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Purpose The aims of this study were to analyze the prevalence and course of disordered eating behavior (DEB) in adolescents with intensively treated type I diabetes, describe differences in age-specific DEB symptoms, and identify predictors of current DEB. Methods Data were taken from 332/218 11- to 27-year-old participants (55.7% girls/women, mean age [SD] 17.8 [3.4] years, mean diabetes duration 14.9 [3.0] years) of two/three surveys of a Germany-wide longitudinal study on early-onset and long duration diabetes, respectively. A diabetes-adapted version of the SCOFF questionnaire was used to assess DEB. Both screening-based overall and age- and sex-specific prevalence of DEB and its symptoms were determined. To estimate transition probabilities between DEB states, first-order Markov transition models were implemented adjusting for previous sociodemographic, socioeconomic, and diabetes-specific covariates. Results The overall screening-based DEB prevalence among all 1,318 observations was 10.8% (95% confidence interval [CI]: 9.2%, 12.6%) with age-specific differences in symptom prevalence. Transition probabilities for developing/persistent DEB were twofold higher among female than male participants (risk ratio [RR] 2.3 [1.4, 3.9]/2.1 [1.3, 3.4]). In multiple adjusted regression, previous DEB (odds ratio [OR] 2.8 [95% CI 1.4, 5.6]), follow-up time (ORper 1-year increase 3.4 [1.4, 8.0]), and sex (ORgirls/women 2.1 [1.1, 3.9]) were the most important predictors of current DEB with further weaker associations for previous age and HbA1c. Conclusions Our results contribute to better understanding the course of DEB in patients with early-onset diabetes and emphasize the relevance of regular DEB screenings including the age group of young adults.

Summary Background Cluster analyses have proposed different diabetes phenotypes using age, BMI, glycaemia, homoeostasis model estimates, and islet autoantibodies. We tested whether comprehensive phenotyping validates and further characterises these clusters at diagnosis and whether relevant diabetes-related complications differ among these clusters, during 5-years of follow-up. Methods Patients with newly diagnosed type 1 or type 2 diabetes in the German Diabetes Study underwent comprehensive phenotyping and assessment of laboratory variables. Insulin sensitivity was assessed using hyperinsulinaemic-euglycaemic clamps, hepatocellular lipid content using magnetic resonance spectroscopy, hepatic fibrosis using non-invasive scores, and peripheral and autonomic neuropathy using functional and clinical criteria. Patients were reassessed after 5 years. The German Diabetes Study is registered with ClinicalTrials.gov , number NCT01055093 , and is ongoing. Findings 1105 patients were classified at baseline into five clusters, with 386 (35%) assigned to mild age-related diabetes (MARD), 323 (29%) to mild obesity-related diabetes (MOD), 247 (22%) to severe autoimmune diabetes (SAID), 121 (11%) to severe insulin-resistant diabetes (SIRD), and 28 (3%) to severe insulin-deficient diabetes (SIDD). At 5-year follow-up, 367 patients were reassessed, 128 (35%) with MARD, 106 (29%) with MOD, 88 (24%) with SAID, 35 (10%) with SIRD, and ten (3%) with SIDD. Whole-body insulin sensitivity was lowest in patients with SIRD at baseline (mean 4·3 mg/kg per min [SD 2·0]) compared with those with SAID (8·4 mg/kg per min [3·2]; p Interpretation Cluster analysis can characterise cohorts with different degrees of whole-body and adipose-tissue insulin resistance. Specific diabetes clusters show different prevalence of diabetes complications at early stages of non-alcoholic fatty liver disease and diabetic neuropathy. These findings could help improve targeted prevention and treatment and enable precision medicine for diabetes and its comorbidities. Funding German Diabetes Center, German Federal Ministry of Health, Ministry of Culture and Science of the state of North Rhine-Westphalia, German Federal Ministry of Education and Research, German Diabetes Association, German Center for Diabetes Research, Research Network SFB 1116 of the German Research Foundation, and Schmutzler Stiftung.

Aims/hypothesis Diabetes has been identified as a risk factor for poor prognosis of coronavirus disease-2019 (COVID-19). The aim of this study is to identify high-risk phenotypes of diabetes associated with COVID-19 severity and death. Methods This is the first edition of a living systematic review and meta-analysis on observational studies investigating phenotypes in individuals with diabetes and COVID-19-related death and severity. Four different databases were searched up to 10 October 2020. We used a random effects meta-analysis to calculate summary relative risks (SRR) with 95% CI. The certainty of evidence was evaluated by the GRADE tool. Results A total of 22 articles, including 17,687 individuals, met our inclusion criteria. For COVID-19-related death among individuals with diabetes and COVID-19, there was high to moderate certainty of evidence for associations (SRR [95% CI]) between male sex (1.28 [1.02, 1.61], n = 10 studies), older age (>65 years: 3.49 [1.82, 6.69], n = 6 studies), pre-existing comorbidities (cardiovascular disease: 1.56 [1.09, 2.24], n = 8 studies; chronic kidney disease: 1.93 [1.28, 2.90], n = 6 studies; chronic obstructive pulmonary disease: 1.40 [1.21, 1.62], n = 5 studies), diabetes treatment (insulin use: 1.75 [1.01, 3.03], n = 5 studies; metformin use: 0.50 [0.28, 0.90], n = 4 studies) and blood glucose at admission (≥11 mmol/l: 8.60 [2.25, 32.83], n = 2 studies). Similar, but generally weaker and less precise associations were observed between risk phenotypes of diabetes and severity of COVID-19. Conclusions/interpretation Individuals with a more severe course of diabetes have a poorer prognosis of COVID-19 compared with individuals with a milder course of disease. To further strengthen the evidence, more studies on this topic that account for potential confounders are warranted. Registration PROSPERO registration ID CRD42020193692. Graphical abstract

Objectives The aim of the study was to identify the validity of effect estimates for serious rare adverse events in clinical study reports of antidepressants trials, across different meta-analysis methods. Study Design and Setting Four serious rare adverse events (all-cause mortality, suicidality, aggressive behavior, and akathisia) were meta-analyzed using different methods. The Yusuf-Peto odds ratio ignores studies with no events and was compared with the alternative approaches of generalized linear mixed models (GLMMs), conditional logistic regression, a Bayesian approach using Markov Chain Monte Carlo (MCMC), and a beta-binomial regression model. Results The estimates for the four outcomes did not change substantially across the different methods; the Yusuf-Peto method underestimated the treatment harm and overestimated its precision, especially when the estimated odds ratio deviated greatly from 1. For example, the odds ratio for suicidality for children and adolescents was 2.39 (95% confidence interval = 1.32–4.33), using the Yusuf-Peto method but increased to 2.64 (1.33–5.26) using conditional logistic regression, to 2.69 (1.19–6.09) using beta-binomial, to 2.73 (1.37–5.42) using the GLMM, and finally to 2.87 (1.42–5.98) using the MCMC approach. Conclusion The method used for meta-analysis of rare events data influences the estimates obtained, and the exclusion of double-zero event studies can give misleading results. To ensure reduction of bias and erroneous inferences, sensitivity analyses should be performed using different methods instead of the Yusuf-Peto approach, in particular the beta-binomial method, which was shown to be superior through a simulation study.

Objectives The propensity score (PS) method is increasingly used to assess treatment effects in nonrandomized trials. Although there are several methods to use the PS for analysis, matching treated and untreated patients by the PS is recommended by most researchers among other reasons because this allows assessing covariate balance before and after matching. Although the standardized difference is commonly applied to compute a measure of balance, it has two deficiencies: its distribution depends on the sample size and one cannot compare standardized differences for baseline covariates on different scales, that is, continuous, binary, ordinal, or nominal covariates. Study Design and Setting We introduce the z -difference to measure covariate balance in matched PS analyses and illustrate it by a recent matched PS analysis from cardiac surgery. Results The z -difference is simple to calculate, can be used with second moments for continuous covariates, and in most cases can also be computed from published data. Its full advantage emerges after displaying z -differences in a Q – Q plot, which allows balance comparisons with respect to (1) a randomized trial and (2) a perfectly matched PS analysis in the sense of Rubin and Thomas. Conclusion The z -difference can be used to measure covariate balance in matched PS analyses.

Objectives Several countries reported a drop in prescription of hormone replacement therapy (HRT) in the 2000s, followed by decreases in breast cancer incidence among postmenopausal women aged 50–69 years. The aim of this study was to provide hormone receptor specific incidence rates of breast cancer in Germany. Methods Breast cancer data were extracted from the cancer registries of the Federal States of Brandenburg and Saarland and the area of Munich for the period from 1998 to 2007. We obtained nationwide data on HRT prescription in 1998–2007 from health insurances. Multiple imputation was used on missing values for the receptor status. Age-standardized (European standard population) and age-specific rates were calculated. Results The age-standardized incidence rates in breast cancer were virtually constant over the entire period in all regions. In particular, no substantial changes over time occurred within the age- and receptor-specific analyses. In the same period we observed a drop in HRT use, starting in 1999 and leveling off in 2004. The incidence trends of carcinoma in situ of the female breast increased during the study period. Conclusions In our data, we did not observe an association between the decline in HRT prescription and breast cancer incidence among women aged from 50 to 69 years. The lack of temporal changes in breast cancer incidence may be explained by introduction of opportunistic and organized mammography screening and low absolute levels of HRT prescription in Germany.

Objective Analyses comparing randomized to nonrandomized clinical trials suffer from the fact that the study populations are usually different. We aimed for a comparison of randomized clinical trials (RCTs) and propensity score (PS) analyses in similar populations. Study Design and Setting In a systematic review, we “meta-matched” RCTs and PS analyses that compared the off- and the on-pump technique in coronary artery bypass grafting. “Meta-confounders” were summarized in a “meta-propensity score” and were used for “meta-matching.” We compared treatment effects between RCTs and PS analyses for 10 previously defined binary clinical outcomes in this “meta-matched” population as differences in “meta-odds ratios.” Results For all clinical outcomes, the estimated differences in “meta-odds ratios” were below an absolute value of 0.15, all confidence intervals included the null. Conclusions In our example, treatment effects of off-pump versus on-pump surgery from RCTs and PS analyses were very similar in a “meta-matched” population of studies, indicating that only a small remaining bias is present in PS analyses.

Descriptive epidemiologic features of testicular cancer suggest that the etiologies of seminoma and nonseminoma of the testis differ. To address this, the authors conducted a systematic review of 150 case-control and cohort studies of the etiology of testicular cancer including 1,148 relative risk estimates, stratified by histologic subgroup, reflecting 631 exposures. Their results do not support the hypothesis that seminoma and nonseminoma have different etiologies among adolescents and young men. To date, only descriptive epidemiologic features, including incidence age patterns and incidence time trends of seminoma and nonseminoma, provide evidence suggesting different etiologies, especially among newborns, infants, and elderly men.

Introduction Measures of heart rate variability (HRV) can be divided in time domain and frequency domain parameters. It is frequently ignored that estimation of frequency-domain parameters is a 2-step procedure where statistical error from the first step (spectral estimation) is neglected in subsequent analyses. Methods We performed a simulation study to quantify the statistical error by using frequency domain instead of time domain parameters. We generated tachograms from a stationary AR(1) process for a wide range of parameters and compared the resulting estimation error (in terms of precision and variability) for the standard deviation of normal RR intervals (SDNN) and low frequency (LF), high frequency (HF), and LF/HF power. Results Estimation of frequency domain parameters is associated with (up to 10-fold) increased variability, as compared with the SDNN. Moreover, the SDNN has higher precision. Conclusion Frequency domain parameters should be applied in HRV analysis only if important physiological reasons suggest their use. If used, frequency domain parameters should be interpreted with caution, taking into account the statistical weaknesses of spectral estimation.

Background: Combinations of gemcitabine–oxaliplatin, gemcitabine–5-fluorouracil (5-FU) and 5-FU–oxaliplatin have synergistic activity and nonoverlapping adverse effect profiles. This trial assessed efficacy and safety of the triple combination gemcitabine–oxaliplatin and infusional 5-FU in patients with locally advanced (n = 11) or metastatic (n = 32) pancreatic adenocarcinoma. Patients and methods: A total of 43 eligible patients were treated with intravenous infusions of gemcitabine (900 mg/m2 over 30 min), followed by oxaliplatin (65 mg/m2 over 2 h) and 5-FU (1500 mg/m2 over 24 h) on days 1 and 8 of a 21-day cycle. Results: Among all 43 patients, the tumor response rate was 19% [95% confidence interval 7% to 30%]. Nine patients were nonassessable for response because they did not complete the first two cycles of chemotherapy due to rapid disease progression, early death or treatment refusal. One patient was lost to follow-up. Median time to progression and overall survival were 5.7 and 7.5 months. Principal grade III/IV toxic effects were leucopenia in 11 (2%), thrombocytopenia in 13 (2%), nausea in 13 (0%), anorexia 16 (7%) and sensory neuropathy in 18 (0%) of patients. Unexpected cardiotoxicity was observed in this trial. Conclusion: Response rates and survival of the three-drug combination compare favorably with single-agent gemcitabine, but do not exceed results for doublets.

Regression models for discrete responses with more than two categories are well established in applied statistics nowadays, where the Proportional odds model is mainly used for ordinal and the Multinomial logistic model for nominal responses. Anderson's Stereotype regression model has been used less. It is a mixture of the aforementioned models that has fewer parameters than the Multinomial model and models the assumed ordinality of the response in terms of the covariates. The main reason for the rare application of the Stereotype model might have been the enhanced mathematical complexity due to multiplicative parameters in the linear predictor and the lack of standard software. Two methods are shown that estimate the model with standard software and the SAS system is used for illustration. The first method interprets the Stereotype model as a nonlinear model with a multivariate response, and thus embeds it in a well-known and mature statistical class of models. The second method maximizes the likelihood function directly. An example on occupational hand eczema in the car industry is used to introduce the model and the different possibilities for computation. Results from a small simulation study, inspired by the hand eczema data set, are given which demonstrate that the estimation of the Stereotype model by the two proposed methods indeed yields valid results in terms of empirical size and power.

Dendritic cells (DC) are increasingly used as a vaccine. Unfortunately, a satisfactory cryopreservation of DC in the absence of FCS is not yet available, so that laborious repeated generation of DC from fresh blood or frozen peripheral blood mononuclear cells for each vaccination has been required to date. We now aimed at developing an effective cryopreservation method, and by testing several variables found that it was crucial to combine the most advantageous maturation stimulus with an improved freezing procedure. We generated monocyte-derived DC from leukapheresis products by using GM-CSF and IL-4 and showed that amongst several known maturation stimuli the cocktail consisting of TNF-alpha+IL-1 beta+IL-6+PGE(2) achieved the highest survival of mature DC. We then systematically explored cryopreservation conditions, and found that freezing matured DC at 1 degrees C/min in pure autologous serum+10% DMSO+5% glucose at a cell density of 10x10(6) DC/ml gave the best results. Using this approach 85-100% of the frozen DC could be recovered in a viable state after thawing (Table 1). The morphology, phenotype, survival as well as functional properties (allogeneic mixed leukocyte reaction, induction of influenza matrix or melan A peptide-specific cytotoxic T cells) of these thawed DC were equivalent to freshly prepared ones. The addition of CD40L or TRANCE/RANKL further improved DC survival. Importantly, we demonstrate that DC can effectively be loaded with antigens (such as Tetanus Toxoid, influenza matrix and melan A peptides) before cryopreservation so that it is now possible to generate antigen-preloaded, frozen DC aliquots that after thawing can be used right away. This is an important advance as both the generation of a standardized DC vaccine under GMP conditions and the carrying out of clinical trials are greatly facilitated.

This paper presents a collection of macros for The SAS System to perform meta-analyses of clinical trials where the results of a single trial can be displayed in a fourfold-table. These macros provide the diagnostic plots most of which can be found in almost every meta-analysis publication (Funnel-Plot, confidence interval plot, Galbraith-Plot, Sensitivity-Plot by Thompson) as well as the computation of the different estimators of the treatment effect along with their summary estimators. Results from a meta-analysis on the comparison of low-molecular weight heparin and standard heparin for the prophylaxis of thromboembolic events are used for illustrative purposes.

A reduced heart rate variability (HRV) is a marker of autonomic dysfunction and has been shown to be associated with an increased risk of cardiovascular morbidity and mortality. However, especially regarding the association of HRV with cardiovascular risk factors the literature is rather inconsistent. We therefore critically discuss the review of Thayer et al. concerning the relationship between autonomic imbalance, heart rate variability and cardiovascular disease risk factors.

With great interest we read the recent publication of Sohn et al. [Sohn, S.Y., Chang, I.S., Moon, T.H., 2007. Random effects Weibull regression model for occupational lifetime. European Journal of Operational Research 179, 124–131] on a Weibull regression model with random effects for modelling occupational lifetime. We congratulate Sohn and colleagues on their comprehensive and clearly written paper. Nevertheless, we would like to comment on two points, the first regarding the moments of the underlying Weibull distribution, the second regarding the relations of Sohn’s model to the class of frailty models.

ObjectiveDespite numerous randomized and nonrandomized trials on off- and on-pump coronary artery bypass grafting, it remains open which method is superior. Patient selection and small sample sizes limit the evidence from randomized trials; lack of randomization limits the evidence from nonrandomized trials. Propensity score analyses are expected to improve on at least some of these problems. We aimed to systematically review all propensity score analyses comparing off- and on-pump coronary artery bypass grafting.MethodsPropensity score analyses comparing off- and on-pump surgery were identified from 8 bibliographic databases, citation tracking, and a free web search. Two independent reviewers abstracted data on 11 binary short-term outcomes.ResultsA total of 35 of 58 initially retrieved propensity score analyses were included, accounting for a total of 123,137 patients. The estimated overall odds ratio was less than 1 for all outcomes, favoring off-pump surgery. This benefit was statistically significant for mortality (odds ratio, 0.69; 95% confidence interval, 0.60–0.75), stroke, renal failure, red blood cell transfusion (P < .0001), wound infection (P < .001), prolonged ventilation (P < .01), inotropic support (P = .02), and intraaortic balloon pump support (P = .05). The odds ratios for myocardial infarction, atrial fibrillation, and reoperation for bleeding were not significant.ConclusionsOur systematic review and meta-analysis of propensity score analyses finds off-pump surgery superior to on-pump surgery in all of the assessed short-term outcomes. This advantage was statistically significant and clinically relevant for most outcomes, especially for mortality, the most valid criterion. These results agree with previous systematic reviews of randomized and nonrandomized trials.