Portal de Periódicos da CAPES

Simple Measures to Monitor b -Cell Mass and Assess Islet Graft Dysfunction

2006; Elsevier BV; Volume: 7; Issue: 2 Linguagem: Inglês

10.1111/j.1600-6143.2006.01620.x

1600-6143

Raquel N. Faradji, Kathy Monroy, Shari Messinger, Antonello Pileggi, Tatiana Froud, DA Baidal, PE Cure, Camillo Ricordi, Livio Luzi, Rodolfo Alejandro,

Diabetes Management and Research

American Journal of TransplantationVolume 7, Issue 2 p. 303-308 Free Access Simple Measures to Monitor β-Cell Mass and Assess Islet Graft Dysfunction R. N. Faradji, R. N. Faradji Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States MedicineSearch for more papers by this authorK. Monroy, K. Monroy Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United StatesSearch for more papers by this authorS. Messinger, S. Messinger Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States EpidemiologySearch for more papers by this authorA. Pileggi, A. Pileggi Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Surgery, Univ. Miami Leonard M. Miller School of Medicine, Miami, FloridaSearch for more papers by this authorT. Froud, T. Froud Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Surgery, Univ. Miami Leonard M. Miller School of Medicine, Miami, FloridaSearch for more papers by this authorD. A. Baidal, D. A. Baidal Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United StatesSearch for more papers by this authorP. E. Cure, P. E. Cure Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United StatesSearch for more papers by this authorC. Ricordi, C. Ricordi Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Surgery, Univ. Miami Leonard M. Miller School of Medicine, Miami, FloridaSearch for more papers by this authorL. Luzi, L. Luzi Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Diabetes Research Institute – Milan, Istituto Scientifico H. San Raffaele, University of Milan, Milan, ItalySearch for more papers by this authorR. Alejandro, Corresponding Author R. Alejandro Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Medicine * Corresponding author: Rodolfo Alejandro, ralejand@med.miami.eduSearch for more papers by this author R. N. Faradji, R. N. Faradji Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States MedicineSearch for more papers by this authorK. Monroy, K. Monroy Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United StatesSearch for more papers by this authorS. Messinger, S. Messinger Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States EpidemiologySearch for more papers by this authorA. Pileggi, A. Pileggi Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Surgery, Univ. Miami Leonard M. Miller School of Medicine, Miami, FloridaSearch for more papers by this authorT. Froud, T. Froud Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Surgery, Univ. Miami Leonard M. Miller School of Medicine, Miami, FloridaSearch for more papers by this authorD. A. Baidal, D. A. Baidal Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United StatesSearch for more papers by this authorP. E. Cure, P. E. Cure Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United StatesSearch for more papers by this authorC. Ricordi, C. Ricordi Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Surgery, Univ. Miami Leonard M. Miller School of Medicine, Miami, FloridaSearch for more papers by this authorL. Luzi, L. Luzi Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Diabetes Research Institute – Milan, Istituto Scientifico H. San Raffaele, University of Milan, Milan, ItalySearch for more papers by this authorR. Alejandro, Corresponding Author R. Alejandro Clinical Islet Transplant Program at the Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, United States Medicine * Corresponding author: Rodolfo Alejandro, ralejand@med.miami.eduSearch for more papers by this author First published: 06 December 2006 https://doi.org/10.1111/j.1600-6143.2006.01620.xCitations: 85AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract The aim of this study was to develop a simple test for the assessment of islet graft dysfunction based on measures involving fasting C-peptide. Calculations were made to account for the dependence of C-peptide secretion on glucose concentration (C-peptide/glucose ratio [CP/G]) and adjusted for renal function by calculating the C-peptide/glucose-creatinine ratio (CP/GCr). Values from 22 recipients were analyzed at different times post-last islet infusion. Receiver operating characteristic curves were used to determine which of these measures best predicts high 90-minute glucose (90 min-Glc; >10 mmol/L) after a Mixed Meal Tolerance Test (MMTT). In this initial analysis, CP/G was found to be superior predicting high 90 min-Glc with a larger area under the ROC curve than C-peptide (p = 0.01) and CP/GCr (p = 0.06). We then correlated C-peptide and CP/G with islet equivalents-IEQ/kg infused, 90 min-Glc after MMTT and clinical outcome (β-score). C-peptide and CP/G in the first 3 months post-last islet infusion correlated with IEQ/kg infused. CP/G correlated with 90 min-Glc and β-score. C-peptide and CP/G are good indicators of islet mass transplanted. CP/G is more indicative of graft dysfunction and clinical outcome than C-peptide alone. The ease of calculation and the good correlation with other tests makes this ratio a practical tool when monitoring and managing islet transplant recipients. Introduction There is no consensus on which test is best to monitor β-cell mass and function in patients with diabetes and after islet transplantation (1). Most tests give variable results, are time consuming and difficult to perform. Therefore, there is an increasing need for simple metabolic tests for the assessment of islet graft function over time. The relatively low variability, high reproducibility and close relationship of C-peptide measurements in the systemic circulation to endogenously secreted insulin in the portal system makes this a suitable assay for monitoring β-cell function (2). C-peptide is currently performed before and after islet transplantation to document islet graft survival (3). β-cell response to meals is evaluated by the Mixed Meal Tolerance Test (MMTT) (3). This test is being widely used to study the response following therapeutic interventions in new onset T1DM (4) and to monitor the function of transplanted islets (3, 5). Evaluation of the 90-min glucose (90 min-Glc) after MMTT is considered a good acute measure of β-cell reserve following islet transplantation (3, 5), as well as the homeostatic ability of the individual to handle a secretagogue load. Levels of ≤10.0 mmol/L (180 mg/dL) indicate good graft function (6). Plasma C-peptide levels depend on glycemic values. Any given plasma C-peptide value may indicate good graft function if glucose levels are normal, but may be inappropriately low if glucose levels are high. Calculations involving C-peptide measurements accounting for glucose concentrations in type 2 diabetes, as well as islet and pancreas transplant models have been reported for the last three decades in urine (7) and recently in serum (8-10). One of them, the HOMA C-peptide β-cell index-2, requires the use of a specific computer program for its assessment and has not been validated in islet transplant recipients or in patients using exogenous insulin therapy (10). We propose the C-peptide to glucose ratio (CP/G), which corrects for glycemic values. Since C-peptide is cleared through the kidney, we also present a formula that accounts for renal function: the ratio of C-peptide to the product of glucose and serum creatinine (CP/GCr) (11). Our objective was to assess and compare each measure involving C-peptide (C-peptide alone, CP/G and CP/GCr) in order to determine which best serves as a simple test for predicting high levels (>10 mmol/L) of 90 min-Glc after MMTT (graft dysfunction) in islet transplant recipients. We then looked for the association between these measures and islet mass transplanted, 90 min-Glc after MMTT, and clinical outcome as assessed by β-score (6). We present data showing that CP/G is the best predictor for high 90 min-Glc and can identify graft dysfunction. Since this ratio is easy to perform on basal peripheral blood samples we propose its use as a practical tool for the monitoring of islet graft function. Methods Islet transplantation We performed a retrospective analysis on 22 T1DM recipients of allogeneic islet grafts. Patients were enrolled in three different islet transplantation protocols: 14 belonged to the Islet Transplantation Alone (IA) (12), four to the Islet After Kidney (IAK, stable renal grafts for 6 months prior to islet transplantation) and four to islet transplantation with concomitant administration of donor-derived, CD34+-enriched, bone marrow cells (BMC) (13). The studies were approved by the Institutional Review Board. Islets were isolated from human pancreata obtained from deceased, multi-organ donors utilizing a modification of the automated method (14) followed by density gradient purification (15). Islets were transplanted as previously described (12, 13). Steroid-free immunosuppressive regimen consisting of induction with daclizumab (Zenapax®, Roche Nutley, NJ) and maintenance with tacrolimus (Prograf®, Fujisawa Deerfield, IL) and sirolimus (Rapamune, Wyeth-Ayerst Madison, NJ), as described (12, 13, 16). In the IA + BMC recipients, immunosuppression was discontinued 1 year after transplantation. Metabolic assays Serum glucose concentrations were determined by the hexokinase method. Plasma C-peptide was measured by double antibody radioimmunoassay (detection limits: 0.3–5 ng/mL, inter- and intra-assay variation coefficient 10mmol/L) after MMTT in islet transplant recipients. Additionally, we examined the relationship between these measures with islet mass (total IEQ/kg infused, at 7 days, 1 and 3 months post-transplant), and clinical outcome given by the β-score (6). This score ranges from 0 (no graft function) to 8 (good clinical outcome) (6). Time points considered for the metabolic and clinical outcomes included pre-transplant and 3, 6, 9, 12, 15 and 18 months post-last islet infusion. Definitions Insulin independence: C-peptide-positive recipients that were able to maintain HbA1c ≤ 6.5%, without exogenous insulin administration, and their capillary fasting and 2-h post-prandial blood glucose levels were ≤7.8 mmol/L (140 mg/dL) and ≤10mmol/L (180 mg/dL), respectively. Graft dysfunction: C-peptide-positive recipients that presented with fasting capillary glucose >7.8 mmol/L and/or 2-h post-prandial capillary glucose >10.0 mmol/L in three or more occasions in 1 week, requiring the reintroduction of exogenous insulin therapy, confirmed by a 90-min-Glc >10.0 mmol/L after MMTT. Statistical analysis Data from this study are clustered: each patient has measures taken at baseline and at every follow-up time point. Analyses for clustered data are used for all comparisons where appropriate. We compared the diagnostic accuracy of the measures (C-peptide alone, CP/G and CP/GCr) using Receiver operating characteristic (ROC) curves and test statistics presented by Obuchowski (18) for the comparison of correlated ROC curves arising from clustered data. ROC curve methodology provides a good measure of test accuracy, incorporating both sensitivity and specificity and accounting for the inherent trade-offs between them in decision making. Multiple logistic regression for repeated measures with generalized estimating equations (GEE) were used to estimate the associations of CP/G to 90 min-Glc, β-score and insulin use. Linear regression methods for repeated measures were used to assess the relationship between C-peptide measures, 90 min-Glc, AIRglu and β-score. Simple linear regression was used to assess the relationship between C-peptide measures and islet mass at 7 days, 1 and 3 months post-transplant. Two-sample t-tests were used to compare measures involving C-peptide, 90 min-Glc and β-score between insulin-independent and insulin-dependent patients at 15 months post-transplant. P-values 10 mmol/L. CP/G was found to be a superior test associated with a larger area under the ROC curve compared to C-peptide alone (p = 0.01) and CP/GCr (p = 0.06). Relationship between C-peptide and CP/G to 90 min-Glc No significant correlation existed between 90 min-Glc and C-peptide at early times post-transplant (3, 6, 9, 12 and 15 months). We observed a significant correlation at 18 months post-transplant possibly due to graft failure in IA + BMC recipients, after discontinuing immunosuppression at 12 months. The CP/G had a significant negative correlation with 90 min-Glc at all time points (Table 2). Table 2. Correlation between C-peptide measures with 90-minute glucose post-last islet infusion at different time points 90 min-glc vs. time after last infusion n C-peptide alone C-peptide/glucose ratio r P r p 3 months 22 −0.325 0.13 −0.443 <0.05* 6 months 21 −0.414 0.062 −0.513 <0.05* 9 months 22 −0.41 0.058 −0.774 <0.001* 12 months 19 −0.429 0.066 −0.733 <0.001* 15 months 19 −0.312 0.194 −0.498 <0.05* 18 months 15 −0.8 <0.001* −0.84 <0.001* *Statistically significant. Relationships using data from all patients at all time points (n = 140 values) comparing 90 min-Glc to C-peptide and CP/G (Figure 2) showed significant correlation for all values (r =−0.65, p < 0.001; and r =−0.762, p < 0.001, respectively). Figure 2Open in figure viewerPowerPoint Correlation between 90min- glu after MMTT and C-peptide/glucose ratio in 140 tests performed on 22 subjects before and after islet transplantation. Multiple logistic regression for repeated measures, considering all time points, revealed that CP/G 10 mmol/L, OR = 14.02, p < 0.0003). Having a higher β-score (>6) carried a positive association with having higher CP/G (>1.0) (OR = 14.43, p < 0.001). The odds of having lower CP/G (<1.0) are about 4 times greater with exogenous insulin use (OR = 4.65, p < 0.001). The results described above for the association between CP/G and 90 min-Glc were adjusted for insulin use and β-score. Relationship between CP/G, 90 min-Glc and AIRglu Relationships using data from the IA and IAK recipients (n = 18) at all time points (n = 83 values) comparing AIRglu to 90 min-Glc and CP/G showed a significant correlation (r =−0.58, p < 0.001; and r =−0.28, p < 0.01; respectively). C-peptide alone did not correlate with the AIRglu (r = 0.171, p = 0.12). Relationship between infused islet mass and C-peptide and CP/G C-peptide and CP/G had a positive correlation with total IEQ infused at 7 days (r = 0.551, p < 0.01; r = 0.502, p = 0.02, respectively), 1 month (r = 0.599, p < 0.01; r = 0.574, p < 0.01, respectively) and 3 months (r = 0.459, p = 0.02; r = 0.55, p < 0.01, respectively) post-last islet infusion. An increase in 1000 IEQ/kg infused was associated with a 0.08 units in the CP/G (p < 0.01) at 3 months post-last islet infusion. Thus, infusing a total of 14,000 IEQ/kg is associated with an average CP/G of 1.12 at 3 months post-last islet infusion in subjects treated with this immunosuppression regimen. Relationship between C-peptide and CP/G to β-score No correlation was found at any time point between C-peptide and β-score. The CP/G was found to be significantly associated with β-score at 12 months (r = 0.71, p < 0.001) and 15 months (r = 0.666, p = 0.001) post-transplant. When the values for all patients at all time points (n = 140) were analyzed for C-peptide and CP/G a correlation was found between each of these measurements and the β-score (r = 0.627, p < 0.001; r = 0.723, p < 0.001, respectively). Insulin independence at 15 months post-transplant Significant differences were observed when comparing patients maintaining insulin independence at 15 months after the last islet infusion to those requiring exogenous insulin, based on CP/G (1.14 ± 0.21 vs. 0.74 ± 0.41, respectively; p < 0.01), 90 min-Glc after MMTT (6.98 ± 1.16 vs. 13.28 ± 3.21 mmol/L, respectively; p < 0.01) and β-score (7.40 ± 0.55 vs. 4.36 ± 1.73, respectively; p < 0.001). Discussion Development of simple methods to assess islet graft dysfunction and assist with the management of transplanted patients is highly desirable. We evaluated calculations using fasting C-peptide such as CP/G and CP/GCr to assess graft dysfunction. Toward this aim, we assessed which one of these measures best serves as a simple diagnostic test for predicting high levels of 90 min-Glc (>10 mmol/L). The CP/G was found to be a superior diagnostic tool to detect graft dysfunction by predicting a high 90 min-Glc when compared to C-peptide (p = 0.01) and to CP/GCr (p = 0.06). CP/G and C-peptide, correlated with the total mass of islets infused when assessed at 7 days and 1 and 3 months post-transplant, suggesting that these values are useful in the assessment of islet engraftment. CP/G correlated with the proposed measures for β-cell function after islet transplantation (90 min-Glc after MMTT; Figure 2, AIRglu after IVGTT) and with the clinical scoring system (β-score) in islet transplantation (6), suggesting that it represents a valuable surrogate marker of islet graft dysfunction that can be easily monitored in transplanted patients. It is conceivable that CP/GCr would be better to assess islet graft dysfunction in patients with renal disease; however, this hypothesis was not formally addressed in our study, since all subjects had normal and stable renal function. Larger studies in patients with progressive nephropathy will be of assistance to address this issue. The CP/G is a simple test that can be estimated at any time point during the post-transplant period, given the ease of its measurement taken from a single fasting blood sample. It can be used as a parameter of insulin secretion on the basal state and can have an immediate application in the assessment of graft dysfunction after islet transplantation. A high CP/G value provides reassurance that a given patient has adequate islet graft function. A lower value could indicate early graft dysfunction and the requirement of more complicated metabolic and immunologic work-up to guide prompt implementation of anti-rejection and graft rescue therapy. A limitation of this study is the absence of control groups (non-obese, non-diabetic subjects; type 2 diabetes patients with and without kidney disease; kidney–pancreas recipients; non-diabetic kidney alone or other solid organ recipients) that could help dissect the effects of kidney disease and immunosuppressive therapy on C-peptide levels. One limitation of the CP/G ratio is that it does not account for the overall patient metabolic state since it does not focus directly on exogenous insulin use or HbA1c levels. Another limitation is that it does not correct for the degree of insulin sensitivity or resistance. To assess the glucose tolerance state, it is best to calculate insulin secretion, insulin sensitivity and the disposition index by the euglycemic hyperinsulinemic glucose clamp (1), the insulin modified frequently sampled IVGTT (19) or the oral glucose tolerance test described by Cobelli et al. (20). Although the HOMA indices have been used to correlate and extrapolate insulin secretion and sensitivity data obtained from the tests mentioned above, in normal controls and in patients with type 2 diabetes, its use has not been validated on subjects using exogenous insulin or in islet transplant recipients (10). Although HOMA C-peptide β-cell index (HOMA-%B) may be superior to CP/G, both measures correlate remarkably well (r = 0.86, p < 0.001) since they contain the same variables with different constants. One advantage of the HOMA β-cell index over the CP/G is the presence of a threshold glucose level of 3.5 mmol/L (63 mg/dL). Calculation of the CP/G is simpler and is superior to the use of C-peptide alone for the detection of graft dysfunction. Further analysis incorporating measures of insulin resistance into these ratios may improve their overall sensitivity and extend their applications to other clinical settings requiring monitoring of β-cell mass and function. In conclusion, our data show that the CP/G is a simple test, easy to perform, which correlates with the mass of transplanted islets, and which is more indicative of graft dysfunction than using CP/GCr and C-peptide alone. The CP/G correlate well with 90 min-Glc and with the clinical β-score, which are widely used in islet transplantation. The ease of calculation of this ratio and its good correlation with other tests assessing graft dysfunction make it a valuable complement for the monitoring and management of recipients of allogeneic islets. Acknowledgments We express gratitude to the staff of the Clinical Islet Transplant Program, the Islet Cell Processing Center, the General Clinical Research Center and the Informatics Core for their continuous support. We also thank Dr. Andrea Caumo, Dr. Norma S. Kenyon, Dr. Paul Casanova-Romero and Dr. Jay Sosenko for their valuable and stimulating discussion. This study was supported by grants from the National Institutes of Health/NIDDK (R01 DK52802), NCRR (GCRCMO1RR16587; U42RR016603), Juvenile Diabetes Foundation International-JDRFI (4-2004-361), State of Florida and Diabetes Research Institute Foundation. References 1 Ferrannini E, Mari A. Beta cell function and its relation to insulin action in humans: a critical appraisal. Diabetologia 2004; 47: 943– 956. CrossrefCASPubMedWeb of Science®Google Scholar 2 Palmer JP, Fleming GA, Greenbaum CJ et al. C-peptide is the appropriate outcome measure for type 1 diabetes clinical trials to preserve beta-cell function: report of an ADA workshop, 21–22 October 2001. Diabetes 2004; 53: 250– 264. CrossrefCASPubMedWeb of Science®Google Scholar 3 Alejandro R, Lehmann R, Ricordi C et al. Long-term function (6 years) of islet allografts in type 1 diabetes. Diabetes 1997; 46: 1983– 1989. CrossrefCASPubMedWeb of Science®Google Scholar 4 Greenbaum CJ, Harrison LC. Guidelines for intervention trials in subjects with newly diagnosed type 1 diabetes. Diabetes 2003; 52: 1059– 1065. CrossrefCASPubMedWeb of Science®Google Scholar 5 Ryan EA, Lakey JR, Paty BW et al. Successful islet transplantation: continued insulin reserve provides long-term glycemic control. Diabetes 2002; 51: 2148– 2157. CrossrefCASPubMedWeb of Science®Google Scholar 6 Ryan EALJ, Paty BW et al. Beta-score—An assessment of beta-cell function after islet transplantation. Diabetes Care 2005; 28: 343– 347. CrossrefPubMedWeb of Science®Google Scholar 7 Secchi A, Pontiroli AE, Traeger J et al. A method for early detection of graft failure in pancreas transplantation. Transplantation 1983; 35: 344– 348. CrossrefCASPubMedWeb of Science®Google Scholar 8 Matsumoto S, Yamada Y, Okitsu T et al. Simple evaluation of engraftment by secretory unit of islet transplant objects for living donor and cadaveric donor fresh or cultured islet transplantation. Transplant Proc 2005; 37: 3435– 3437. CrossrefCASPubMedWeb of Science®Google Scholar 9 Yamada Y, Fukuda K, Fujimoto S et al. SUIT, secretory units of islets in transplantation: an index for therapeutic management of islet transplanted patients and its application to type 2 diabetes. Diabetes Res Clin Pract 2006; 74: 222– 226. CrossrefCASPubMedWeb of Science®Google Scholar 10 Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004; 27: 1487– 1495. CrossrefPubMedWeb of Science®Google Scholar 11 Zerbini G, Mangili R, Luzi L. Higher post-absorptive C-peptide levels in Type 1 diabetic patients without renal complications. Diabet Med 1999; 16: 1048. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 12 Froud T, Ricordi C, Baidal DA et al. Islet transplantation in type 1 diabetes mellitus using cultured islets and steroid-free immunosuppression: miami experience. Am J Transplant 2005; 5: 2037– 2046. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 13 Pileggi ARC, Kenyon NS, Froud T et al. Twenty years of clinical islet transplantation at the Diabetes Research institute-University of Miami. In: JM Cecka, PI Terasaki (eds). Clinical transplants. Los Angeles: UCLA Immunogenetics Center, 2004: 1– 28. Google Scholar 14 Ricordi C, Lacy PE, Finke EH, Olack BJ, Scharp DW. Automated method for isolation of human pancreatic islets. Diabetes 1988; 37: 413– 420. PubMedWeb of Science®Google Scholar 15 Ichii H, Pileggi A, Molano RD et al. Rescue purification maximizes the use of human islet preparations for transplantation. Am J Transplant 2005; 5: 21– 30. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 16 Shapiro AM, Lakey JR, Ryan EA et al. Islet transplantation in seven patients with type 1 diabetes mellitus using a glucocorticoid-free immunosuppressive regimen. N Engl J Med 2000; 343: 230– 238. CrossrefCASPubMedWeb of Science®Google Scholar 17 Teuscher A, Kendall D, Smets Y, Leone J, Sutherland D, Robertson R. Successful islet autotransplantation in humans: functional insulin secretory reserve as an estimate of surviving islet cell mass. Diabetes 1998; 47: 324– 330. CrossrefCASPubMedWeb of Science®Google Scholar 18 Obuchowski NA. Nonparametric analysis of clustered ROC curve data. Biometrics 1997; 53: 567– 578. CrossrefCASPubMedWeb of Science®Google Scholar 19 Bergman RN, Ader M, Huecking K, Van Citters G. Accurate assessment of beta-cell function: the hyperbolic correction. Diabetes 2002; 51(Suppl 1): S212– 220. CrossrefCASPubMedWeb of Science®Google Scholar 20 Dalla Man C, Caumo A, Basu R, Rizza R, Toffolo G, Cobelli C. Minimal model estimation of glucose absorption and insulin sensitivity from oral test: validation with a tracer method. Am J Physiol Endocrinol Metab 2004; 287: E637– E643. CrossrefCASPubMedWeb of Science®Google Scholar Citing Literature Volume7, Issue2February 2007Pages 303-308 AST and ASTS members - please log in via your Society website for full journal access.AST Members >> ASTS Members >> FiguresReferencesRelatedInformation