Statis tical Analyse sFor patient description, median and IQRs were provided forcontinuous variables and percentage for binary variables. Forgroup comparison (patients included in the study vs patientslost to follow-up) Wilcoxon rank test (continuous variables),and c2 test (binary variables) were applied. P values wereadjusted for multiple comparisons according to Holm (Bonferroni step-down). For intra-individual comparisons ofmetabolic control during the prepubertal, pubertal, and postpubertal/young adult period, respective differences wereanalyzed by Wilcoxon signed-rank test.Spearman correlation with Fisher z-transformation tocalculate 95% CI was used to reflect tracking of metaboliccontrol, relating median HbA1c-values in each patient during the prepubertal period with the respective values duringpuberty, as well as in adulthood. The c2test was used toanalyze the relationship between tertiles of metabolic controlduring prepuberty and adulthood, as well as the achievementof adequate control as recommended in current guidelines.To analyze the contribution of prepubertal metabolic control on adult HbA1c, a mixed hierarchic regression modelwas used (dependent variable: HbA1c in adulthood, independent variable: HbA1c during prepuberty). Center was enteredas a random effect in the model (covariance structure: Cholesky), the intraclass correlation (between center variation)was 21%. Estimation was based on residual pseudolikelihood, denominator degrees of freedom were calculatedaccording to Kenward-Roger, and iterations were optimizedaccording to Newton-Raphson. In addition to this simplemodel, a fully adjusted model including sex, migration background, and year of manifestation, diabetes duration, insulintherapy, and adult BMI together with type of treatment center was implemented.Logistic regression models, with identical covariates as inthe fully adjusted model, were used to calculate odds forgood metabolic control in adulthood based on recommended HbA1c levels adopting either American Diabetes Association (ADA) or International Society for Pediatric andAdolescent Diabetes guidelines respectively.For all analyses, a 2-sided P value of <.05 was consideredstatistically significant. The statistical software package SAS9.3 was used for analysis (SAS Institute Inc, Cary, NorthCarolina).ResultsBy March 2013, the DPV database included 15 162 patientswith type 1 diabetes manifestation younger than 11 years ofage, born prior to 1993, with complete baseline documentation. Among these, 1146 patients were followed continuouslyfrom prepuberty through puberty to adulthood. The largenumber of patients lost to follow-up is due to change of providers of diabetes care, especially during transition from pediatric centers to adult internal medicine. We consequentlycompared the study group (n = 1146) with 14 016 patientsTab le I. Patient demographicsStudy cohort,complete follow-upuntil the age of20 y (n = 1146)Patient group,loss-offollow-up(n = 14 016) PMale (%) (SD) 49.4 ( 0.5) 49.0 ( 0.5) n.s.Mean age at onset (y) (SD) 6.9 ( 2.8) 6.9 ( 2.8) n.s.Mean age (y) (SD) 21.6 ( 2.8) 17.8 ( 2.8) <.0001Migration background (%) 8.0 ( 0.3) 6.5 ( 0.3) n.s.Pediatric center (%) 77.3 ( 0.4) 83.4 ( 0.4) <.0001BMI (kg/m2) (SD) 24.5 (3.7) 23.1 ( 4.1) <.0001Mean HbA1c (%) (SD) 8.3 (1.8) 8.7 ( 2.0) <.0001n.s., not significant.Comparison of patient demographics of the study cohort with complete documentation until theage of $20 years and the cohort with incomplete documentation and loss of follow-up.Vol. 165, No. 5 November 201495
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