White7336 (62.9%)1.00=reference
Hispanic1437 (12.3%)1.35 (1.19–1.54)<0.0001
Non-Hispanic/unknown10222 (87.7%)1.00=reference
Female5199 (44.6%)1.00=reference
Male6460 (55.4%)1.12 (1.03–1.21)0.0090
01275 (10.9%)1.00=reference
6816 (7.0%)1.30 (1.07–1.58)0.0085
Body mass index≥30kg/m22008 (17.2%)1.73 (1.57–1.90)<0.0001
Body mass index<30kg/m29651 (82.8%)1.00=reference
Negative/unknown11001 (94.4%)1.00=reference
Positive658 (5.6%)1.33 (1.15–1.55)<0.0001
College degree1077 (9.2%)0.78 (0.67–0.90)0.0011
No college degree/unknown10582 (90.8%)1.00=reference
Tacrolimus2785 (23.9%)1.53 (1.29–1.81)<0.0001
No tacrolimus8874 (76.1%)1.00=reference
Azathioprine1739 (14.9%)0.84 (0.72–0.97)0.0160
No azathioprine9920 (85.1%)1.00=reference
Mycophenolate mofetil8228 (70.6%)0.78 (0.69–0.88)<0.0001
No mycophenolate mofetil3431 (29.4%)1.00=reference
Cause of disease
Glomerulonephritis3659 (31.4%)0.80 (0.73–0.88)<0.0001
Nondiabetes/unknown10544 (68.6%)1.00=reference

The unadjusted cumulative incidences for PTDM at 3, 12, and 36 months were 13.8%, 22.9%, and 35.2%, respectively, for obese patients compared with 8.2%, 14.6% and 21.8% for nonobese patients (p < 0.0001 by the log-rank test). The effect of obesity was also significant (p < 0.0001) after adjusting for multiple other risk factors (Table 2). Similarly, for patients who were hepatitis C antibody positive at transplantation, the unadjusted cumulative incidences for PTDM at 3, 12, and 36 months were 15.6%, 25.6%, and 35.4%, respectively, compared with 8.8%, 15.4% and 23.4% for patients who were hepatitis C antibody negative at transplantation (p < 0.0001 by the log-rank test). Hepatitis C infection was also an independent risk factor PTDM (Table 2). For patients receiving tacrolimus the unadjusted cumulative incidences of PTDM at 3, 12, and 36 months were 13.5%, 22.1%, and 31.8%, respectively, compared with 7.8%, 14.2%, and 21.9% for patients not receiving tacrolimus (Figure 2). The effect of tacrolimus continued to be significant (p < 0.0001) after adjusting for multiple risk factors (Table 2). For patients treated initially with MMF the unadjusted cumulative incidences of PTDM at 3, 12, and 36 months were 8.9%, 15.6%, and 23.5%, compared with 9.7%, 17.1%, and 25.3% for patients not receiving MMF (p = 0.0236). The effect of MMF was statistically significant (p < 0.0001) after adjusting for multiple other risk factors (Table 2). For patients treated initially with azathioprine the unadjusted cumulative incidences of PTDM at 3, 12, and 36 months were 7.9%, 14.2%, and 22.2%, compared with 9.4%, 16.4%, and 24.4% for patients not receiving azathioprine (p = 0.0704). The effect of azathioprine was statistically significant (p = 0.0161) after adjusting for multiple other risk factors (Table 2). The unadjusted incidence of PTDM changed from 14.3% at one year for those transplanted in 1996–97 to 17.3% at one year for those transplanted in 1998–2000 (p = 0.0029 by the log-rank test). However, the year of transplantation was not an independent risk factor for PTDM after adjusting for other covariates.

image

Figure 2. Survival free of post-transplant diabetes for patients treated without(solid black line) and with(solid gray line) tacrolimus as initial maintenance immunosuppressive medication. The dashed lines indicate the 95% confidence intervals. The numbers above the X-axis indicate the total number of patients surviving with a functioning graft free of diabetes at that time (upper row for patients treated without, and lower row for patients treated with tacrolimus).

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The PTDM was associated with higher rates of graft failure, death-censored graft failure, and mortality (Table 3). These associations were independent of the risk factors for PTDM (Table 2), as well as multiple other risk factors for graft failure. Interestingly, while tacrolimus was associated with a higher rate of PTDM (Table 2), and PTDM was associated with an increased risk for graft failure, tacrolimus was nevertheless associated with a reduced risk for graft failure (Table 3). Similarly, Hispanic ethnicity was associated with a higher rate of PTDM (Table 2), but a slightly reduced risk of graft failure.

Table 3.  Independent effects of post-transplant diabetes on graft failure
CharacteristicRelative risk (95% Cl) Graft failure Death-censored graft failure Death
  1. Results of the Cox proportional hazards analyses, where numbers greater or less than 1.00 indicate an increased or reduced risk of graft failure. Each characteristic was adjusted for all other characteristics, as well as transplant year, donor source (living vs. cadaver), preemptive transplantation, gender, employability, donor age, donor race, cold ischemia time, panel reactive antibody status, employability, and other immunosuppressive agents (not shown).

  2. 1p<0.0001; 20.0001=p<0.0010; 30.0010=p<0.0100; 40.0100=p<0.0500.

Post-transplant diabetes1.63 (1.46–1.84)11.46 (1.25–1.70)11.87 (1.60–2.18)1
Age
0–17 years1.03 (0.81–1.32)1.10 (0.85–1.44)0.80 (0.48–1.34)
18–44 years1.00=reference1.00=reference1.00=reference
45–59 years1.02 (0.92–1.14)0.75 (0.66–0.86)12.13 (1.79–2.54)1
60+years1.48 (1.31–1.68)10.73 (0.62–0.88)24.08 (3.33–4.83)1
Race
African American1.29 (1.16–1.44)11.67 (1.46–1.90)10.86 (0.74–1.02)
Other/unknown0.78 (0.62–0.98)40.86 (0.65–1.15)0.63 (0.44–0.89)3
White1.00=reference1.00=reference1.00=reference
Ethnicity
Hispanic0.77 (0.66–0.91)30.92 (0.75–1.11)0.58 (0.44–0.76)1
Non-Hispanic/unknown1.00=reference1.00=reference1.00=reference
Donor gender
Female1.00=reference1.00=reference1.00=reference
Male0.87 (0.79–0.95)30.88 (0.78–0.98)40.86 (0.75–0.98)4
HLA mismatches
01.00=reference1.00=reference1.00=reference
21.31 (1.06–1.60)41.32 (1.01–1.72)41.33 (0.99–1.77)
31.39 (1.15–1.67)21.46 (1.15–1.86)31.32 (1.01–1.73)4
41.65 (1.38–1.99)11.73 (1.37–2.19)11.47 (1.13–1.92)3
51.59 (1.31–1.93)11.59 (1.24–2.04)21.60 (1.21–2.11)3
61.80 (1.45–2.25)11.90 (1.44–2.51)11.52 (1.10–2.12)4
Obesity
Body mass index≥30 kg/m21.13 (1.01–1.27)41.24 (1.08–1.42)31.01 (0.85–1.20)
Body mass index<30 kg/m21.00=reference1.00=reference1.00=reference
Hepatitis C
Negative1.00=reference1.00=reference1.00=reference
Positive1.24 (1.05–1.46)41.15 (0.94–1.42)1.27 (0.99–1.64)
Education
College degree0.88 (0.75–1.04)0.86 (0.70–1.07)0.88 (0.70–1.11)
No college degree/unknown1.00=reference1.00=reference1.00=reference
Immunosuppression
Tacrolimus0.70 (0.59–0.83)10.72 (0.58–0.88)30.65 (0.50–0.84)2
No tacrolimus1.00=reference1.00=reference1.00=reference
Azathioprine0.90 (0.77–1.04)0.87 (0.72–1.05)0.92 (0.74–1.14)
No azathioprine1.00=reference1.00=reference1.00=reference
Mycophenolate mofetil0.81 (0.71–0.93)30.82 (0.69–0.96)40.77 (0.64–0.93)3
No mycophenolate mofetil1.00=reference1.00=reference1.00=reference
Cause of disease
Glomerulonephritis0.96 (0.87–1.06)1.00 (0.89–1.13)0.91 (0.78–1.06)
Other/unknown1.00=reference1.00=reference1.00=reference

The relative risk of PTDM (adjusted for other clinical correlates of PTDM) for the 923 deaths from any cause [1.87 (1.60–2.18), p < 0.0001], was similar to the relative risks for the 186 deaths as a result of infection [1.87 (1.31–2.67) p = 0.0006], the 258 deaths as a result of cardiovascular disease [1.47 (1.08–1.99), p = 0.0140], and the 188 deaths from other causes [1.82 (1.29–2.58), p = 0.0007]. The relative risk of PTDM for the 62 deaths as a result of malignancy was not statistically significant [1.18 (0.63–2.20), p = 0.5993], while the relative risk for the 229 deaths of unknown causes was 2.77 (2.07–3.72), p < 0.0001.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Post-transplant diabetes is a common complication of immunosuppressive medications after kidney transplantation. Our results suggest that the incidence of PTDM among Medicare beneficiaries is very high. However, it is important to keep in mind that the rate of detection of PTDM may vary depending on the methods used, e.g. how diabetes is defined, the duration of follow up, the types and amounts of immunosuppression used, and the presence of pretransplant risk factors. A recent meta-analysis of observational studies and randomized controlled trials reported that the incidence of PTDM (variously defined) in the first year after transplantation varied from 2 to 50% (27). Our study population included only Medicare beneficiaries, who had a higher prevalence of risk factors for PTDM compared with the non-Medicare primary population. Despite potentially important differences between the clinical trials and the analysis of registry data, the overall incidence of PTDM in this study, 16.0% in one year, is in the range (5–25%) reported in recent randomized controlled trials (Table 4).

Table 4.  Incidence of post-transplant diabetes in randomized controlled trials 1
FirstYearDiabetesYears of Diabetes incidence (%)Other
authorpublisheddefinitionfollow upnPREDCSANEOTACSIRagents
  • 1

    The Scantlebury study did not include patients crossing over. All other studies were analyzed by intention-to-treat. Patients treated with CSA, TAC, or SIR also received prednisone, except as noted in the Isoniemi study.2 CsA and AZA only.FBS=fasting blood sugar, OGT=oral glucose tolerance test, PRED=prednisone, CSA=cyclosporine, NEO=CsA microemulsion, TAC=tacrolimus=SIR=sirolimus, AZA=azathioprine, MMF=mycophenolate mofetil.

Boudreaux (3)1987FBS>140 and OGT2–547 586.4 6.9   AZA AZA
Scantlebury (16)1991Insulin or oral agent1.014 20 7.0  25.0 – –
Isoniemi (17)1991Insulin or oral agent2.025 25 27 21 3.712.0 0.02 14.3   AZA AZA AZA
Ponticelli (18)1996Not Defined1053 5512.2 13.3   AZA AZA
Vincenti (19)1996Insulin> 1week1.028 67 5.0  25.4 AZA AZA
Pirsch (20)1997Insulin> 30days1.0151 151 4.0  19.9 AZA AZA
Mayer (21)1997Insulin> 30days1.0145 303 2.1  11.6 AZA AZA
Shapiro (22)1999Not Defined1.3106 102   9.3 4.7 – MMF
Groth (23)1999Not defined1.042 41 46 2.06.5  2.0AZA AZA MMF
Johnson (24)2000Insulin> 30days1.057 42 42   14.0 6.5 19.0 AZA MMF AZA
Miller (25)2000Insulin> 30days1.041 43   12.2 4.7 MMF (1g) MMF (2g)

We identified several risk factors for PTDM, but only obesity, hepatitis C infection, and the type of immunosuppressive medications used are potentially modifiable. The risk of PTDM was 53% greater in the patients treated with tacrolimus compared with the patients not initially treated with tacrolimus (Table 2). This is consistent with the findings of randomized controlled trials, where the incidence of PTDM has been consistently higher among patients treated with tacrolimus compared with CsA and CsA microemulsion (Table 4). It is likely that some patients changed their immunosuppressive medications during the follow-up period, but in any case the most valid analysis of the effects of immunosuppression is arguably by intention to treat. It is also possible that the association between tacrolimus and PTDM is not causal, and that more patients at risk for PTDM were placed on tacrolimus. However, it seems unlikely that family history for diabetes, or other risk factors not included in the statistical adjustment for the risk of PTDM, would have been more common in the patients treated with tacrolimus.

In contrast to the effects of tacrolimus, the use of azathioprine and MMF were associated with 16% and 22% lower risks, respectively, for PTDM (Table 2). The reasons for these associations are not clear, but it is possible that the use of MMF or azathioprine allowed clinicians to use lower doses of other immunosuppressive medications that are more likely to cause PTDM.

One of the strongest risk factors for PTDM was obesity (Table 2). Several retrospective, single-center, observational and case-control studies have also reported that obesity is associated with an increased risk of PTDM (1,3,7). Lifestyle modification was recently shown to reduce the risk of type 2 diabetes in nontransplant patients with elevated fasting or postload plasma glucose (28). Thus, to the extent that these results may be applicable to kidney transplant recipients, lifestyle modification may help to reduce the risk of PTDM.

Diabetes has been reported to be more common in patients with hepatitis C than in other types of liver disease in the general population (29,30). Similarly, hepatitis C has been associated with an increased incidence of PTDM in liver transplant recipients (31,33), and there is a preliminary report linking hepatitis C and PTDM in kidney transplant recipients (34). Importantly, successful antiviral treatment of hepatitis C in liver transplant recipients appears to be associated with improved glycemic control (35,36). This suggests that successful pre- or post-transplant treatment of hepatitis C could potentially reduce the incidence of PTDM after kidney transplantation.

Age is another important risk factor for PTDM (Table 2). Single-center, retrospective studies have consistently found PTDM to be much more common in older compared with younger individuals (1,3,5,8–10,12,13). Indeed, PTDM was recently reported to occur in less than 3% of children (14).

In the present study, PTDM was more common among African Americans compared with Caucasians. This has also been reported in single-center, retrospective studies (1,2,8,14). Similarly, Hispanic ethnicity was associated with a higher risk of PTDM in the current study, and this has been reported in a single-center study (8). However, another study reported that Hispanic children were at lower risk for PTDM compared with non-Hispanic children (14). These inconsistencies may be because of the small number of children with PTDM in the latter study.

Age, race and ethnicity are not modifiable risk factors, and obesity is a risk factor that is difficult to modify. However, the effects of risk factors are additive, and it may be possible to reduce the overall risk of PTDM by avoiding or reducing the doses of immunosuppressive medications that are pajticularly likely to cause PTDM in patients with these other risk factors. Of course the risk of acute rejection must also be included in the selection of immunosuppressive medications.

It is interesting that despite the association between tacrolimus and PTDM, and the association between PTDM and reduced graft survival, tacrolimus was nevertheless associated with improved graft survival (Table 3). Similarly, MMF was associated with improved outcomes (Table 3). Of course, none of these associations proves causal relationships, and to date there have been no randomized controlled trials showing that either tacrolimus or MMF improve graft survival. In the end, only long-term follow up of patients treated in randomized trials will allow us to judge the relative effects of different immunosuppressive medications on graft and patient survival.

Some of the associations between PTDM and graft failure can be explained by the higher risk for death, and indeed the relative risk associated with PTDM is higher for death than for death-censored graft failure (Table 3). It is plausible that PTDM had a direct effect on mortality, as diabetes is associated with an increased risk for infection and other complications that can increase mortality. Less clear is why PTDM was associated with death-censored graft failure. Given the relatively short period of follow up in this study, it seems unlikely that PTDM caused death-censored graft failure solely because of recurrence of diabetes in the allograft. It is possible that PTDM influenced the structure and function of the graft and accelerated graft deterioration in ways that remain poorly defined. However, it is even more plausible that the association between PTDM and death-censored graft survival was the result of early acute rejection that led to both PTDM and death-censored graft survival. Specifically, acute rejection and/or graft dysfunction may have led to the use of more immunosuppression that caused PTDM and (independently) a higher risk for death censored graft failure.

In summary, this study shows that there is a very high incidence of PTDM after kidney transplantation, and that PTDM is associated with worse outcomes. Although the reasons for these associations may not be causal, it is advisable to minimize the risk for PTDM after kidney transplantation. The results of this study suggest that the selection of immunosuppression, pajticularly in high-risk patients, may be one way in which the risk of PTDM may be reduced.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The data reported here have been supplied by the United States Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the U.S. Government. Portions of this work were presented at the American Society of Nephrology and International Congress of Nephrology's joint World Congress of Nephrology, October 16, 2001, in San Francisco, CA.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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