Recurrent events refer to events that over time can occur several times for each individual. Full use of such data in a clinical trial requires a method that addresses the dependence between events. For modelling this dependence, there are two time scales to consider, namely time since start of the study (running time) or time since most recent event (gap time). In the multi-state setup, it is possible to estimate parameters also in the case, where the hazard model allows for an effect of both time scales, making this an extremely flexible approach. However, for summarizing the effect of a treatment in a transparent and informative way, the choice of time scale and model requires much more care. This paper discusses these choices both from a theoretical and practical point of view. This is supported by a simulation study showing that in a frailty model with assumptions covered by both time scales, the gap time approach may give misleading results. A literature dataset is used for illustrating the issues.

Studies with twins provide fundamental insights to lifespans of humans. We aim to clarify if monozygotic and dizygotic twin individuals differ in lifespan, that is, if zygosity matters. We investigate whether a possible difference in mortality after infancy between zygosities is stable in different age cohorts, and whether the difference remains when twins with unknown zygosity are taken into account. Further, we compare the distribution of long-livers, that is, the upper-tail of the lifespan distribution, between monozygotic and same-sex dizygotic twin individuals. The Danish Twin Registry provides a nationwide cohort of 109,303 twins born during 1870 to 1990 with valid vital status. Standard survival analysis is used to compare mortality in monozygotic and dizygotic twin individuals and twin individuals with unknown zygosity. The mortality of monozygotic and dizygotic twin individuals differs slightly after taking into consideration effects of birthand age-cohorts, gender differences, and that twins are paired. However, no substantial nor systematic differences remain when taking twins with unknown zygosity into account. Further, the distribution of long-livers is very similar by zygosity, suggesting the same mortality process. The population-based and oldest twin cohort ever studied suggests that monozygotic and dizygotic twins have similar lifespans.

Studies with twins provide fundamental insights to lifespans of humans. We aim to clarify if monozygotic and dizygotic twin individuals differ in lifespan, that is, if zygosity matters. We investigate whether a possible difference in mortality after infancy between zygosities is stable in different age cohorts, and whether the difference remains when twins with unknown zygosity are taken into account. Further, we compare the distribution of long-livers, that is, the upper-tail of the lifespan distribution, between monozygotic and same-sex dizygotic twin individuals. The Danish Twin Registry provides a nationwide cohort of 109,303 twins born during 1870 to 1990 with valid vital status. Standard survival analysis is used to compare mortality in monozygotic and dizygotic twin individuals and twin individuals with unknown zygosity. The mortality of monozygotic and dizygotic twin individuals differs slightly after taking into consideration effects of birth- and age-cohorts, gender differences, and that twins are paired. However, no substantial nor systematic differences remain when taking twins with unknown zygosity into account. Further, the distribution of long-livers is very similar by zygosity, suggesting the same mortality process. The population-based and oldest twin cohort ever studied suggests that monozygotic and dizygotic twins have similar lifespans.

Circulating microRNAs (miRNAs) have been implicated in several pathologies including type 1 diabetes. In the present study, we aimed to identify circulating miRNAs affected by disease duration in children with recent onset type 1 diabetes. Forty children and adolescents from the Danish Remission Phase Cohort were followed with blood samples drawn at 1, 3, 6, 12, and 60 months after diagnosis. Pancreatic autoantibodies were measured at each visit. Cytokines were measured only the first year. miRNA expression profiling was performed by RT-qPCR. The effect of disease duration was analyzed by mixed models for repeated measurements adjusted for sex and age. Eight miRNAs (hsa-miR-10b-5p, hsa-miR-17-5p, hsa-miR-30e-5p, hsa-miR-93-5p, hsa-miR-99a-5p, hsa-miR-125b-5p, hsa-miR-423-3p, and hsa-miR-497-5p) were found to significantly change in expression (adjusted p-value < 0.05) with disease progression. Three pancreatic autoantibodies, ICA, IA-2A, and GAD65A, and four cytokines, IL-4, IL-10, IL-21, and IL-22, were associated with the miRNAs at different time points. Pathway analysis revealed associations with various immune-mediated signaling pathways. Eight miRNAs that were involved in immunological pathways changed expression levels during the first five years after diagnosis and were associated with variations in cytokine and pancreatic antibodies, suggesting a possible effect on the immunological processes in the early phase of the disease.

Circulating microRNAs (miRNAs) have been implicated in several pathologies including type 1 diabetes. In the present study, we aimed to identify circulating miRNAs affected by disease duration in children with recent onset type 1 diabetes. Forty children and adolescents from the Danish Remission Phase Cohort were followed with blood samples drawn at 1, 3, 6, 12, and 60 months after diagnosis. Pancreatic autoantibodies were measured at each visit. Cytokines were measured only the first year. miRNA expression profiling was performed by RT-qPCR. The effect of disease duration was analyzed by mixed models for repeated measurements adjusted for sex and age. Eight miRNAs (hsa-miR-10b-5p, hsa-miR-17-5p, hsa-miR-30e-5p, hsa-miR-93-5p, hsa-miR-99a-5p, hsa-miR-125b-5p, hsa-miR-423-3p, and hsa-miR-497-5p) were found to significantly change in expression (adjusted p-value < 0.05) with disease progression. Three pancreatic autoantibodies, ICA, IA-2A, and GAD65A, and four cytokines, IL-4, IL-10, IL-21, and IL-22, were associated with the miRNAs at different time points. Pathway analysis revealed associations with various immune-mediated signaling pathways. Eight miRNAs that were involved in immunological pathways changed expression levels during the first five years after diagnosis and were associated with variations in cytokine and pancreatic antibodies, suggesting a possible effect on the immunological processes in the early phase of the disease.

In drug development, assessment of the dose-response relationship gives essential insight into which doses are efficacious, yet safe. These relationships are often estimated by parametric, nonlinear models. A hurdle for trials that aim to estimate these models, is that the optimal study design depends on the unknown model parameters. A solution is to use adaptive designs. Ideally, such procedures evaluate a safety and an efficacy endpoint to get the best understanding of the therapeutic window. Many such designs have already been proposed. However, the outcomes are typically required to be of a specific type and the correlation between them has to be modeled explicitly. We propose a more general and simpler approach. Separate models can be specified for each endpoint, without restrictions on the type of model or outcome. The dependence between the outcomes is considered, without having to specify its structure. A new penalty function is introduced to balance the need for optimal precision and safe dose assignments. The method is illustrated by an example study in depression. Simulation results indicate that the adaptive design is more efficient than a fixed design. Use of the penalty function decreases estimation efficiency, but increases dose assignment to favorable doses. Supplementary materials for this article are available online.

The induction of neuropathic pain-like behaviors in rodents often requires surgical intervention. This engages acute nociceptive signaling events that contribute to pain and stress post-operatively that from a welfare perspective demands peri-operative analgesic treatment. However, a large number of researchers avoid providing such care based largely on anecdotal opinions that it might interfere with model pathophysiology in the longer term.To investigate effects of various peri-operative analgesic regimens encapsulating different mechanisms and duration of action, on the development of post-operative stress/welfare and pain-like behaviors in the Spared Nerve Injury (SNI)-model of neuropathic pain.Starting on the day of surgery, male Sprague-Dawley rats were administered either vehicle (s.c.), carprofen (5.0mg/kg, s.c.), buprenorphine (0.1mg/kg s.c. or 1.0mg/kg p.o. in Nutella®), lidocaine/bupivacaine mixture (local irrigation) or a combination of all analgesics, with coverage from a single administration, and up to 72 hours. Post-operative stress and recovery were assessed using welfare parameters, bodyweight, food-consumption, and fecal corticosterone, and hindpaw mechanical allodynia was tested for assessing development of neuropathic pain for 28 days.None of the analgesic regimes compromised the development of mechanical allodynia. Unexpectedly, the combined treatment with 0.1mg/kg s.c. buprenorphine and carprofen for 72 hours and local irrigation with lidocaine/bupivacaine, caused severe adverse effects with peritonitis. This was not observed when the combination included a lower dose of buprenorphine (0.05mg/kg, s.c.), or when buprenorphine was administered alone (0.1mg/kg s.c. or 1.0mg/kg p.o.) for 72 hours. An elevated rate of wound dehiscence was observed especially in the combined treatment groups, underlining the need for balanced analgesia. Repeated buprenorphine injections had positive effects on body weight the first day after surgery, but depressive effects on food intake and body weight later during the first week.Post-operative analgesia does not appear to affect established neuropathic hypersensitivity outcome in the SNI model.

We aimed to identify circulating microRNA (miRNA) that predicts clinical progression in a cohort of 123 children with new-onset type 1 diabetes mellitus.

Aim To determine the mortality rate in a Danish cohort of children and adolescents diagnosed with Type 1 diabetes mellitus compared with the general population.Methods In 1987 and 1989 we included 884 children and 1020 adolescents aged 20 years and under, corresponding to 75% of all Danish children and adolescents with Type 1 diabetes, in two nationwide studies in Denmark. Those who had participated in both investigations (n = 720) were followed until 1 January 2014, using the Danish Civil Registration System on death certificates and emigration. We derived the expected number of deaths in the cohort, using population data values from Statistics Denmark to calculate the standardized mortality ratio. Survival analysis was performed using Cox proportional hazards model.Results During the 24 years of follow-up, 49 (6.8%) patients died, resulting in a standardized mortality ratio of 4.8 (95% confidence interval 3.5, 6.2) compared with the age-standardized general population. A 1% increase in baseline HbA(1c) (1989), available in 718 of 720 patients, was associated with all-cause mortality (hazard ratio = 1.38; 95% confidence interval 1.2, 1.6; P < 0.0001). Type 1 diabetes with multiple complications was the most common reported cause of death (36.7%).Conclusion We found an increased mortality rate in this cohort of children and adolescents with Type 1 diabetes compared with the general population. The only predictor for increased risk of death up to 24 years after inclusion was the HbA(1c) level in 1989. This emphasizes the importance of achieving optimal metabolic control in young people with Type 1 diabetes.

During development of a drug, typically the choice of dose is based on a Phase II dose-finding trial, where selected doses are included with placebo. Two common statistical dose-finding methods to analyze such trials are separate comparisons of each dose to placebo (using a multiple comparison procedure) or a model-based strategy (where a dose-response model is fitted to all data). The first approach works best when patients are concentrated on few doses, but cannot conclude on doses not tested. Model-based methods allow for interpolation between doses, but the validity depends on the correctness of the assumed dose-response model. Bretz et al. (2005, Biometrics 61, 738-748) suggested a combined approach, which selects one or more suitable models from a set of candidate models using a multiple comparison procedure. The method initially requires a priori estimates of any non-linear parameters of the candidate models, such that there is still a degree of model misspecification possible and one can only evaluate one or a few special cases of a general model. We propose an alternative multiple testing procedure, which evaluates a candidate set of plausible dose-response models against each other to select one final model. The method does not require any a priori parameter estimates and controls the Type I error rate of selecting a too complex model.

Pediatric DiabetesVolume 16, Issue S21 p. 24-49 Oral Abstract SessionsFree Access Oral Abstract Sessions First published: 06 October 2015 https://doi.org/10.1111/pedi.12308AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Volume16, IssueS21Special Issue: Abstracts of the Joint Annual Conference of the International Society for Pediatric and Adolescent Diabetes and Australasian Paediatric Endocrine Group (ISPAD+APEG 2015), 7–10 October 2015, Brisbane, AustraliaOctober 2015Pages 24-49 RelatedInformation

An important aim of drug trials is to characterize the dose-response relationship of a new compound. Such a relationship can often be described by a parametric (nonlinear) function that is monotone in dose. If such a model is fitted, it is useful to know the uncertainty of the fitted curve. It is well known that Wald confidence intervals are based on linear approximations and are often unsatisfactory in nonlinear models. Apart from incorrect coverage rates, they can be unreasonable in the sense that the lower confidence limit of the difference to placebo can be negative, even when an overall test shows a significant positive effect. Bootstrap confidence intervals solve many of the problems of the Wald confidence intervals but are computationally intensive and prone to undercoverage for small sample sizes. In this work, we propose a profile likelihood approach to compute confidence intervals for the dose-response curve. These confidence bounds have better coverage than Wald intervals and are more precise and generally faster than bootstrap methods. Moreover, if monotonicity is assumed, the profile likelihood approach takes this automatically into account. The approach is illustrated using a public dataset and simulations based on the Emax and sigmoid Emax models.

OBJECTIVE:To validate the partial remission (PR) definition based on insulin dose-adjusted HbA1c (IDAA1c). SUBJECTS AND METHODS:The 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). RESULTS:PR (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.

Background Insulin analogues have been developed to reduce the risk of hypoglycaemia in patients with diabetes who require insulin-based treatment, but their effect on this endpoint in patients with type 1 diabetes complicated by recurrent severe hypoglycaemia is unknown. We compared the occurrence of severe hypoglycaemic episodes in such patients during treatment with insulin analogues or human insulin.Methods In this investigator-initiated, prospective, randomised, open-label, blinded-endpoint crossover trial at seven medical centres in Denmark, we recruited patients (aged >= 18 years) with type 1 diabetes (diagnosed for > 5 years) who had reported two or more episodes of severe hypoglycaemia in the preceding year. Patients were randomly assigned (1:1) using computer-generated site-specific randomisation lists in blocks of four to treatment with basal-bolus therapy with either analogue insulin (detemir and aspart) or human insulin (human neutral protamine Hagedorn and human regular) in a balanced crossover design. A 1-year plus 1-year treatment period was specified, consisting of two 3-month run-in periods, each followed by a 9-month maintenance period. The primary endpoint was the number of validated episodes of severe hypoglycaemia (defined by need for treatment assistance from others) reported during the maintenance periods, analysed by intention to treat. The study is registered with ClinicalTrials.gov, number NCT00346996.Findings Between May 9, 2007, and Oct 30, 2009, 159 patients were randomly assigned. 18 patients discontinued during the first run-in period, leaving 141 patients in the intention-to-treat population. 136 severe hypoglycaemic episodes were reported during treatment with human insulin and 105 episodes were reported during treatment with insulin analogues, resulting in an absolute rate reduction of 0.51 episodes (95% CI 0.19-0.84) per patient-year with insulin analogues. This result corresponds to a relative rate reduction of 29% (95% CI 11-48; p=0.010).Interpretation Treatment with insulin detemir and aspart in patients with type 1 diabetes and recurrent severe hypoglycaemia resulted in a clinically significant reduced rate of severe hypoglycaemia compared with human insulin. Patients with the greatest chance of benefitting from improved insulin therapy should be offered treatment with insulin analogues and be included in future trials of new insulins.