Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk of (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care.

Type 1 Diabetes Continuous Glucose Monitoring Use in the Pediatric Emergency Department Affects Laboratory Test Frequency but Not Treatment Timing.

Regular use of continuous glucose monitoring (CGM) in type 1 diabetes management increases the achievement of glycemic targets and reduces health care utilization, specifically emergency department (ED) visits. This retrospective chart review examined the effects of CGM use in patients with type 1 diabetes in a pediatric ED. Use of CGM was associated with several differences in patient management in the ED. This work is a first step toward development of guidelines for the appropriate use of CGM in the pediatric ED. In the future, CGM use in type 1 diabetes may lead to reduced ED-specific health care costs.

Factors Associated With Achieving Target A1C in Children and Adolescents With Type 1 Diabetes: Findings From the T1D Exchange Quality Improvement Collaborative.

The optimal care of type 1 diabetes involves consistent glycemic management to avoid short- and long-term complications. However, despite advancements in diabetes technology and standards, achieving adequate glycemic levels in children and adolescents remains a challenge. This study aimed to identify factors associated with achieving the recommended A1C target of <7% from the United States-based multicenter T1D Exchange Quality Improvement Collaborative cohort, including 25,383 children and adolescents living with type 1 diabetes.

Making Diabetes Electronic Medical Record Data Actionable: Promoting Benchmarking and Population Health Improvement Using the T1D Exchange Quality Improvement Portal.

This article describes how the T1D Exchange Quality Improvement Collaborative leverages an innovative web platform, the QI Portal, to gather and store electronic medical record (EMR) data to promote benchmarking and population health improvement in a type 1 diabetes learning health system. The authors explain the value of the QI Portal, the process for mapping center-level data from EMRs using standardized data specifications, and the QI Portal's unique features for advancing population health.

Learning experience design of an mHealth self-management intervention for adolescents with type 1 diabetes.

Type 1 diabetes (T1D) is a lifelong and chronic condition that can cause severely compromised health. The T1D treatment regimen is complex, and is a particular challenge for adolescents, who frequently experience a number of treatment adherence barriers (e.g., forgetfulness, planning and organizational challenges, stress). Diabetes Journey is a gamified mHealth program designed to improve T1D self-management through a specific focus on decreasing adherence barriers and improving executive functioning skills for adolescents. Grounded in situativity theory and guided by a sociotechnical-pedagogical usability framework, Diabetes Journey was designed, developed, and evaluated using a learning experience design approach. This approach applied design thinking methods within a Successive Approximation Model design process. Iterative design and formative evaluation were conducted across three design phases, and improvements were implemented following each phase. Findings from the user testing phase indicate Diabetes Journey is a user-friendly mHealth program with high usability that holds promise for enhancing adolescents' T1D self-management. Implications for future designers and researchers are discussed regarding the social dimension of the sociotechnical-pedagogical usability framework. An extension to the framework is proposed to extend the social dimension to include socio-cultural and contextual considerations when designing mHealth applications. Consideration of the pedagogical and sociocultural dimensions of learning is imperative when developing psychoeducational interventions.

Index60 as an additional diagnostic criterion for type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both. METHODS: We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165]. RESULTS: Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%). CONCLUSIONS/INTERPRETATION: Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.

Barriers to retinopathy screening in youth and young adults with type 1 diabetes.

Early detection of diabetic retinopathy (DR) is imperative; however, adherence to screening guidelines is poor. We hypothesized that youth and young adults with type 1 diabetes (T1D) who met American Diabetes Association criteria for recommended DR screening at the time of the study (10 years old or greater with diabetes duration of 5 years or more) would report multiple barriers to screening and that targeted barriers and subpopulations could be identified to improve access to care. 271 youth aged 10 to 26 years with T1D of at least 5 years duration were recruited from clinic, diabetes camp, and a diabetes conference and completed a patient-reported questionnaire. 113 (41.7%) reported at least one barrier to DR screening, with missed school and work being the most common (20.7%). Older participants (P = 0.007) and those with a longer diabetes duration (P = 0.018) were more likely to report barriers to screening. Recruitment location, sex, race and ethnicity, HbA1c, insulin regimen, and clinic visit frequency were not associated with reporting at least one barrier. Slightly less than two-thirds (62.1%) of participants who responded (n = 235 out of 271) adhered to recommended screening guidelines of the time and reported having an eye exam within the past year, 24.7% 12-23 months ago, 9.8% 2 years ago or more, and 3.4% had never had a DR exam. As older patients and those with longer duration of diabetes are more likely to have DR, targeted interventions to address barriers to care, such as, missed school and work should be implemented in these groups.

Real-World Screening for Retinopathy in Youth With Type 1 Diabetes Using a Nonmydriatic Fundus Camera.

OBJECTIVE: To assess the use of a portable retinal camera in diabetic retinopathy (DR) screening in multiple settings and the presence of associated risk factors among children, adolescents, and young adults with type 1 diabetes. DESIGN AND METHODS: Five hundred youth with type 1 diabetes of at least 1 year's duration were recruited from clinics, diabetes camp, and a diabetes conference and underwent retinal imaging using a nonmydriatic fundus camera. Retinal characterization was performed remotely by a licensed ophthalmologist. Risk factors for DR development were evaluated by a patient-reported questionnaire and medical chart review. RESULTS: Of the 500 recruited subjects aged 9-26 years (mean 14.9, SD 3.8), 10 cases of DR were identified (nine mild and one moderate nonproliferative DR) with 100% of images of gradable quality. The prevalence of DR was 2.04% (95% CI 0.78-3.29), at an average age of 20.2 years, with the youngest affected subject being 17.1 years of age. The rate of DR was higher, at 6.5%, with diabetes duration >10 years (95% CI 0.86-12.12, P = 0.0002). In subjects with DR, the average duration of diabetes was 12.1 years (SD 4.6, range 6.2-20.0), and in a subgroup of clinic-only subjects (n = 114), elevated blood pressure in the year before screening was associated with DR (P = 0.0068). CONCLUSION: This study in a large cohort of subjects with type 1 diabetes demonstrates that older adolescents and young adults (>17 years) with longer disease duration (>6 years) are at risk for DR development, and screening using a portable retinal camera is feasible in clinics and other locations. Recent elevated blood pressure was a risk factor in an analyzed subgroup.

The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening.

AIMS/HYPOTHESIS: Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. METHODS: Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. RESULTS: Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. CONCLUSIONS/INTERPRETATION: Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.

Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children.

OBJECTIVE: The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. METHODS: Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A). RESULTS: A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models. CONCLUSIONS: This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches.

Immune Mechanisms and Pathways Targeted in Type 1 Diabetes.

PURPOSE OF REVIEW: The immunosuppressive agent cyclosporine was first reported to lower daily insulin dose and improve glycemic control in patients with new-onset type 1 diabetes (T1D) in 1984. While renal toxicity limited cyclosporine's extended use, this observation ignited collaborative efforts to identify immunotherapeutic agents capable of safely preserving ß cells in patients with or at risk for T1D. RECENT FINDINGS: Advances in T1D prediction and early diagnosis, together with expanded knowledge of the disease mechanisms, have facilitated trials targeting specific immune cell subsets, autoantigens, and pathways. In addition, clinical responder and non-responder subsets have been defined through the use of metabolic and immunological readouts. Herein, we review emerging T1D biomarkers within the context of recent and ongoing T1D immunotherapy trials. We also discuss responder/non-responder analyses in an effort to identify therapeutic mechanisms, define actionable pathways, and guide subject selection, drug dosing, and tailored combination drug therapy for future T1D trials.

T Cell Receptor Profiling in Type 1 Diabetes.

PURPOSE OF REVIEW: The genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate ß-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility. RECENT FINDINGS: Advances in acquisition of pancreata and islets from T1D organ donors have facilitated studies of T cells isolated from the target tissues. Immunosequencing of TCR α/ß-chain complementarity determining regions, along with transcriptional profiling, offers the potential to transform biomarker discovery. Herein, we review recent studies characterizing the autoreactive TCR signature in T1D, emerging technologies, and the challenges and opportunities associated with tracking TCR molecular profiles during the natural history of T1D.

Low-Dose Antithymocyte Globulin: A Pragmatic Approach to Treating Stage 2 Type 1 Diabetes.

OBJECTIVE: Low-dose antithymocyte globulin (ATG) (2.5 mg/kg) preserves C-peptide and reduces HbA1c in new-onset stage 3 type 1 diabetes, yet efficacy in delaying progression from stage 2 to stage 3 has not been evaluated. RESEARCH DESIGN AND METHODS: Children (n = 6) aged 5-14 years with stage 2 type 1 diabetes received off-label, low-dose ATG. HbA1c, C-peptide, continuous glucose monitoring, insulin requirements, and side effects were followed for 18-48 months. RESULTS: Three subjects (50%) remained diabetes free after 1.5, 3, and 4 years of follow-up, while three developed stage 3 within 1-2 months after therapy. Eighteen months posttreatment, even disease progressors demonstrated near-normal HbA1c (5.1% [32 mmol/mol], 5.6% [38 mmol/mol], and 5.3% [34 mmol/mol]), time in range (93%, 88%, and 98%), low insulin requirements (0.17, 0.18, and 0.34 units/kg/day), and robust C-peptide 90 min after mixed meal (1.3 ng/dL, 2.3 ng/dL, and 1.4 ng/dL). CONCLUSIONS: These observations support additional prospective studies evaluating ATG in stage 2 type 1 diabetes.

Early Metabolic Endpoints Identify Persistent Treatment Efficacy in Recent-Onset Type 1 Diabetes Immunotherapy Trials.

OBJECTIVE: Mixed-meal tolerance test-stimulated area under the curve (AUC) C-peptide at 12-24 months represents the primary end point for nearly all intervention trials seeking to preserve ß-cell function in recent-onset type 1 diabetes. We hypothesized that participant benefit might be detected earlier and predict outcomes at 12 months posttherapy. Such findings would support shorter trials to establish initial efficacy. RESEARCH DESIGN AND METHODS: We examined data from six Type 1 Diabetes TrialNet immunotherapy randomized controlled trials in a post hoc analysis and included additional stimulated metabolic indices beyond C-peptide AUC. We partitioned the analysis into successful and unsuccessful trials and analyzed the data both in the aggregate as well as individually for each trial. RESULTS: Among trials meeting their primary end point, we identified a treatment effect at 3 and 6 months when using C-peptide AUC (P = 0.030 and P < 0.001, respectively) as a dynamic measure (i.e., change from baseline). Importantly, no such difference was seen in the unsuccessful trials. The use of C-peptide AUC as a 6-month dynamic measure not only detected treatment efficacy but also suggested long-term C-peptide preservation (R2 for 12-month C-peptide AUC adjusted for age and baseline value was 0.80, P < 0.001), and this finding supported the concept of smaller trial sizes down to 54 participants. CONCLUSIONS: Early dynamic measures can identify a treatment effect among successful immune therapies in type 1 diabetes trials with good long-term prediction and practical sample size over a 6-month period. While external validation of these findings is required, strong rationale and data exist in support of shortening early-phase clinical trials.

Erratum. Consensus Guidance for Monitoring Individuals With Islet Autoantibody-Positive Pre-Stage 3 Type 1 Diabetes. Diabetes Care 2024;47:1276-1298.

In the article cited above, incorrect affiliation information was given for author Linda A. DiMeglio. The correct affiliation for Linda A. DiMeglio is Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN. The online version of the article (https://doi.org/10.2337/dci24-0042) has been updated to correct the error.

Consensus Guidance for Monitoring Individuals With Islet Autoantibody-Positive Pre-Stage 3 Type 1 Diabetes.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programs are being increasingly emphasized. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk for (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in nonspecialized settings. To inform this monitoring, JDRF, in conjunction with international experts and societies, developed consensus guidance. Broad advice from this guidance includes the following: 1) partnerships should be fostered between endocrinologists and primary care providers to care for people who are IAb+; 2) when people who are IAb+ are initially identified, there is a need for confirmation using a second sample; 3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; 4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; 5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and 6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasizes significant unmet needs for further research on early-stage type 1 diabetes to increase the rigor of future recommendations and inform clinical care.

Longitudinal Trends in Glycemic Outcomes and Technology Use for Over 48,000 People with Type 1 Diabetes (2016-2022) from the T1D Exchange Quality Improvement Collaborative.

Objective: Previous studies revealed that hemoglobin A1c (HbA1c) increased overall in the United States in the past decade. In addition, health inequities in type 1 diabetes (T1D) outcomes by race/ethnicity and insurance type persist. This study examines the trends in HbA1c from 2016 to 2022 stratified by race/ethnicity and insurance in a large multicenter national database. Research Design and Methods: We analyzed glycemic outcomes and diabetes device use trends for >48,000 people living with type 1 diabetes (PwT1D) from 3 adult and 12 pediatric centers in the T1D Exchange Quality Improvement Collaborative (T1DX-QI), comparing data from 2016 to 2017 with data from 2021 to 2022. Results: The mean HbA1c in 2021-2022 was lower at 8.4% compared with the mean HbA1c in 2016-2017 of 8.7% (0.3% improvement; P < 0.01). Over the same period, the percentage of PwT1D using a continuous glucose monitor (CGM), insulin pump, or hybrid closed-loop system increased (45%, 12%, and 33%, respectively). However, these improvements were not equitably demonstrated across racial/ethnic groups or insurance types. Racial/ethnic and insurance-based inequities persisted over all 7 years across all outcomes; comparing non-Hispanic White and non-Hispanic Black PwT1D, disparate gaps in HbA1c (1.2%-1.6%), CGM (30%), pump (25%-35%), and hybrid-closed loop system (up to 20%) are illuminated. Conclusion: Population-level data on outcomes, including HbA1c, can provide trends and insights into strategies to improve health for PwT1D. The T1DX-QI cohort showed a significant improvement in HbA1c from 2016 to 2022. Improvements in diabetes device use are also demonstrated. However, these increases were inconsistent across all racial/ethnic groups or insurance types, an important focus for future T1D population health improvement work.

Phenotypes Associated With Zones Defined by Area Under the Curve Glucose and C-peptide in a Population With Islet Autoantibodies.

OBJECTIVE: Metabolic zones were developed to characterize heterogeneity of individuals with islet autoantibodies. RESEARCH DESIGN AND METHODS: Baseline 2-h oral glucose tolerance test data from 6,620 TrialNet Pathway to Prevention Study (TNPTP) autoantibody-positive participants (relatives of individuals with type 1 diabetes) were used to form 25 zones from five area under the curve glucose (AUCGLU) rows and five area under the curve C-peptide (AUCPEP) columns. Zone phenotypes were developed from demographic, metabolic, autoantibody, HLA, and risk data. RESULTS: As AUCGLU increased, changes of glucose and C-peptide response curves (from mean glucose and mean C-peptide values at 30, 60, 90, and 120 min) were similar within the five AUCPEP columns. Among the zones, 5-year risk for type 1 diabetes was highly correlated with islet antigen 2 antibody prevalence (r = 0.96, P < 0.001). Disease risk decreased markedly in the highest AUCGLU row as AUCPEP increased (0.88-0.41; P < 0.001 from lowest AUCPEP column to highest AUCPEP column). AUCGLU correlated appreciably less with Index60 (an indicator of insulin secretion) in the highest AUCPEP column (r = 0.33) than in other columns (r ≥ 0.78). AUCGLU was positively related to "fasting glucose × fasting insulin" and to "fasting glucose × fasting C-peptide" (indicators of insulin resistance) before and after adjustments for Index60 (P < 0.001). CONCLUSIONS: Phenotypes of 25 zones formed from AUCGLU and AUCPEP were used to gain insights into type 1 diabetes heterogeneity. Zones were used to examine GCRC changes with increasing AUCGLU, associations between risk and autoantibody prevalence, the dependence of glucose as a predictor of risk according to C-peptide, and glucose heterogeneity from contributions of insulin secretion and insulin resistance.