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Record W2115504370 · doi:10.1681/asn.2007111202

Sirolimus Is Associated with New-Onset Diabetes in Kidney Transplant Recipients

2008· article· en· W2115504370 on OpenAlex

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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
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Bibliographic record

VenueJournal of the American Society of Nephrology · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of British ColumbiaSt. Paul's Hospital
Fundersnot available
KeywordsSirolimusMedicineHazard ratioTacrolimusNodInternal medicineTransplantationDiabetes mellitusKidney transplantationGastroenterologyUrologyConfidence intervalEndocrinology

Abstract

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New-onset diabetes (NOD) is associated with transplant failure. A few single-center studies have suggested that sirolimus is associated with NOD, but this is not well established. With the use of data from the United States Renal Data System, this study evaluated the association between sirolimus use at the time of transplantation and NOD among 20,124 adult recipients of a first kidney transplant without diabetes. Compared with patients treated with cyclosporine and either mycophenolate mofetil or azathioprine, sirolimus-treated patients were at increased risk for NOD, whether it was used in combination with cyclosporine (adjusted hazard ratio [HR] 1.61; 95% confidence interval [CI] 1.36 to 1.90), tacrolimus (adjusted HR 1.66; 95% CI 1.42 to 1.93), or an antimetabolite (mycophenolate mofetil or azathioprine; adjusted HR 1.36; 95% CI 1.09 to 1.69). Similar results were obtained in a subgroup analysis that included the 16,861 patients who did not have their immunosuppressive regimen changed throughout the first posttransplantation year. In conclusion, sirolimus is independently associated with NOD. Given the negative impact of NOD on posttransplantation outcomes, these findings should be confirmed in prospective studies or in meta-analyses of existing trials that involved sirolimus. New-onset diabetes (NOD) is an increasingly common posttransplantation complication1,2 that is associated with patient death,3–5 graft loss,6,7 and increased health care expenditures.8 Several risk factors for NOD have been identified: Older age,3,9,10 black race,2,3,10 Hispanic ethnicity,2,10 obesity,2,6 family history of diabetes,10 hepatitis C positivity,2,11 and transplantation of a deceased-donor organ.3,10 In addition, the use of corticosteroids12,13 and calcineurin inhibitors (CNI) has been associated with an increased risk for NOD.2,14–18 The higher risk for NOD in tacrolimus compared with cyclosporine A (CsA)-treated patients identified in observational studies2 was recently confirmed in a randomized, controlled trial.19 Single-center studies have suggested that sirolimus may also be diabetogenic.20,21 There are a number of possible mechanisms by which sirolimus may cause NOD, including impaired insulin-mediated suppression of hepatic glucose production,22 insulin resistance from ectopic triglyceride deposition,23,24 or direct β cell toxicity.25,26 Although multicenter trials using sirolimus failed to demonstrate an association between sirolimus and NOD,27–29 patients in the comparator groups in these studies received corticosteroids and CNI; therefore, an independent association between sirolimus and NOD may not have been evident despite the relatively large number of participants in these trials. We therefore performed this analysis using patients captured in the United States Renal Data System (USRDS) to determine whether there is an association between sirolimus and NOD. RESULTS Among the 21,546 adult recipients of a first kidney only transplant who did not have diabetes and had Medicare as their primary payer during the study period, we excluded 1421 patients who were not prescribed a CNI or sirolimus in combination or with mycophenolate mofetil (MMF) or azathioprine (AZA), as described in the Concise Methods section. The 20,124 study patients were less likely to be of white race than excluded patients (68.5 versus 71.6% respectively; P = 0.04). Other demographic variables, including known risk factors for NOD (age, gender, Hispanic ethnicity, cause of ESRD, body mass index, hepatitis C serostatus, deceased-donor source, and corticosteroid use at time of transplantation) were similar between included and excluded patients (data not shown). Study patients were followed for a median of 2.63 yr (quartile 1, quartile 3 = 1.26, 3.00). The majority of patients were prescribed a CNI in combination with MMF/AZA (Table 1). Because of the large sample size, there were a number of statistically significant differences between patients treated with different maintenance immunosuppressive drug combinations in univariate analyses (Table 1). Cumulative Incidence of NOD by Drug Combination Patients treated with sirolimus in combination with a CNI (either CsA or tacrolimus) had the highest incidence of NOD (Figure 1). The 3-yr cumulative incidence of NOD in patients treated with sirolimus with CsA and with sirolimus with tacrolimus was 21.9 and 21.5%, respectively. Patients treated with tacrolimus and MMF/AZA had the next highest incidence of NOD (cumulative incidence 19.0%). Patient treated with sirolimus and MMF/AZA had a cumulative incidence of NOD of 17.8%. Patients treated with CsA in combination with MMF/AZA had the lowest incidence of NOD (15.6%; overall log rank P < 0.0001). Risk for NOD on the Basis of Maintenance Immunosuppressant Drug Combination at the Time of Transplantation On the basis of the immunosuppressant drug combinations prescribed at the time of transplantation and after adjustment for multiple confounders, patients treated with sirolimus and CsA, sirolimus and tacrolimus, and sirolimus and MMF/AZA all were at increased risk for NOD compared with the reference group of patients treated with CsA and MMF/AZA (Table 2). Of note, these associations were independent of corticosteroid use at the time of hospital discharge after transplantation and acute rejection during the first posttransplantation year. To determine whether the increased risk for NOD in patients treated with the combination of sirolimus and tacrolimus compared with the reference group of patients treated with the combination of CsA and MMF/AZA was simply related to the use of tacrolimus, we repeated the multivariate analysis using patients treated with the combination of tacrolimus and MMF/AZA as the reference group. In this analysis, patients treated with sirolimus and tacrolimus had an increased risk for NOD (hazard ratio [HR] 1.19; 95% confidence interval [CI] 1.02 to 1.37), compared with the reference group of patients treated with the combination of tacrolimus and MMF/AZA, suggesting that sirolimus was associated with an increased risk for NOD independent of any effect of tacrolimus. Risk for NOD among Patients Treated with the Same Immunosuppressant Drug Combinations throughout the First Posttransplantation Year When the Cox multivariate analysis was repeated using only 16,861 (83.8%) patients known to be treated with the same immunosuppressant medications during the first posttransplantation year, patients treated with sirolimus and CsA or with sirolimus and tacrolimus remained at increased risk for NOD compared with the reference group of patients treated with the combination of CsA and MMF/AZA (Table 3). No statistically significant association with NOD was identified in patients treated with the combination of sirolimus and MMF/AZA (only 349 patients could be confirmed to have received the combination of sirolimus and MMF/AZA during the first posttransplantation year). We again considered the possibility that the increased risk for NOD in patients treated with the combination of sirolimus and tacrolimus was simply related to the use of tacrolimus. We therefore repeated the analysis using the patients treated with the combination of tacrolimus and MMF/AZA as the reference group. In this analysis, patients treated with the combination of sirolimus and tacrolimus had an increased risk for NOD (HR 1.25; 95% CI 1.03 to 1.52), suggesting that sirolimus was associated with an increased risk for NOD independent of any effect of tacrolimus. DISCUSSION We found that sirolimus-treated patients were at increased risk for NOD. This association was consistent whether sirolimus was used in combination with CsA, tacrolimus, or MMF/AZA. Indeed, because tacrolimus itself is associated with an increased risk for NOD compared with CsA, we considered the possibility that the risk for NOD in patients treated with the combination of tacrolimus and sirolimus, compared with patients treated with the combination of CsA and MMF/AZA, was simply related to the use of tacrolimus. When the multivariate analysis was repeated with patients treated with the combination of tacrolimus and MMF/AZA as the reference group, patients treated with the combination of sirolimus and tacrolimus remained at increased risk for NOD, suggesting that sirolimus itself increases the risk for NOD. The association of sirolimus with NOD was also demonstrated in a restricted analysis involving patients prescribed the same combination of medications during the first posttransplantation year. The associations demonstrated in this observational study should be confirmed by additional prospective studies or meta-analysis of previously completed trials involving sirolimus that reported the incidence of NOD. To date, only a few clinical studies have suggested that sirolimus and its analogues are associated with hyperglycemia.20,21,30–32 In a randomized trial of 150 renal transplant recipients, the incidence of NOD in patients who received tacrolimus with sirolimus, tacrolimus with MMF, or CsA with sirolimus was 17, 14, and 33%, respectively (P = 0.06), suggesting a possible diabetogenic effect of sirolimus.30,31 In an uncontrolled study, Hricik et al.33 compared clinical outcomes in 56 black patients treated with corticosteroids, sirolimus, and tacrolimus targeted to relatively low tacrolimus trough levels with those in white patients (n = 65) treated with steroids, MMF, and tacrolimus targeted to higher tacrolimus levels. Despite lower tacrolimus levels in the black patients, the incidence of NOD in the black patients was 36 compared with 15% in white patients (P = 0.02). In a retrospective study to examine the incidence of NOD among 86 consecutive renal transplant recipients in a single center between 1997 and 2004, Romagnoli et al.20 reported that patients treated with the combination of sirolimus and CsA had a significantly higher incidence of NOD compared with patients treated with CsA alone. Teutonico et al.21 demonstrated that chronic inhibition of mammalian target of rapamycin (mTOR) caused an increase in peripheral insulin resistance, along with impaired pancreatic β cell response to a glucose load, in a cohort of 26 renal transplant recipients who were converted from treatment with CsA to sirolimus. A pivotal multicenter study using sirolimus did not suggest an increased risk for NOD.28 This may be related to the fact that patients in the comparator group received CsA, which itself is diabetogenic.2,14–18 Using the effect size seen in our analysis, we estimated that enrolment of 1340 patients (670 patients in each treatment group) would be needed to demonstrate an increased risk for NOD in a trial comparing sirolimus with CsA, with α = 0.05 and β = 0.20. Thus, the multicenter trial that enrolled 719 patients28 would have been underpowered to demonstrate an association between sirolimus and NOD. The mechanisms by which sirolimus may cause NOD are not clearly defined. Sirolimus acts on the mTOR, a serine/threonine kinase that integrates signals from various nutrients and growth factors to regulate protein translation through a variety of downstream effectors.34,35 Overactivation of mTOR downstream from the phosphatidylinositol 3-kinase–AKT pathway modulates insulin signaling by insulin receptor substrates.34,35 Physiologic conditions such as hyperinsulinemia promote serine/threonine phosphorylation of insulin receptor substrate proteins that inhibits their function and promotes their degradation, leading to insulin resistance. Inhibitors of mTOR would therefore be expected to prevent development of insulin resistance through this mechanism. Indeed, sirolimus has been associated with a decreased likelihood of NOD.36 More recently, Di Paolo et al.34 studied 30 patients treated with long-term sirolimus and reported an unexpected impairment of insulin receptor substrate signaling and AKT activation, a finding that could help to explain deterioration of glucose metabolism in sirolimus-treated patients. Other mechanisms that have been proposed for the induction of hyperglycemia by sirolimus include ectopic triglyceride deposition with sirolimus leading to insulin resistance,23,24 impairment of insulin-mediated suppression of hepatic glucose production,22 or a direct toxic effect on pancreatic β cells.25,26 When interpreting the results of this study, readers should consider the inherent limitations of retrospective analyses of administrative data sets including nonrandom assignment of patients to different immunosuppressive medication protocols. Although we adjusted for multiple factors known to be associated with NOD, the associations identified may be confounded by other factors not included in our analysis. We are able to adjust only for the use of corticosteroids at the time of hospital discharge after transplantation and at approximately 1 yr after the date of transplantation. We do not have information regarding the dosage of maintenance corticosteroids used in the various regimens. We included adjustment for the incidence of acute rejection to account for some of the variation in corticosteroid use between patients during the first posttransplantation year in our analyses; however, we did not have information regarding the dosage of corticosteroids used to treat acute rejection. We hypothesize that the association of acute rejection with NOD in our analysis is due to a higher exposure to corticosteroids in patients with acute rejection, but other mechanisms may be responsible. Similarly, we do not have information regarding the dosage of sirolimus and CNI used. The study was limited to patients in the United States who had Medicare as the primary payer, which may limit the applicability of our findings to other patient populations. We defined NOD from Medicare claims data according to previously published and validated methods.2,37–41 It is important to note that this criterion is not the same as the “gold standard” established by the American Diabetes Association and World Health Organization, which requires laboratory results and patient symptoms42,43 that are not available in the USRDS data sets. A consistently high level of accuracy and concordance between cases that were identified by this method and the American Diabetes Association/World Health Organization criteria38,40,41 has been established. Our definition has a sensitivity of 0.75, a specificity of 0.97, and a positive predictive value of 0.88 compared with self-reported diabetes.38 In summary, this study identifies an association of sirolimus with NOD. Given the importance of NOD as a determinant of posttransplantation outcomes and the current use of sirolimus in both pancreas and islet cell transplantation, the findings of our study should be confirmed in further prospective studies or in meta-analyses of existing trials using sirolimus. CONCISE METHODS Data Source and Study Population The data source for the study was the USRDS. The study population included adult patients (≥18 yr) who received a first kidney-only transplant between April 30, 1995, and December 31, 2003. The study population was limited to patients with Medicare as the primary payer to permit ascertainment of NOD from institutional claims data. In addition, patients were included only when they were prescribed one of the following recognized combinations of immunosuppressant medications at the time of transplantation: CsA with MMF or AZA, tacrolimus with MMF or AZA, sirolimus with CsA, sirolimus with tacrolimus, or sirolimus with MMF or AZA. Patients with diabetes before transplantation were excluded from the study. Diabetes before transplantation was identified when diabetes was listed as the cause of ESRD, as a comorbid condition, or when there were any inpatient or outpatient Medicare claims for diabetes in the 12 mo before transplantation (see next section for details of Medicare claims used to identify diabetes). Definition of NOD and Patient Follow-up NOD was defined according to previously published and validated methods,2,37–41 based on Medicare claims data. This method required a minimum of one inpatient claim or of two outpatient claims within 1 yr to establish a diagnosis of NOD. Patients were followed from the date of transplantation until death, transplant failure (either dialysis initiation or repeat transplantation), or end of follow-up (December 31, 2004) for the development of NOD. In addition, ascertainment of NOD was limited to the first 3 yr after transplantation, when patients normally retain ESRD Medicare eligibility, to ensure complete ascertainment of NOD from Medicare claims. The specific International Classification of Disease, Ninth Revision, Clinical Modification diagnostic codes used to identify NOD were 250; 250.x (x = 0 to 9), 250.0x, and 250.xy (y = 0 to 3). The date of onset of NOD was assumed to be the date of the earliest Medicare claim. Descriptive Statistics Patients were categorized on the basis of the combination of immunosuppressant medications prescribed at the time of transplantation, and group differences were compared with the χ2 test or ANOVA as appropriate. Association of Sirolimus with NOD The time to NOD after transplantation was determined with the Kaplan-Meier method among patients prescribed the various combinations of immunosuppressant medications described already, and group differences were compared with the log rank test. A Cox multivariate regression analysis was performed to determine the risk for NOD in patients prescribed the different combinations of immunosuppressant medications. The following variables associated with NOD in univariate analyses were included in the model: Patient age at transplantation, gender, race, ethnicity, acute rejection in the first posttransplantation year, cause of ESRD, duration of dialysis before transplantation, donor source, body mass index, hepatitis C serostatus, transplant year, HLA mismatch, comorbid conditions (ischemic heart disease, cerebrovascular disease, peripheral vascular disease, and cardiac failure), and corticosteroid use. Variables were entered into these models when they met the proportional hazards assumption. The proportional hazards assumption was tested for using log-negative-log plots of the within-group survivor probabilities versus log time. Patients with missing covariate information were coded as “missing” for that covariate and included in the multivariate models. A second Cox multivariate regression model, including only patients who remained on the same immunosuppressant drug combination during the first posttransplantation year, was also performed. All analyses were performed using SAS 9.1 (SAS Institute, Cary, NC) and S-Plus 7.0 (Insightful Corp., Seattle, WA). The study was approved by our local hospital research ethics review board. DISCLOSURES None.Figure 1: Cumulative incidence of NOD within the first 3 yr posttransplantation by drug combination at hospital discharge from transplantation.Table 1: Patient characteristics and comparison of patients treated with various immunosuppressant medicationsaTable 2: Factors associated with NODaTable 3: Factors associated with NOD among 16,861 patients treated with the same immunosuppressant drug combinations throughout the first posttransplantation yearJ.G. is supported by the Michael Smith Foundation for Health Research; O.J. is supported by a grant from the Canadian Institute of Health Research and the Michael Smith Foundation for Health Research. This work was presented in abstract form at the American Transplant Congress; San Francisco, CA; May 5–9, 2007.

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Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.269
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it