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BACKGROUND: The INNODIA consortium has established a pan-European infrastructure using validated centres to prospectively evaluate clinical data from individuals with newly diagnosed type 1 diabetes combined with centralised collection of clinical samples to determine rates of decline in beta-cell function and identify novel biomarkers, which could be used for future stratification of phase 2 clinical trials. METHODS: In this context, we have developed a Master Protocol, based on the "backbone" of the INNODIA natural history study, which we believe could improve the delivery of phase 2 studies exploring the use of single or combinations of Investigational Medicinal Products (IMPs), designed to prevent or reverse declines in beta-cell function in individuals with newly diagnosed type 1 diabetes. Although many IMPs have demonstrated potential efficacy in phase 2 studies, few subsequent phase 3 studies have confirmed these benefits. Currently, phase 2 drug development for this indication is limited by poor evaluation of drug dosage and lack of mechanistic data to understand variable responses to the IMPs. Identification of biomarkers which might permit more robust stratification of participants at baseline has been slow. DISCUSSION: The Master Protocol provides (1) standardised assessment of efficacy and safety, (2) comparable collection of mechanistic data, (3) the opportunity to include adaptive designs and the use of shared control groups in the evaluation of combination therapies, and (4) benefits of greater understanding of endpoint variation to ensure more robust sample size calculations and future baseline stratification using existing and novel biomarkers.

AIM: To systematically assess the impact of commercially available hybrid closed loop (HCL) systems on psychological outcomes in youths with type 1 diabetes and their parents. METHODS: We performed a systematic review including studies published in the last 10 years. PICOS framework was used in the selection process, and evidence was assessed using the GRADE system. RESULTS: A total of 215 studies were identified after duplicate removal, and 31 studies were included in this systematic review: 20 on first-generation HCL and 11 on second-generation HCL systems. According to studies with moderate- to high-level quality of evidence, HCL systems led to better, or in some studies, unchanged psychological outcomes such as distress and burden related to diabetes management, fear of hypoglycemia, quality of life, satisfaction; instead, quality of sleep was perceived as improved, although results were not confirmed in studies using actigraphy. From semi-structured interviews, answers were more homogeneous, and participants reported a positive experience and attitude towards HCL technology, which was felt to be easy to use and apt to achieve glycemic targets. CONCLUSIONS: Evidence confirms the importance of evaluating the psychosocial needs of youths with diabetes and their families when starting HCL systems and during follow-up, and to set realistic expectations of what can be achieved along with awareness of the limitations of the systems, and educate and motivate families to overcome barriers.

Juvenile idiopathic arthritis (JIA) is a common pediatric rheumatic disease. Renal manifestations have been rarely observed in JIA, although amyloidosis could be a renal complication in systemic JIA (sJIA). To investigate renal damage in JIA children and to establish the relationship with treatment. Blood urea nitrogen (BUN), creatinine, cystatin C (CysC), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), urinary albumin excretion (UAE), estimated glomerular filtration rate (eGFR), and renal resistive index (RRI) were assessed in 49 JIA children (9 boys/40 girls, mean age 10.3 ± 3.8 years) and in 49 healthy controls (24 boys/25 girls, mean age 11.3 ± 3.4 years). Twenty-two JIA patients were on methotrexate (MTX) therapy (group A) and 27 on biologic drugs (group B). CysC and BUN (respectively, 0.8 ± 0.1 vs. 0.7 ± 0.1 mg/dl; 13.3 ± 2.9 vs. 11.7 ± 1.4 mg/dl) were higher (p ≤ 0.001) whereas creatinine and eGFR (respectively, 0.5 ± 0.1 vs. 0.6 ± 0.1 mg/dl; 99.2 ± 10.5 vs. 122.5 ± 19.8 ml/min/1.73 m2) were lower in JIA children as compared to controls (p p = 0.003). Mean RRI was higher in JIA children than controls (0.7 ± 0.04 vs. 0.6 ± 0.04; p p p p = 0.003) and eGFR (p = 0.001). JIA children had reduced eGFR, increased UAE and higher RRI values, than controls. RRIs were higher in patients on biologic drugs than MTX group and were associated with inflammation indexes and disease state, suggesting a direct effect of the disease.

Background: The INNODIA consortium has established a pan-European infrastructure using validated centres to evaluate prospectively clinical data from individuals with newly diagnosed Type 1 diabetes combined with centralized collection of clinical samples to determine rates of decline in beta-cell function and identify novel biomarkers, which could be used for future stratification of Phase 2 clinical trials. Methods: In this context we have developed a Master Protocol, based on the “backbone” of the INNODIA natural history study, which we believe could improve the delivery of Phase 2 studies exploring the use of single or combinations of Investigational Medicinal Products (IMPs), designed to prevent or reverse declines in beta-cell function in individuals with newly diagnosed Type 1 diabetes. Although many IMPs have demonstrated potential efficacy in Phase 2 studies, few subsequent Phase 3 studies have confirmed these benefits. Currently Phase 2 drug development for this indication is limited by poor evaluation of drug dosage and lack of mechanistic data to understand variable responses to the IMPs. Identification of biomarkers which might permit more robust stratification of participants at baseline has been slow. Discussion: The Master Protocol provides: 1) standardized assessment of efficacy and safety; 2) comparable collection of mechanistic data; 3) the opportunity to include adaptive designs and the use of shared control groups in the evaluation of combination therapies; 4) benefits of greater understanding of endpoint variation to ensure more robust sample size calculations and future baseline stratification using existing and novel biomarkers.