Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach
A standardized approach to assessing islet autotransplantation outcomes is crucial for evaluating graft function and guiding clinical decisions. This study compares the performance of existing classification systems—Milan, Minneapolis, Chicago, Leicester, Igls, and a novel Data-Driven approach—by ev...
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| Format: | Article |
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Frontiers Media S.A.
2025-07-01
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| Series: | Transplant International |
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| Online Access: | https://www.frontierspartnerships.org/articles/10.3389/ti.2025.14714/full |
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| author | Davide Catarinella Paola Magistretti Raffaella Melzi Alessia Mercalli Stefano Tentori Chiara Gremizzi Vera Paloschi Simona Sala Libera Valla Francesca Aleotti Sabrina Costa Francesco De Cobelli Francesco De Cobelli Rossana Caldara Lorenzo Piemonti Lorenzo Piemonti |
| author_facet | Davide Catarinella Paola Magistretti Raffaella Melzi Alessia Mercalli Stefano Tentori Chiara Gremizzi Vera Paloschi Simona Sala Libera Valla Francesca Aleotti Sabrina Costa Francesco De Cobelli Francesco De Cobelli Rossana Caldara Lorenzo Piemonti Lorenzo Piemonti |
| author_sort | Davide Catarinella |
| collection | DOAJ |
| description | A standardized approach to assessing islet autotransplantation outcomes is crucial for evaluating graft function and guiding clinical decisions. This study compares the performance of existing classification systems—Milan, Minneapolis, Chicago, Leicester, Igls, and a novel Data-Driven approach—by evaluating their ability to differentiate transplant outcomes using metabolic and insulin secretion parameters. Our analysis shows strong concordance among Milan, Minneapolis, Chicago, and Igls, primarily due to minor variations in C-peptide thresholds. The Leicester and Data-Driven systems, however, exhibit greater divergence, with the Leicester system simplifying assessment by excluding severe hypoglycemic events and HbA1c, and the Data-Driven approach offering a more dynamic framework without predefined thresholds. Fasting C-peptide levels emerged as a highly reliable predictor of graft function, with the arginine test proving more effective than Mixed Meal Tolerance Test for additional evaluation. The Data-Driven approach provided superior stratification of outcomes, highlighting the importance of residual insulin secretion in metabolic control. These findings suggest that refining classification systems, particularly by considering insulin sensitivity and residual secretion, could enhance long-term patient monitoring and improve our understanding of beta-cell replacement therapies. Further validation across diverse cohorts is essential for broader clinical adoption. |
| format | Article |
| id | doaj-art-27d1c96a0fc3485fa43bf97f7a05c831 |
| institution | Kabale University |
| issn | 1432-2277 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Transplant International |
| spelling | doaj-art-27d1c96a0fc3485fa43bf97f7a05c8312025-08-20T03:51:09ZengFrontiers Media S.A.Transplant International1432-22772025-07-013810.3389/ti.2025.1471414714Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven ApproachDavide Catarinella0Paola Magistretti1Raffaella Melzi2Alessia Mercalli3Stefano Tentori4Chiara Gremizzi5Vera Paloschi6Simona Sala7Libera Valla8Francesca Aleotti9Sabrina Costa10Francesco De Cobelli11Francesco De Cobelli12Rossana Caldara13Lorenzo Piemonti14Lorenzo Piemonti15Clinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyClinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyClinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyClinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyClinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyPancreatic Surgery, Pancreas Translational and Clinical Research Center, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Radiology, Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan, ItalyUniversità Vita-Salute San Raffaele, Milan, ItalyClinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyClinic Unit of Regenerative Medicine and Organ Transplants, IRCCS Ospedale San Raffaele, Milan, ItalyUniversità Vita-Salute San Raffaele, Milan, ItalyA standardized approach to assessing islet autotransplantation outcomes is crucial for evaluating graft function and guiding clinical decisions. This study compares the performance of existing classification systems—Milan, Minneapolis, Chicago, Leicester, Igls, and a novel Data-Driven approach—by evaluating their ability to differentiate transplant outcomes using metabolic and insulin secretion parameters. Our analysis shows strong concordance among Milan, Minneapolis, Chicago, and Igls, primarily due to minor variations in C-peptide thresholds. The Leicester and Data-Driven systems, however, exhibit greater divergence, with the Leicester system simplifying assessment by excluding severe hypoglycemic events and HbA1c, and the Data-Driven approach offering a more dynamic framework without predefined thresholds. Fasting C-peptide levels emerged as a highly reliable predictor of graft function, with the arginine test proving more effective than Mixed Meal Tolerance Test for additional evaluation. The Data-Driven approach provided superior stratification of outcomes, highlighting the importance of residual insulin secretion in metabolic control. These findings suggest that refining classification systems, particularly by considering insulin sensitivity and residual secretion, could enhance long-term patient monitoring and improve our understanding of beta-cell replacement therapies. Further validation across diverse cohorts is essential for broader clinical adoption.https://www.frontierspartnerships.org/articles/10.3389/ti.2025.14714/fullislet autotransplantationgraft functionclassification systemsC-peptideinsulin secretion |
| spellingShingle | Davide Catarinella Paola Magistretti Raffaella Melzi Alessia Mercalli Stefano Tentori Chiara Gremizzi Vera Paloschi Simona Sala Libera Valla Francesca Aleotti Sabrina Costa Francesco De Cobelli Francesco De Cobelli Rossana Caldara Lorenzo Piemonti Lorenzo Piemonti Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach Transplant International islet autotransplantation graft function classification systems C-peptide insulin secretion |
| title | Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach |
| title_full | Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach |
| title_fullStr | Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach |
| title_full_unstemmed | Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach |
| title_short | Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach |
| title_sort | comparative analysis of islet auto transplantation outcome classification systems evaluating concordance feasibility and a data driven approach |
| topic | islet autotransplantation graft function classification systems C-peptide insulin secretion |
| url | https://www.frontierspartnerships.org/articles/10.3389/ti.2025.14714/full |
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