Advancements and challenges in pancreatic islet transplantation: Insights from the Collaborative Islet Transplant Registry
Bibliographic record
Abstract
Since the seminal success of Edmonton protocol in 2000, pancreatic islet transplantation has been very actively pursued worldwide1. This breakthrough has provided considerable encouragement to patients affected with type 1 diabetes, particularly those experiencing severe hypoglycemia and poor glycemic control, as well as healthcare professionals dedicated to their treatment. As of the latest report, over 1,300 patients have undergone pancreatic islet transplantation2. Notably, several recent studies have presented long-term follow-up results extending beyond 10 or even 20 years2. Despite these advancements, the field faces a significant challenge stemming from the diverse criteria employed across studies for assessing graft survival and transplantation success. This challenge is exacerbated by disparate transplantation protocols and confinement of studies to specific countries or institutions, hindering a comprehensive assessment of transplantation responses and the identification of prognostic factors. To integrate and compile data from islet transplantation, the Collaborative Islet Transplant Registry (CITR) was established in 2001, with participation from more than 39 centers across over 10 countries to date2. Over the past two decades, this expansive registry has played a crucial role in aggregating islet transplantation data, significantly advancing our understanding of this therapeutic approach. This year, the CITR has reported three pivotal studies based on the accumulation and long-term analysis of this extensive dataset (Table 1)2-4. Primary outcome Secondary outcome High predictability of C-peptide for primary outcome The higher the C-peptide level, the greater the likelihood of achieving each outcome Cut-off value of C-peptide for optimal graft function: ≥1.0 ng/mL Outperformance of the mixed-meal tolerance test-stimulated C-peptide-to-glucose ratio in predictive ability for all primary outcomes except absence of SHEs, compared with both fasting and stimulated C-peptide First, Bernhard Hering and colleagues4 provided important clinical insights into transplantation protocols and post-transplant management by proposing a common set of four favorable factors. This study involved an extensive and thorough exploration, encompassing various affecting factors such as recipient/donor characteristics, islet graft properties, and immunosuppression methods. Four factors were identified with the highest predictive power, including recipient age of 35years or older, total infused islets of 325,000 islet equivalents or more, induction of immunosuppression with T cell depletion and/or tumor necrosis factor-alpha (TNF-α) inhibition, and maintenance with both the mechanistic target of rapamycin (mTOR) and a calcineurin inhibitor with the highest predictive power. Importantly, with the exception of age, these factors are modifiable and amenable to intervention. Secondly, David Baidal et al.3 observed a robust correlation between clinical outcomes and concurrent measurements of fasting and stimulated C-peptide levels, along with the C-peptide-to-glucose ratio. This finding implies that retention of C-peptide function should be regarded as another potential goal of islet transplantation. Lastly, in The Lancet Diabetes & Endocrinology, Mikaël Chetboun et al.2 reported the primary graft function (PGF; islet graft function after islet the last islet infusion) and 5 year outcome results. They utilized the BETA-2 score (derived from fasting C-peptide, fasting plasma glucose, HbA1c, and insulin dose expressed as continuous variables), based on 28 days after last islet transplantation, as an indicator to predict the 5 year success rate of islet transplantation2. This is significant as it introduces an indicator for predicting the success rate of transplantation, which, until now, either did not exist or was challenging to apply in practice due to diverse standards in various studies. Notably, the correlation analysis between PGF and long-term outcome considered all possible confounding factors, enhancing the reliability and verification power of the study, given its multi-center nature involving more than 1,000 transplants. It is important to note that the PGF was evaluated at 28 days after the last islet infusion. As the authors have already mentioned2, this timeframe is considered appropriate, taking into account graft engraftment and vascularization. Additionally, it could allow sufficient time for stabilizing glucose homeostasis after transplantation. Previous studies have measured the BETA-2 score at 3 months or continuously after islet transplantation to analyze its relationship with transplantation outcomes5. However, given the rapid decline in graft function during the first month after transplantation and a gradual decrement thereafter5, the 1-month time point suggested in this study appears to be appropriate for evaluating graft function to predict clinical outcomes. Lastly, they are unveiling a prediction model based on the results of this study (accessible on http://pgf.diabinnov.com/), providing crucial information for predicting the prognosis after islet transplantation, determining the need for additional islet transplantation, and offering valuable guidance to healthcare professionals and patients before and after islet transplantation. It is imperative to emphasize that the BETA-2 score at 28 days after transplantation is derived from the composite outcomes of various donor and recipient factors, encompassing islet number and function, immune responses, metabolic factors, and even unknown or poorly measured elements. Therefore, considering a multivariate analysis incorporating PGF in the model, it is necessary to reevaluate their conclusion that the number of islet infusions and the transplanted islet mass had no significant impact on major clinical outcomes. While the BETA-2 score can serve as a useful indicator for assessing graft function and predicting long-term outcomes, successful islet transplantation still requires meticulous preparation and vigilant post-transplant management, addressing factors ranging from islet number, mass, and function to post-transplant immunosuppressants1, 3. Chetboun et al.2 applied the Igls 2.0 criteria (revised from the original version), which distinguishes clinical outcomes based on glucose regulation from beta cell graft function using C-peptide and insulin requirement. Consequently, they excluded insulin dependence from the category of unsuccessful islet transplantation but considered fasting C-peptide as low as 0.2 ng/mL as a favorable outcome. This aspect warrants careful attention when interpreting their findings. As noted in another CITR report this year, the retention of C-peptide is closely tied to outcomes such as metabolic restoration, loss of severe hypoglycemic events (defined as hypoglycemia associated with loss of consciousness or requiring third-party assistance for recovery), and achieving insulin independence3. Despite the use of more lenient criteria for defining unsuccessful islet transplantation, the 5 year transplant success rate in this integrated registry remains below 30%. If more stringent parameters, such as insulin independence or a significant reduction in insulin requirement as suggested in the initial Igls criteria (a consensus definition for outcomes of beta cell replacement therapy in the treatment of diabetes from the international pancreas and islet transplantation association (IPITA)/European pancreas and islet transplantation (EPITA), consisting of four factors: HbA1c, severe hypoglycemia, insulin requirement, and C-peptide), and a higher C-peptide level (at least 0.3 ng/mL or more) are employed, the success rate could be anticipated to be even lower. This underscores that, despite significant progress in pancreatic islet transplantation, there is still considerable more room for improvement in achieving successful islet transplantation in the future. Over the past two decades, remarkable advancements have transpired in islet transplantation. The outcomes delineated by the CITR, spanning this period and involving more than 30 centers, provide valuable insights that could significantly contribute to the broader adoption of islet transplantation. We are now able to systematically address common favorable factors associated with successful transplantation outcomes, and there is a growing recognition that maintaining C-peptide levels after transplantation may be another critical goal for successful outcomes. Furthermore, it is now pertinent to deliberate the utilization of the BETA-2 score, measured at 28 days after islet transplantation, as a pivotal tool for guiding re-transplantation decisions in patients. Prospective clinical trials are warranted to explore the BETA-2 score threshold at 28 days, guiding re-transplantation decisions, assessing the target goal of graft function, and validating these findings across diverse ethnic groups including Asian populations. In addition to benefiting from this extensive registry data, the development of modalities capable of assessing islet function before transplantation, such as islets-on-chip, along with the advancement of innovative immunomodulatory approaches, may pave the way for more successful islet transplantation in the future. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1C1C1013016) to E.Y.L.; by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health &Welfare, Republic of Korea (grant number: HI13C0954) and Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01345301) Rural Development Administration, Republic of Korea to K.H.Y. Editorial services were provided by Caron Modeas, Evolved Editing, LLC. Kun-Ho Yoon is an Editorial Board member of Journal of Diabetes Investigation and a co-author of this article. To minimize bias, they were excluded from all editorial decision-making related to the acceptance of this article for publication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".