Jacob S Petersen

Novo Nordisk, København, Capital Region, Denmark

Are you Jacob S Petersen?

Claim your profile

Publications (3)7.79 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Objective To validate the partial remission (PR) definition based on insulin dose-adjusted HbA1c (IDAA1c).Subjects and methodsThe IDAA1c was developed using data in 251 children from the European Hvidoere cohort. For validation, 129 children from a Danish cohort were followed from the onset of type 1 diabetes (T1D). Receiver operating characteristic curve (ROC) analysis was used to evaluate the predictive value of IDAA1c and age on partial C-peptide remission (stimulated C-peptide, SCP > 300 pmol/L).ResultsPR (IDAA1c ≤ 9) in the Danish and Hvidoere cohorts occurred in 62 vs. 61% (3 months, p = 0.80), 47 vs. 44% (6 months, p = 0.57), 26 vs. 32% (9 months, p = 0.32) and 19 vs. 18% (12 months, p = 0.69). The effect of age on SCP was significantly higher in the Danish cohort compared with the Hvidoere cohort (p < 0.0001), likely due to higher attained Boost SCP, so the sensitivity and specificity of those in PR by IDAA1c ≤ 9, SCP > 300 pmol/L was 0.85 and 0.62 at 6 months and 0.62 vs. 0.38 at 12 months, respectively. IDAA1c with age significantly improved the ROC analyses and the AUC reached 0.89 ± 0.04 (age) vs. 0.94 ± 0.02 (age + IDAA1c) at 6 months (p < 0.0004) and 0.76 ± 0.04 (age) vs. 0.90 ± 0.03 (age + IDAA1c) at 12 months (p < 0.0001).Conclusions The diagnostic and prognostic power of the IDAA1c measure is kept but due to the higher Boost stimulation in the Danish cohort, the specificity of the formula is lower with the chosen limits for SCP (300 pmol/L) and IDAA1c ≤9, respectively.
    Pediatric Diabetes 11/2014; 15(7). DOI:10.1111/pedi.12208 · 2.13 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: To clarify whether the rate of decline in stimulated C-peptide (SCP) from 2 to 15 months after diagnosis has changed over an interval of 27 yr. The rate of decline in SCP levels at 1, 2, 3, 6, 9, 12, and 15 months after diagnosis was compared in four paediatric cohorts from Scandinavian and European countries including 446 children with new onset type 1 diabetes (T1D, 1982-2004). Findings were evaluated against 78 children (2004-2009) from the TrialNet studies. The mean rate of decline [%/month (±SEM)] in SCP for a 10-yr-old child was 7.7%/month (±1.5) in the 1982-1985 Cohort, 6.3%/month (±1.7) in the 1995-1998 Cohort, 7.8%/month (±0.7) in the 1999-2000 Cohort, and 10.7%/month (±0.9) in the latest 2004-2005 Cohort (p = 0.05). Including the TrialNet Cohort with a rate of decline in SCP of 10.0%/month (±0.9) the differences between the cohorts are still significant (p = 0.039). The rate of decline in SCP was negatively associated with age (p < 0.0001), insulin antibodies (IA) (p = 0.003), and glutamic acid decarboxylase-65 (GAD65A) (p = 0.03) initially with no statistically significant effect of body mass index (BMI) Z-score at 3 months. Also, at 3 months the time around partial remission, the effect of age on SCP was significantly greater in children ≤5 yr compared with older children (p ≤ 0.0001). During the past 27 yr, initial C-peptide as well as the rate of C-peptide decline seem to have increased. The rate of decline was affected significantly by age, GAD65A, and IA, but not BMI Z-score or initial C-peptide.
    Pediatric Diabetes 11/2013; 15(5). DOI:10.1111/pedi.12098 · 2.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The purpose of the present study is to explore the progression of type 1 diabetes (T1D) in Danish children 12 months after diagnosis using Latent Factor Modelling. We include three data blocks of dynamic paraclinical biomarkers, baseline clinical characteristics and genetic profiles of diabetes related SNPs in the analyses. This method identified a model explaining 21.6% of the total variation in the data set. The model consists of two components: (1) A pattern of declining residual β-cell function positively associated with young age, presence of diabetic ketoacidosis and long duration of disease symptoms (P = 0.0004), and with risk alleles of WFS1, CDKN2A/2B and RNLS (P = 0.006). (2) A second pattern of high ZnT8 autoantibody levels and low postprandial glucagon levels associated with risk alleles of IFIH1, TCF2, TAF5L, IL2RA and PTPN2 and protective alleles of ERBB3 gene (P = 0.0005). These results demonstrate that Latent Factor Modelling can identify associating patterns in clinical prospective data - future functional studies will be needed to clarify the relevance of these patterns.
    PLoS ONE 06/2013; 8(6):e64632. DOI:10.1371/journal.pone.0064632 · 3.53 Impact Factor