ABSTRACT
AIMS/HYPOTHESIS: We aimed to determine whether disease severity was reduced at onset of clinical (stage 3) type 1 diabetes in children previously diagnosed with presymptomatic type 1 diabetes in a population-based screening programme for islet autoantibodies. METHODS: Clinical data obtained at diagnosis of stage 3 type 1 diabetes were evaluated in 128 children previously diagnosed with presymptomatic early-stage type 1 diabetes between 2015 and 2022 in the Fr1da study and compared with data from 736 children diagnosed with incident type 1 diabetes between 2009 and 2018 at a similar age in the DiMelli study without prior screening. RESULTS: At the diagnosis of stage 3 type 1 diabetes, children with a prior early-stage diagnosis had lower median HbA1c (51 mmol/mol vs 91 mmol/mol [6.8% vs 10.5%], p<0.001), lower median fasting glucose (5.3 mmol/l vs 7.2 mmol/l, p<0.05) and higher median fasting C-peptide (0.21 nmol/l vs 0.10 nmol/l, p<0.001) compared with children without previous early-stage diagnosis. Fewer participants with prior early-stage diagnosis had ketonuria (22.2% vs 78.4%, p<0.001) or required insulin treatment (72.3% vs 98.1%, p<0.05) and only 2.5% presented with diabetic ketoacidosis at diagnosis of stage 3 type 1 diabetes. Outcomes in children with a prior early-stage diagnosis were not associated with a family history of type 1 diabetes or diagnosis during the COVID-19 pandemic. A milder clinical presentation was observed in children who participated in education and monitoring after early-stage diagnosis. CONCLUSIONS/INTERPRETATION: Diagnosis of presymptomatic type 1 diabetes in children followed by education and monitoring improved clinical presentation at the onset of stage 3 type 1 diabetes.
Subject(s)
COVID-19 , Diabetes Mellitus, Type 1 , Humans , Child , Diabetes Mellitus, Type 1/diagnosis , Diabetes Mellitus, Type 1/epidemiology , Diabetes Mellitus, Type 1/drug therapy , Pandemics , Public Health , Insulin/therapeutic useABSTRACT
AIMS/HYPOTHESIS: The aim of this study was to develop strategies that identify children from the general population who have late-stage presymptomatic type 1 diabetes and may, therefore, benefit from immune intervention. METHODS: We tested children from Bavaria, Germany, aged 1.75-10 years, enrolled in the Fr1da public health screening programme for islet autoantibodies (n=154,462). OGTT and HbA1c were assessed in children with multiple islet autoantibodies for diagnosis of presymptomatic stage 1 (normoglycaemia) or stage 2 (dysglycaemia) type 1 diabetes. Cox proportional hazards and penalised logistic regression of autoantibody, genetic, metabolic and demographic information were used to develop a progression likelihood score to identify children with stage 1 type 1 diabetes who progressed to stage 3 (clinical) type 1 diabetes within 2 years. RESULTS: Of 447 children with multiple islet autoantibodies, 364 (81.4%) were staged. Undiagnosed stage 3 type 1 diabetes, presymptomatic stage 2, and stage 1 type 1 diabetes were detected in 41 (0.027% of screened children), 30 (0.019%) and 293 (0.19%) children, respectively. The 2 year risk for progression to stage 3 type 1 diabetes was 48% (95% CI 34, 58) in children with stage 2 type 1 diabetes (annualised risk, 28%). HbA1c, islet antigen-2 autoantibody positivity and titre, and the 90 min OGTT value were predictors of progression in children with stage 1 type 1 diabetes. The derived progression likelihood score identified substages corresponding to ≤90th centile (stage 1a, n=258) and >90th centile (stage 1b, n=29; 0.019%) of stage 1 children with a 4.1% (95% CI 1.4, 6.7) and 46% (95% CI 21, 63) 2 year risk of progressing to stage 3 type 1 diabetes, respectively. CONCLUSIONS/INTERPRETATION: Public health screening for islet autoantibodies found 0.027% of children to have undiagnosed clinical type 1 diabetes and 0.038% to have undiagnosed presymptomatic stage 2 or stage 1b type 1 diabetes, with 50% risk to develop clinical type 1 diabetes within 2 years.
Subject(s)
Diabetes Mellitus, Type 1 , Islets of Langerhans , Child , Humans , Diabetes Mellitus, Type 1/epidemiology , Islets of Langerhans/metabolism , Public Health , Autoantibodies , Mass Screening , Disease ProgressionABSTRACT
BACKGROUND: Islet autoimmunity commonly develops early in infancy. We assessed whether specific parameters of early growth (including weight gain) were associated with the development of islet autoimmunity in children of type 1 diabetes patients, taking individual developmental patterns into account. METHODS: Growth parameters were estimated in n = 1011 children followed from birth in the prospective BABYDIAB and BABYDIET studies using longitudinal models. Cox proportional hazard models, adjusted for study, sex, gestational age, birth weight percentile, and maternal type 1 diabetes status, were calculated to assess hazard ratios (HR) for islet autoimmunity with corresponding 95% confidence intervals (95% CI) by 2 SD increases in growth parameters. In a subset of n = 170 infants, we investigated whether the growth hormones insulin-like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein-3 (IGFBP-3) were in the causal pathway. RESULTS: We found an early age at infant body mass index (BMI) peak to be associated with the development of islet autoimmunity [HR 0.60 (95% CI 0.41-0.87), per 2 SD increase in age]. Islet autoimmunity was also associated with BMI difference between infant BMI peak and childhood BMI rebound [HR 1.52 (95% CI 1.04-2.22)], but not after adjustment for age at infant BMI peak, and not with other parameters such as peak height and weight velocity during infancy. Serum concentrations of IGF-1 and IGFBP-3 at birth, 9 months, and 2 yr, respectively, were not significantly different between children with and without later islet autoimmunity. CONCLUSIONS: Variations in early growth rate have subtle effects on the risk of islet autoimmunity with growth hormones unlikely to be in the causal pathway.
Subject(s)
Autoimmunity , Child Development , Diabetes Mellitus, Type 1/immunology , Insulin-Like Growth Factor Binding Protein 3/blood , Insulin-Like Growth Factor I/analysis , Islets of Langerhans/immunology , Body Mass Index , Cohort Studies , Diabetes Mellitus, Type 1/blood , Diabetes Mellitus, Type 1/epidemiology , Diabetes Mellitus, Type 1/genetics , Female , Genetic Predisposition to Disease , Germany/epidemiology , Humans , Infant, Newborn , Longitudinal Studies , Male , Parents , Proportional Hazards Models , Prospective Studies , Risk , Weight GainABSTRACT
Background: Retention of study participants in observational studies is essential to maintaining the representativeness of the population, minimizing selection bias, and assuring sufficient statistical power. The aim of this report is to describe the structures and strategies used to retain participants in The Environmental Determinants of Diabetes in the Young (TEDDY) Study, an observational study of children at increased genetic risk for type 1 diabetes followed in an intense protocol with frequent clinic visits from birth until age 15. Methods: A systematic review of methodologies used to retain research subjects identified four domains: barrier reduction strategies; community building strategies; follow-up/reminder strategies; and tracing strategies. Independent reviewers categorized the retention strategies implemented by the TEDDY Study into each of these domains. Strategies not fitting into any of these categories were placed into a fifth category unique to TEDDY. Results: TEDDY identified over one hundred retention strategies used during the 15 years of follow-up; most could be categorized in these domains. Those unique to TEDDY included (1) study organization and structures to support retention; (2) efforts to meet the changing developmental needs of the TEDDY population, (3) implementation of efforts to address protocol challenges in real-time; and (4) employment of a re-engagement protocol for those who had dropped out of the study. Conclusion: Pediatric cohort studies should include strategies, structures, and resources addressing retention at the study's initiation. It is recommended that child and parent engagement in addition to the developmental needs of the child be an integrated focus of all strategies. Putting mechanisms in place to address protocol and retention challenges in real time would facilitate effectively addressing challenges as they arise. Trial registration: ClinicalTrials.gov Identifier: NCT00279318.
ABSTRACT
BACKGROUND: Antibody responses to virus reflect exposure and potential protection. METHODS: We developed a highly specific and sensitive approach to measuring antibodies against SARS-CoV-2 for population-scale immune surveillance. Antibody positivity was defined as a dual-positive response against both the receptor-binding domain and nucleocapsid proteins of SARS-CoV-2. Antibodies were measured by immunoprecipitation assays in capillary blood from 15,771 children aged 1 to 18 years living in Bavaria, Germany, and participating in a public health type 1 diabetes screening program (ClinicalTrials.gov: NCT04039945), in 1,916 dried blood spots from neonates in a Bavarian screening study (ClinicalTrials.gov: NCT03316261), and in 75 SARS-CoV-2-positive individuals. Virus positive incidence was obtained from the Bavarian health authority data. FINDINGS: Dual-antibody positivity was detected in none of the 3,887 children in 2019 (100% specificity) and 73 of 75 SARS-CoV-2-positive individuals (97.3% sensitivity). Antibody surveillance in children during 2020 resulted in frequencies of 0.08% in January to March, 0.61% in April, 0.74% in May, 1.13% in June, and 0.91% in July. Antibody prevalence from April 2020 was 6-fold higher than the incidence of authority-reported cases (156 per 100,000 children), showed marked variation between the seven Bavarian regions (p < 0.0001), and was not associated with age or sex. Transmission in children with virus-positive family members was 35%. 47% of positive children were asymptomatic. No association with type 1 diabetes autoimmunity was observed. Antibody frequency in newborns was 0.47%. CONCLUSIONS: We demonstrate the value of population-based screening programs for pandemic monitoring. FUNDING: The work was supported by funding from the BMBF (FKZ01KX1818).