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Relationship between participant-reported outcomes, residual beta cell function and metabolic parameters in youth with newly diagnosed type 1 diabetes.

AIMS/HYPOTHESIS: Clinical trials of interventions to preserve beta cell function in new-onset type 1 diabetes frequently employ participant-reported outcome measures (PROMs). However, the expected changes in PROMs scores immediately following diagnosis and their association with residual beta cell function, metabolic markers and continuous glucose monitoring (CGM) are unclear. METHODS: Repeated PROMs including Paediatric Quality of Life Inventory diabetes module (PedsQL) and hypoglycaemia fear survey (HFS) were recorded from participants aged 10-18 years with newly diagnosed type 1 diabetes and their parents in two clinical trials: CLOuD (N=97, hybrid closed loop [HCL] vs multiple daily injections [MDI]) and USTEKID (N=72, ustekinumab immunotherapy vs placebo). Scores were compared with serial mixed meal-stimulated C-peptide levels (AUC C-peptide), HbA1c and CGM data. RESULTS: PedsQL and HFS scores for children/adolescents and their parents showed wide variation between individuals but did not change substantially within individuals over the first 48 months from diagnosis. Baseline scores were highly predictive of scores at 12-48 months (p<0.001). PedsQL scores were higher (better) in those reported by children/adolescents than by their parents (p<0.01). In contrast, HFS scores were higher in parents than children (p<0.001), indicating more fear. Strong correlations were observed between child and parent scores (p<0.001). No significant improvement in these scores was detected following intervention (ustekinumab or HCL). Meta-analysis revealed modest but statistically significant associations between HbA1c and PedsQL (&#x3b2;(std)=-0.11; 95% CI -0.20, -0.03) and HFS (&#x3b2;(std)=0.11; 95% CI 0.00, 0.21), and between CGM time in range and PedsQL (&#x3b2;(std)=0.14; 95% CI 0.03, 0.26) but not HFS (&#x3b2;(std)=-0.05; 95% CI -0.16, 0.06). Beta cell function (AUC C-peptide) was strongly associated with HbA1c (&#x3b2;(std)=-0.29; 95% CI -0.39, -0.20) and CGM time in range (&#x3b2;(std)=0.41; 95% CI 0.30, 0.52). Higher beta cell function showed a trend towards better PedsQL (&#x3b2;(std)=0.11; 95% CI -0.03, 0.25) and lower HFS (&#x3b2;(std)=-0.05; 95% CI -0.17, 0.07) but this did not reach statistical significance. CONCLUSIONS/INTERPRETATION: PedsQL and HFS scores changed little during the first 48 months after diagnosis of type 1 diabetes. These scores showed modest but statistically significant associations with measures of glucose management (HbA1c and CGM time in range), whereas the relationships with residual beta cell function (C-peptide) were weaker and did not reach significance. The modest size of these effects suggests current PROMs capture only limited aspects of the clinical benefit associated with beta cell preservation. Future research should incorporate psychometric instruments that are specifically adapted for young people using modern diabetes technologies and undergoing disease-modifying therapy, to ensure outcomes are meaningfully represented in early-stage type 1 diabetes trials.

Adolescent

Assay-dependent variability in peptide biomarker quantification: experimental evidence from renalase in chronic kidney disease.

BACKGROUND: Renalase is a promising biomarker for kidney disease, but published levels vary widely between studies. We hypothesised that variability in commercial enzyme-linked immunosorbent assays (ELISAs) kits and matrix effects (serum vs plasma) drive these inconsistencies. METHODS: Paired serum and plasma samples from 56 participants (28 chronic kidney disease (CKD) stages 2-5, 28 healthy controls) were tested using three commercial renalase ELISAs (BTLAB, Cloud-Clone, EIAab). We assessed intra-assay precision, inter-assay agreement (Spearman's rank correlation and Bland-Altman analysis on log10-transformed values), matrix effects, and associations with estimated glomerular filtration rate (eGFR). Diagnostic performance was evaluated by Receiver operating characteristic (ROC) analysis. RESULTS: Inter-assay renalase concentrations differed markedly (up to orders of magnitude), with weak inter-assay correlations (r&#x2009;&#x2264;&#x2009;0.25). Bland-Altman analyses revealed large, systematic biases between kits. Only the BTLAB assay showed consistent serum/plasma agreement, a significant correlation with eGFR (&#x3c1;&#x2009;&#x2248;&#x2009;0.32-0.42, p&#x2009;<&#x2009;0.05), and moderate discriminatory performance for CKD in serum (AUC = 0.70) and plasma (AUC = 0.68). Cloud-Clone and EIAab produced divergent results and strong matrix-dependent biases. CONCLUSIONS: Observed variability among commercial ELISA platforms may compromise comparability between studies. Harmonisation, standardised reference materials, and cross-validation are necessary before renalase assays can be used reliably in clinical practice.

Humans