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We propose a parametric model for describing chronic disease mortality from cohort data and illustrate its use for Type 2 diabetes. The model uses ideas from accelerated life testing in reliability theory and conceptualizes the occurrence of a chronic disease as putting the observational unit to an enhanced stress level, which is supposed to shorten its lifetime. It further addresses the issue of semi-competing risk, that is, the asymmetry of death and diagnosis of disease, where the disease can be diagnosed before death, but not after. With respect to the cohort structure of the data, late entry into the cohort is taken into account and prevalent as well as incident cases inform the analysis. We finally give an extension of the model that allows age at disease diagnosis to be observed not exactly, but only partially within an interval. Model parameters can be straightforwardly estimated by Maximum Likelihood, using the assumption of a Gompertz distribution we show in a small simulation study that this works well. Data of the Cardiovascular Disease, Living and Ageing in Halle (CARLA) study, a population-based cohort in the city of Halle (Saale) in the eastern part of Germany, are used for illustration., (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)

Aim: To investigate the associations of the Dietary Approaches to Stop Hypertension (DASH) score with subcutaneous (SAT) and visceral (VAT) adipose tissue volume and hepatic lipid content (HLC) in people with diabetes and to examine whether changes in the DASH diet were associated with changes in these outcomes., Methods: In total, 335 participants with recent-onset type 1 diabetes (T1D) and type 2 diabetes (T2D) from the German Diabetes Study were included in the cross-sectional analysis, and 111 participants in the analysis of changes during the 5-year follow-up. Associations between the DASH score and VAT, SAT and HLC and their changes were investigated using multivariable linear regression models by diabetes type. The proportion mediated by changes in potential mediators was determined using mediation analysis., Results: A higher baseline DASH score was associated with lower HLC, especially in people with T2D (per 5 points: -1.5% [-2.7%; -0.3%]). Over 5 years, a 5-point increase in the DASH score was associated with decreased VAT in people with T2D (-514 [-800; -228] cm 3 ). Similar, but imprecise, associations were observed for VAT changes in people with T1D (-403 [-861; 55] cm 3 ) and for HLC in people with T2D (-1.3% [-2.8%; 0.3%]). Body mass index and waist circumference changes explained 8%-48% of the associations between DASH and VAT changes in both groups. In people with T2D, adipose tissue insulin resistance index (Adipo-IR) changes explained 47% of the association between DASH and HLC changes., Conclusions: A shift to a DASH-like diet was associated with favourable VAT and HLC changes, which were partly explained by changes in anthropometric measures and Adipo-IR., (© 2024 John Wiley & Sons Ltd.)

The development of new statistical models for the meta-analysis of diagnostic test accuracy studies is still an ongoing field of research, especially with respect to summary receiver operating characteristic (ROC) curves. In the recently published updated version of the "Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy", the authors point to the challenges of this kind of meta-analysis and propose two approaches. However, both of them come with some disadvantages, such as the nonstraightforward choice of priors in Bayesian models or the requirement of a two-step approach where parameters are estimated for the individual studies, followed by summarizing the results. As an alternative, we propose a novel model by applying methods from time-to-event analysis. To this task we use the discrete proportional hazard approach to treat the different diagnostic thresholds, that provide means to estimate sensitivity and specificity and are reported by the single studies, as categorical variables in a generalized linear mixed model, using both the logit- and the asymmetric cloglog-link. This leads to a model specification with threshold-specific discrete hazards, avoiding a linear dependency between thresholds, discrete hazard, and sensitivity/specificity and thus increasing model flexibility. We compare the resulting models to approaches from the literature in a simulation study. While the estimated area under the summary ROC curve is estimated comparably well in most approaches, the results depict substantial differences in the estimated sensitivities and specificities. We also show the practical applicability of the models to data from a meta-analysis for the screening of type 2 diabetes., (© 2024 The Author(s). Research Synthesis Methods published by John Wiley & Sons Ltd.)

In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing meta-analyses from the Cochrane Database of Systematic Reviews in scenarios with zero event trials and few trials. For each scenario, we computed one-stage methods (Generalised linear mixed model [GLMM], Beta-binomial model [BBM], Bayesian binomial-normal hierarchical model using a weakly informative prior [BNHM-WIP]) and compared them with conventional methods (Peto-Odds-ratio [PETO], DerSimonian-Laird method [DL] for zero event trials; DL, Paule-Mandel [PM], Restricted maximum likelihood [REML] method for few trials). While all methods showed similar treatment effect estimates, substantial variability in statistical precision emerged. Conventional methods generally resulted in smaller confidence intervals (CIs) compared to one-stage models in the zero event situation. In the few trials scenario, the CI lengths were widest for the BBM on average and significance often changed compared to the PM and REML, despite the relatively wide CIs of the latter. In agreement with simulations and guidelines for meta-analyses with zero event trials, our results suggest that one-stage models are preferable. The best model can be either selected based on the data situation or, using a method that can be used in various situations. In the few trial situation, using BBM and additionally PM or REML for sensitivity analyses appears reasonable when conservative results are desired. Overall, our results encourage careful method selection., (© 2024 The Author(s). Research Synthesis Methods published by John Wiley & Sons Ltd.)

Weighting methods are widely used for causal effect estimation in non-randomised studies. In general, these methods use the propensity score (PS), the probability of receiving the treatment given the covariates, to arrive at the respective weights. All of these "modelling" methods actually optimize prediction of the respective outcome, which is, in the PS model, treatment assignment. However, this does not match with the actual aim of weighting, which is eliminating the association between covariates and treatment assignment. In the "balancing" approach, covariates are thus balanced directly by solving systems of numerical equations, explicitly without fitting a PS model. To compare modelling, balancing and hybrid approaches to weighting we performed a large simulation study for a binary treatment and a survival outcome. For maximal practical relevance all simulation parameters were selected after a systematic review of medical studies that used PS methods for analysis. We also introduce a new hybrid method that uses the idea of the covariate balancing propensity score and matching weights, thus avoiding extreme weights. In addition, we present a corrected robust variance estimator for some of the methods. Overall, our simulations results indicate that balancing approach methods work worse than expected. However, among the considered balancing methods, entropy balancing consistently outperforms the variance balancing approach. All methods estimating the average treatment effect in the overlap population perform well with very little bias and small standard errors even in settings with misspecified propensity score models. Finally, the coverage using the standard robust variance estimator was too high for all methods, with the proposed corrected robust variance estimator improving coverage in a variety of settings., (© 2024 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Aims: The Gompertz law of mortality proclaims that human mortality rates in middle to old ages grow log-linearly with age and this law has been confirmed at multiple instances. We investigated if diabetes mortality in Germany also obeys to the Gompertz law and how this information helps to communicate diabetes mortality more intuitively., Methods: We analyzed all statutory health-insured persons in Germany in 2013 that were aged 30 years or older. Deaths in 2014 were recorded and given in 5-year age groups. We fitted weighted linear regression models (separately for females and males and for people with and without diabetes) and additionally computed the probability that a person with diabetes dies before a person of the same age and sex without diabetes, and the "diabetes age", that is, the additional years of mortality risk added to an individual's chronological age due to diabetes-related excess mortality., Results: We included N = 47,365,120 individuals, 6,541,181 of them with diabetes. In 2014, 763,228 deaths were recorded, among them 288,515 with diabetes. Diabetes mortality followed nearly perfectly Gompertz distributions. The probability that a person with diabetes dies before a person without diabetes was 61.9% for females and 63.3% for males., Conclusions: Diabetes mortality for females and males aged 30 years or older in Germany in 2014 followed the Gompertz law of mortality. The survival information of the population with diabetes during a large part of the lifespan can thus be reduced to the two parameters of the Gompertz distribution., (© 2024. The Author(s).)

Time-to-event analysis often relies on prior parametric assumptions, or, if a semiparametric approach is chosen, Cox's model. This is inherently tied to the assumption of proportional hazards, with the analysis potentially invalidated if this assumption is not fulfilled. In addition, most interpretations focus on the hazard ratio, that is often misinterpreted as the relative risk (RR), the ratio of the cumulative distribution functions. In this paper, we introduce an alternative to current methodology for assessing a treatment effect in a two-group situation, not relying on the proportional hazards assumption but assuming proportional risks. Precisely, we propose a new nonparametric model to directly estimate the RR of two groups to experience an event under the assumption that the risk ratio is constant over time. In addition to this relative measure, our model allows for calculating the number needed to treat as an absolute measure, providing the possibility of an easy and holistic interpretation of the data. We demonstrate the validity of the approach by means of a simulation study and present an application to data from a large randomized controlled trial investigating the effect of dapagliflozin on all-cause mortality., (© 2024 The Authors. Biometrical Journal published by Wiley‐VCH GmbH.)

Aims: To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability., Methods: We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta-regression analyses were performed with respect to variability of body weight after treatment and potential predictors., Results: A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta-regression model, the difference in body weight log(SD) was -0.026 (95% confidence interval -0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo)., Conclusions: We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting., (© 2024 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Background: Water T 1 of the liver has been shown to be promising in discriminating the progressive forms of fatty liver diseases, inflammation, and fibrosis, yet proper correction for iron and lipid is required., Purpose: To examine the feasibility of an empirical approach for iron and lipid correction when measuring imaging-based T 1 and to validate this approach by spectroscopy on in vivo data., Study Type: Retrospective., Population: Next to mixed lipid-iron phantoms, individuals with different hepatic lipid content were investigated, including people with type 1 diabetes (N = 15, %female = 15.6, age = 43.5 ± 14.0), or type 2 diabetes mellitus (N = 21, %female = 28.9, age = 59.8 ± 9.7) and healthy volunteers (N = 9, %female = 11.1, age = 58.0 ± 8.1)., Field Strength/sequences: 3 T, balanced steady-state free precession MOdified Look-Locker Inversion recovery (MOLLI), multi- and dual-echo gradient echo Dixon, gradient echo magnetic resonance elastography (MRE)., Assessment: T 1 values were measured in phantoms to determine the respective correction factors. The correction was tested in vivo and validated by proton magnetic resonance spectroscopy ( 1 H-MRS). The quantification of liver T 1 based on automatic segmentation was compared to the T 1 values based on manual segmentation. The association of T 1 with MRE-derived liver stiffness was evaluated., Statistical Tests: Bland-Altman plots and intraclass correlation coefficients (ICCs) were used for MOLLI vs. 1 H-MRS agreement and to compare liver T 1 values from automatic vs. manual segmentation. Pearson's r correlation coefficients for T 1 with hepatic lipids and liver stiffness were determined. A P-value of 0.05 was considered statistically significant., Results: MOLLI T 1 values after correction were found in better agreement with the 1 H-MRS-derived water T 1 (ICC = 0.60 [0.37; 0.76]) in comparison with the uncorrected T 1 values (ICC = 0.18 [-0.09; 0.44]). Automatic quantification yielded similar liver T 1 values (ICC = 0.9995 [0.9991; 0.9997]) as with manual segmentation. A significant correlation of T 1 with liver stiffness (r = 0.43 [0.11; 0.67]) was found. A marked and significant reduction in the correlation strength of T 1 with liver stiffness (r = 0.05 [-0.28; 0.38], P = 0.77) was found after correction for hepatic lipid content., Data Conclusion: Imaging-based correction factors enable accurate estimation of water T 1 in vivo., Level of Evidence: 1 TECHNICAL EFFICACY: Stage 1., (© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Absolute treatment benefits-expressed as numbers needed to treat-of the glucose lowering and cardiovascular drugs, glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose transporter 2 (SGLT2) inhibitors on renal outcomes remain uncertain. With the present meta-analysis of digitalized individual patient data, we aimed to display and compare numbers needed to treat of both drugs on a composite renal outcome., Methods: From Kaplan-Meier plots of major cardiovascular outcome trials of GLP-1 receptor agonists and SGLT2 inhibitors vs. placebo, we digitalized individual patient time-to-event information on composite renal outcomes with WebPlotDigitizer 4.2; numbers needed to treat from individual cardiovascular outcome trials were estimated using parametric Weibull regression models and compared to original data. Random-effects meta-analysis generated meta-numbers needed to treat with 95% confidence intervals (CI)., Results: Twelve cardiovascular outcome trials (three for GLP-1 receptor agonists, nine for SGLT2 inhibitors) comprising 90,865 participants were included. Eight trials were conducted in primary type 2 diabetes populations, two in a primary heart failure and two in a primary chronic kidney disease population. Mean estimated glomerular filtration rate at baseline ranged between 37.3 and 85.3 ml/min/1.73 m 2 . Meta-analyses estimated meta-numbers needed to treat of 85 (95% CI 60; 145) for GLP-1 receptor agonists and 104 (95% CI 81; 147) for SGLT2 inhibitors for the composite renal outcome at the overall median follow-up time of 36 months., Conclusion: The present meta-analysis of digitalized individual patient data revealed moderate and similar absolute treatment benefits of GLP-1 receptor agonists and SGLT2 inhibitors compared to placebo for a composite renal outcome., (© 2024. The Author(s).)

Background: In recent years, the use of non- and semi-parametric models which estimate hazard ratios for analysing time-to-event outcomes is continuously criticized in terms of interpretation, technical implementation, and flexibility. Hazard ratios in particular are critically discussed for their misleading interpretation as relative risks and their non-collapsibility. Additive hazard models do not have these drawbacks but are rarely used because they assume a non- or semi-parametric additive hazard which renders computation and interpretation complicated., Methods: As a remedy, we propose a new parametric additive hazard model that allows results to be reported on the original time rather than on the hazard scale. Being an essentially parametric model, survival, hazard and probability density functions are directly available. Parameter estimation is straightforward by maximizing the log-likelihood function., Results: Applying the model to different parametric distributions in a simulation study and in an exemplary application using data from a study investigating medical care to lung cancer patients, we show that the approach works well in practice., Conclusions: Our proposed parametric additive hazard model can serve as a powerful tool to analyze time-to-event outcomes due to its simple interpretation, flexibility and facilitated parameter estimation., (© 2024. The Author(s).)

Background: Heterogeneity in type 2 diabetes can be represented by a tree-like graph structure by use of reversed graph-embedded dimensionality reduction. We aimed to examine whether this approach can be used to stratify key pathophysiological components and diabetes-related complications during longitudinal follow-up of individuals with recent-onset type 2 diabetes., Methods: For this cohort analysis, 927 participants aged 18-69 years from the German Diabetes Study (GDS) with recent-onset type 2 diabetes were mapped onto a previously developed two-dimensional tree based on nine simple clinical and laboratory variables, residualised for age and sex. Insulin sensitivity was assessed by a hyperinsulinaemic-euglycaemic clamp, insulin secretion was assessed by intravenous glucose tolerance test, hepatic lipid content was assessed by 1 H magnetic resonance spectroscopy, serum interleukin (IL)-6 and IL-18 were assessed by ELISA, and peripheral and autonomic neuropathy were assessed by functional and clinical measures. Participants were followed up for up to 16 years. We also investigated heart failure and all-cause mortality in 794 individuals with type 2 diabetes undergoing invasive coronary diagnostics from the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort., Findings: There were gradients of clamp-measured insulin sensitivity (both dimensions: p<0·0001) and insulin secretion (p dim1 <0·0001, p dim2 =0·00097) across the tree. Individuals in the region with the lowest insulin sensitivity had the highest hepatic lipid content (n=205, p dim1 <0·0001, p dim2 =0·037), pro-inflammatory biomarkers (IL-6: n=348, p dim1 <0·0001, p dim2 =0·013; IL-18: n=350, p dim1 <0·0001, p dim2 =0·38), and elevated cardiovascular risk (n events =143, p dim1 =0·14, p dim2 <0·00081), whereas individuals positioned in the branch with the lowest insulin secretion were more prone to require insulin therapy (n events =85, p dim1 =0·032, p dim2 =0·12) and had the highest risk of diabetic sensorimotor polyneuropathy (n events =184, p dim1 =0·012, p dim2 =0·044) and cardiac autonomic neuropathy (n events =118, p dim1 =0·0094, p dim2 =0·06). In the LURIC cohort, all-cause mortality was highest in the tree branch showing insulin resistance (n events =488, p dim1 =0·12, p dim2 =0·0032). Significant gradients differentiated individuals having heart failure with preserved ejection fraction from those who had heart failure with reduced ejection fraction., Interpretation: These data define the pathophysiological underpinnings of the tree structure, which has the potential to stratify diabetes-related complications on the basis of routinely available variables and thereby expand the toolbox of precision diabetes diagnosis., 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, European Community, German Research Foundation, and Schmutzler Stiftung., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: Studies have shown an increased incidence of pediatric type 1 diabetes during the COVID-19 pandemic, but the detailed role of SARS-CoV-2 infection in the incidence increase in type 1 diabetes remains unclear. We investigated the spatiotemporal association of pediatric type 1 diabetes and COVID-19 incidence at the district level in Germany., Methods: For the period from March 2020 to June 2022, nationwide data on incident type 1 diabetes among children and adolescents aged <20 years and daily documented COVID-19 infections in the total population were obtained from the German Diabetes Prospective Follow-up Registry and the Robert Koch Institute, respectively. Data were aggregated at district level and seven time periods related to COVID-19 pandemic waves. Spatiotemporal associations between indirectly standardized incidence rates of type 1 diabetes and COVID-19 were analyzed by Spearman correlation and Bayesian spatiotemporal conditional autoregressive Poisson models., Results: Standardized incidence ratios of type 1 diabetes and COVID-19 in the pandemic period were not significantly correlated across districts and time periods. A doubling of the COVID-19 incidence rate was not associated with a significant increase in the incidence rate of type 1 diabetes (relative risk 1.006, 95% CI 0.987; 1.019)., Conclusion: Our findings based on data from the pandemic period indirectly indicate that a causal relationship between SARS-COV-2 infection and type 1 diabetes among children and adolescents is unlikely., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Rosenbauer, Stahl-Pehe, Baechle, Lanzinger, Kamrath, Kuß and Holl.)

The aim was to investigate prevalence of dry eye syndrome (DES) in a population-based sample in Germany. The association between coexisting eye diseases and DES was also of interest. We recontacted participants of the Heinz Nixdorf Recall study between 2018 and 2021 by postal questionnaire that included the Women's Health Study questionnaire on DES. We estimated prevalence of DES and examined DES-associated factors among 2095 participants aged 62-91 years. We performed interaction analyses between sex and coexisting eye diseases in relation to the DES prevalence and performed bias analyses to examine the robustness of the results. The DES prevalence was 31.5% (34-36% after correction for potential non-response bias, 24.1% after correction for outcome misclassification) and it was almost 2.1-times higher in women than in men (women 42.3%, men 20.4%). Among DES subjects, 70.3% had received treatment in the previous 12 months. There was synergism between female sex and coexisting eye diseases (cataract, glaucoma, macular degeneration) in terms of DES prevalence. The extrapolated numbers of patients aged 62-91 years with DES in Germany are 1.1-1.3 million men and 6.1-6.8 million women. The observed synergism may be explained by differences in ocular physiology, subjective perception and response behavior. Women with eye diseases (cataract, glaucoma, macula degeneration) appear to have a markedly higher susceptibility to suffer from DES than men, so that a diagnostic workup of DES symptoms is particularly justified in women with these eye diseases., (© 2024. The Author(s).)

Background: Mediation analysis addresses the question of the mechanisms by which an exposure causes an outcome. This article is intended to convey basic knowledge of statistical mediation analysis., Methods: Selected articles and examples are used to explain the principle of mediation analysis., Results: The goal of mediation analysis is to express an overall exposure effect as a combination of an indirect and a direct effect. For example, it might be of interest whether the increased risk of diabetes (outcome) due to obesity (exposure) is mediated by insulin resistance (indirect effect), and, if so, how much of a direct effect remains. In this example, insulin resistance is a potential mediator of the effect of obesity on the risk of diabetes. In general, for a mediation analysis to be valid, more confounders must be taken into account than in the estimation of the overall effect size. A regression-based approach can be used to ensure the consideration of all relevant confounders in a mediation analysis., Conclusion: By decomposing the overall exposure effect into indirect and direct components, a mediation analysis can reveal not just whether an exposure causes an outcome, but also how. For a mediation analysis to be valid, however, multiple assumptions must be satisfied that cannot easily be checked, potentially compromising such analyses as compared to the estimation of an overall effect.

Introduction: Automated insulin delivery (AID), also known as artificial pancreas system or 'closed-loop system', represents a novel option for current treatments for type 1 diabetes (T1D). The objective of this systematic review and meta-analysis is to assess the efficacy of AID systems in comparison with current intensified insulin therapy for glycaemic control and patient-reported outcomes in individuals with T1D., Methods and Analysis: Studies will be eligible if they are randomised controlled trials (RCTs) in people with T1D of all ages, and if they compare an AID system for self-administration during the day and night period with any other type of insulin therapy for at least 3 weeks. The primary outcome will be time in the glucose target range of 70-180 mg/dL. A systematic review will be conducted in the MEDLINE, Embase, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov registries from their inception dates. Two authors will independently screen all references based on titles and abstracts against the eligibility criteria. For data extraction, standard forms will be developed and tested before extraction. All information will be assessed independently by at least two reviewers. The risk of bias of the included studies will be assessed using the Cochrane Risk of Bias 2 tool. The data synthesis will include a random-effects pairwise and network meta-analysis (NMA) in a frequentist framework. Where applicable and if sufficient RCTs are available, sensitivity analyses will be performed, and heterogeneity and publication bias will be assessed. The certainty of evidence from the NMA will be evaluated following the Grading of Recommendations Assessment, Development, and Evaluation working group guidance., Ethics and Dissemination: No ethical approval is needed. The results will be reported to the funder, presented in a peer-reviewed scientific journal and at conferences, and disseminated via press release, social media and public events., Prospero Registration Number: CRD42023395492., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background/objectives: Findings from epidemiological studies showed controversial findings between dietary sugar intake and the development of diabetes. Most of these studies assessed dietary sugar intake by self-reports which might be prone to bias. Urinary sucrose, an objective biomarker of sucrose intake, might provide better insights into this association. Thus, the aim of this study was to investigate the associations between sucrose intake, measured via self-reports and urinary sucrose, with incident diabetes and to detect the impact of obesity on this association., Subjects/methods: Data of a sub-group (n = 2996) from the prospective EPIC-Norfolk cohort were investigated. Sucrose intake was assessed by self-reports (validated food frequency questionnaire (FFQ) and 7-day diet diaries (7DD)) and as an objective urinary sucrose biomarker. Cox proportional hazard models were conducted to calculate hazard ratios (HRs) and 95% confidence intervals (CI) for the associations between urinary and dietary sucrose intake and incident diabetes. Mediation analysis was performed to investigate the mediated percentage of body mass index (BMI) and waist circumference (WC) on this association., Results: The mean age of the participants was 60.6 ± 9.5 years and 53% were women. After a mean follow-up of 11.2 ± 2.9 years, 97 participants developed diabetes. Findings suggested inverse associations regarding incident diabetes for self-reported sucrose intake per 50 g/d via 7DD [HR: 0.63 (95% CI: 0.43, 0.91)], and a tendency via FFQ [HR: 0.81 (95% CI: 0.46, 1.42)]. Urinary sucrose indicated a positive association with incident diabetes for each increase of 100 µM [HR: 1.14 (95% CI: 0.95, 1.36)]. The proportion mediated of BMI and WC for this association was 16 and 22%., Conclusions: These findings indicate that sucrose measured as objective urinary biomarker points to a positive association with incident diabetes. BMI might partly mediate this association. However, to obtain more precise results, more studies are warranted that consider this objective biomarker., (© 2023. Springer Nature Limited.)

Aims/hypothesis: There are two prerequisites for the precision medicine approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in the case of treatment heterogeneity, we need to detect clinical predictors to identify people who would benefit from one treatment more than from others. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials. Our aim was to apply this approach to the treatment of type 2 diabetes., Methods: We performed a meta-regression analysis using information from 174 placebo-controlled randomised trials with 178 placebo and 272 verum (i.e. active treatment) arms including 86,940 participants with respect to the variability of glycaemic control as assessed by HbA 1c after treatment and its potential predictors., Results: The adjusted difference in log(SD) values between the verum and placebo arms was 0.037 (95% CI: 0.004, 0.069). That is, we found a small increase in the variability of HbA 1c values after treatment in the verum arms. In addition, one potentially relevant predictor for explaining this increase, drug class, was observed, and GLP-1 receptor agonists yielded the largest differences in log(SD) values., Conclusions/interpretation: The potential of the precision medicine approach in the treatment of type 2 diabetes is modest at best, at least with regard to an improvement in glycaemic control. Our finding of a larger variability after treatment with GLP-1 receptor agonists in individuals with poor glycaemic control should be replicated and/or validated with other clinical outcomes and with different study designs., Funding: The research reported here received no specific grant from any funding agency in the public, commercial or not-for-profit sectors., Data Availability: Two datasets (one for the log[SD] and one for the baseline-corrected log[SD]) to reproduce the analyses from this paper are available on https://zenodo.org/record/7956635 ., (© 2023. The Author(s).)

Aims/hypothesis: To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death., Methods: This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach., Results: A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA 1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m 2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×10 9 /l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19  vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out., Conclusions/interpretation: Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease., Registration: PROSPERO registration no. CRD42020193692., Previous Version: This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD)., (© 2023. The Author(s).)

The use of hazard ratios as the standard treatment effect estimators for randomized trials with time-to-event outcomes has been the subject of repeated criticisms in recent years, e.g., for its non-collapsibility or with respect to (causal) interpretation. Another important issue is the built-in selection bias, which arises when the treatment is effective and when there are unobserved or not included prognostic factors that influence time-to-event. In these cases, the hazard ratio has even been termed "hazardous" because it is estimated from groups that increasingly differ in their (unobserved or omitted) baseline characteristics, yielding biased treatment estimates. We therefore adapt the Landmarking approach to assess the effect of ignoring a gradually increasing proportion of early events on the estimated hazard ratio. We propose an extension called "Dynamic Landmarking". This approach is based on successive deletion of observations, refitting Cox models and balance checking of omitted but observed prognostic factors, to obtain a visualization that can indicate built-in selection bias. In a small proof-of-concept simulation, we show that our approach is valid under the given assumptions. We further use "Dynamic Landmarking" to assess the suspected selection bias in the individual patient data sets of 27 large randomized clinical trials (RCTs). Surprisingly, we find no empirical evidence of selection bias in these RCTs and thus conclude that the supposed bias of the hazard ratio is of little practical relevance in most cases. This is mainly due to treatment effects in RCTs being small and the patient populations being homogeneous, e.g., due to inclusion and exclusion criteria., (© 2023. Springer Nature B.V.)

Background: Primary retroperitoneal lymph node dissection (RPLND) for clinical stage (CS) IIA/B seminoma without adjuvant treatment is an experimental treatment to avoid radiotherapy- or chemotherapy-related toxicity from standard treatment., Objective: The PRIMETEST trial aimed to prospectively evaluate the oncological efficacy and surgical safety of primary RPLND., Design, Setting, and Participants: PRIMETEST is a single-arm, single-center prospective phase 2 trial. Patients with seminoma, unilateral retroperitoneal lymph node metastases <5 cm, and human chorionic gonadotropin levels <5 mU/ml were included. Patients with CS IIA/B seminoma at initial diagnosis, and recurrence under active surveillance or following adjuvant carboplatin for CS I disease were eligible., Outcome Measurements and Statistical Analysis: Unilateral open or robot-assisted primary RPLND was performed. The primary endpoint of the study was progression-free survival (PFS) after 36 mo. The trial was considered positive if <30% of patients experienced a recurrence., Results and Limitations: Between 2016 and 2021, 33 patients were accrued (nine with primary CS IIA/B, 19 recurrences during active surveillance, and five recurrences following adjuvant carboplatin). Thirteen and 20 patients had CS IIA and IIB, respectively. Open and robot-assisted RPLND procedures were performed in 14 (42%) and 19 (58%) patients, respectively. After a median follow-up of 32 mo (interquartile range 23-46), ten recurrences were detected (30%, 95% confidence interval: 16-49%); thus, the primary endpoint was not met. Infield recurrences occurred in three of ten patients. The current analysis of risk factors could not identify the predictors of recurrence. Three of 33 patients (9%) presented with pN0., Conclusions: The PRIMETEST trial did not meet its primary endpoint. Nevertheless, PFS of 70% after a median follow-up of 32 mo suggests this approach to be of interest for highly selected patients. Selection criteria, however, need to be defined and validated in a larger prospective cohort of patients. Until then, surgery alone for the treatment of patients with CS IIA/B seminoma cannot be recommended outside of a clinical trial setting., Patient Summary: In this study, we investigated primary surgery as an alternative to conventional treatment (chemotherapy or radiation therapy) in patients with metastatic seminoma. The primary objective of the study, to prevent at least 30% of patients from recurrence, was not met. However, certain patients may benefit from this approach and thereby avoid chemotherapy or radiation therapy. Predictive factors need to be analyzed to better select patients for this surgery-only approach., (Copyright © 2022 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Introduction: To investigate the associations of a lifestyle score with various cardiovascular risk markers, indicators for fatty liver disease as well as MRI-determined total, subcutaneous and visceral adipose tissue mass in adults with new-onset diabetes., Research Design and Methods: This cross-sectional analysis included 196 individuals with type 1 (median age: 35 years; median body mass index (BMI): 24 kg/m²) and 272 with type 2 diabetes (median age: 53 years; median BMI: 31 kg/m²) from the German Diabetes Study. A healthy lifestyle score was generated based on healthy diet, moderate alcohol consumption, recreational activity, non-smoking and non-obese BMI. These factors were summed to form a score ranging from 0 to 5. Multivariable linear and non-linear regression models were used., Results: In total, 8.1% of the individuals adhered to none or one, 17.7% to two, 29.7% to three, 26.7% to four, and 17.7% to all five favorable lifestyle factors. High compared with low adherence to the lifestyle score was associated with more favorable outcome measures, including triglycerides (β (95% CI) -49.1 mg/dL (-76.7; -21.4)), low-density lipoprotein (-16.7 mg/dL (-31.3; -2.0)), and high-density lipoprotein cholesterol (13.5 mg/dL (7.6; 19.4)), glycated hemoglobin (-0.5% (-0.8%; -0.1%)), high-sensitivity C reactive protein (-0.4 mg/dL (-0.6; -0.2)), as well as lower hepatic fat content (-8.3% (-11.9%; -4.7%)), and visceral adipose tissue mass (-1.8 dm³ (-2.9; -0.7)). The dose-response analyses showed that adherence to every additional healthy lifestyle factor was associated with more beneficial risk profiles., Conclusions: Adherence to each additional healthy lifestyle factor was beneficially associated with cardiovascular risk markers, indicators of fatty liver disease and adipose tissue mass. Strongest associations were observed for adherence to all healthy lifestyle factors in combination., Trial Registration Number: NCT01055093., Competing Interests: Competing interests: MR has been on scientific advisory boards of Allergan, AstraZeneca, Bristol Myers Squibb, Eli Lilly, Gilead Sciences, Inventiva, Intercept Pharma, Novartis, Novo Nordisk, Servier Laboratories, Target NRW and Terra Firma; and received support for investigator-initiated studies from Boehringer Ingelheim, Nutricia/Danone and Sanofi-Aventis. CH received a research grant from Sanofi-Aventis outside the submitted work. SS received a research grant from ALPRO outside the submitted work. The other authors declare that they have no conflicts of interest to disclose., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aim: To identify distinct HbA1c trajectories in people with type 2 diabetes (T2D) starting second-line glucose-lowering therapy., Materials and Methods: DISCOVER was a 3-year observational study of individuals with T2D beginning second-line glucose-lowering therapy. Data were collected at initiation of second-line treatment (baseline) and at 6, 12, 24 and 36 months. Latent class growth modelling was used to identify groups with distinct HbA1c trajectories., Results: After exclusions, 9295 participants were assessed. Four distinct HbA1c trajectories were identified. Mean HbA1c levels decreased between baseline and 6 months in all groups; 72.4% of participants showed stable good levels of glycaemic control over the remainder of follow-up, 18.0% showed stable moderate levels of glycaemic control and 2.9% showed stable poor levels of glycaemic control. Only 6.7% of participants showed highly improved glycaemic control at month 6 and stable control over the rest of follow-up. For all groups, dual oral therapy use decreased over time, compensated for by the increasing use of other treatment regimens. Use of injectable agents increased over time in groups with moderate and poor glycaemic control. Logistic regression models suggested that participants from high-income countries were more probable to be in the stable good trajectory group., Conclusions: Most people receiving second-line glucose-lowering treatment in this global cohort achieved stable good or highly improved long-term glycaemic control. One-fifth of participants showed moderate or poor glycaemic control during follow-up. Further large-scale studies are required to characterize possible factors associated with patterns of glycaemic control to inform personalized diabetes treatment., (© 2023 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Objective: We investigated whether COVID-19 vaccination had an impact on diabetes risk., Methods: We used data of 6,198 patients (mean age 64.3 years) from the nationwide Disease Analyzer database, a representative panel of physicians' practices in Germany. Patients received their first COVID-19 vaccination between 1 April 2021 and 31 March 2022, and all were newly diagnosed with diabetes within 183 days before or after this vaccination. Incident rates of diabetes after vaccination were compared to incident rates before vaccination., Results: The incidence rate of diabetes was lower after vaccination than before vaccination (incidence rate ratio = 0.79, 95% confidence interval: 0.75-0.83). The number of incident cases of diabetes was not greater in 2021 than in 2019., Conclusion: Our study did not confirm an increased risk of diabetes after COVID-19 vaccination. Further studies are needed to show whether the vaccination may be associated with a reduced diabetes risk., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Objectives: Left atrial appendage (LAA) amputation concomitant to coronary artery bypass grafting (CABG) has become an increasingly performed technique in patients with atrial fibrillation (AF) or with sinus rhythm and a CHA2DS2-VASc score ≥2. However, LAA amputation has come under suspicion to cause postoperative atrial fibrillation (POAF) due to left atrial (LA) dilation. This study aims to assess this assumption in patients undergoing CABG in off-pump technique with and without amputation of the LAA., Methods: Patients who underwent isolated CABG in off-pump technique without history of AF were retrospectively examined. Cohorts were divided according to the concomitant execution of LAA amputation. LA volume was measured by transthoracic echocardiography and rhythm was analyzed by electrocardiography, medication protocol, and visit documentation. Propensity score (PS) matching was performed based on 20 preoperative risk variables to correct for selection bias., Results: A total of 1,522 patients were enrolled, with 1,267 in the control group and 255 in the LAA amputation group. Occurrence of POAF was compared in 243 PS-matched patient pairs. Neither the unmatched cohort (odds ratio [OR] 0.82; 95% confidence interval or CI [0.61; 1.11], p  = 0.19) nor the PS-matched cohort (OR 0.94; 95% CI [0.62; 1.41], p  = 0.75) showed significant differences in POAF occurrence. Subgroup analysis of sex, use of β-blockers, pulmonary disease, ejection fraction, and CHA2DS2-VASc-Score also showed no tendencies. LA volume did not change significantly ( p  = 0.18, 95% CI [-0.29; 1.51])., Conclusion: Surgical amputation of the LAA concomitant to CABG did not lead to LA dilation and has no significant impact on the occurrence of POAF., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: There are no data on recent trends in the incidence rate of type 2 diabetes (T2D) in Germany. The aim of this study was to determine the sex-, age-, and region-specific trends in the T2D incidence rate between 2014 and 2019., Methods: Based on nationwide data from statutorily insured persons in Germany, negative binomial regression models were used to analyze age- and sex-specific trends in the T2D incidence rate. Age- and sex-adjusted trends were calculated for 401 administrative districts using a Bayesian spatio-temporal regression model., Results: During the period concerned, approximately 450 000 new cases of T2D were observed each year among some 63 million persons. Taking all age groups together, the incidence rate decreased in both women and men, from 6.9 (95% confidence interval [6.7; 7.0]) and 8.4 [8.2; 8.6] respectively per 1000 persons in 2014 to 6.1 [5.9; 6.3] and 7.7 [7.5; 8.0] per 1000 persons in 2019. This corresponds to an annual reduction of 2.4% [1.5; 3.2] for women and 1.7% [0.8; 2.5] for men. The incidence rate increased in the age group 20-39 years. The age- and sex-adjusted incidence rate decreased in almost all districts, although regional differences persisted., Conclusion: The T2D incidence rate should be closely monitored to see whether the decreasing trend continues. One must not forget that the prevalence can rise despite decreasing incidence. For this reason, the findings do not necessarily mean a decrease in the disease burden of T2D and the associated demand on healthcare resources.

Aims/hypothesis: No established blood-based biomarker exists to monitor diabetic sensorimotor polyneuropathy (DSPN) and evaluate treatment response. The neurofilament light chain (NFL), a blood biomarker of neuroaxonal damage in several neurodegenerative diseases, represents a potential biomarker for DSPN. We hypothesised that higher serum NFL levels are associated with prevalent DSPN and nerve dysfunction in individuals recently diagnosed with diabetes., Methods: This cross-sectional study included 423 adults with type 1 and type 2 diabetes and known diabetes duration of less than 1 year from the prospective observational German Diabetes Study cohort. NFL was measured in serum samples of fasting participants in a multiplex approach using proximity extension assay technology. DSPN was assessed by neurological examination, nerve conduction studies and quantitative sensory testing. Associations of serum NFL with DSPN (defined according to the Toronto Consensus criteria) were estimated using Poisson regression, while multivariable linear and quantile regression models were used to assess associations with nerve function measures. In exploratory analyses, other biomarkers in the multiplex panel were also analysed similarly to NFL., Results: DSPN was found in 16% of the study sample. Serum NFL levels increased with age. After adjustment for age, sex, waist circumference, height, HbA 1c , known diabetes duration, diabetes type, cholesterol, eGFR, hypertension, CVD, use of lipid-lowering drugs and use of non-steroidal anti-inflammatory drugs, higher serum NFL levels were associated with DSPN (RR [95% CI] per 1-normalised protein expression increase, 1.92 [1.50, 2.45], p<0.0001), slower motor (all p<0.0001) and sensory (all p≤0.03) nerve conduction velocities, lower sural sensory nerve action potential (p=0.0004) and higher thermal detection threshold to warm stimuli (p=0.023 and p=0.004 for hand and foot, respectively). There was no evidence for associations between other neurological biomarkers and DSPN or nerve function measures., Conclusions/interpretation: Our findings in individuals recently diagnosed with diabetes provide new evidence associating higher serum NFL levels with DSPN and peripheral nerve dysfunction. The present study advocates NFL as a potential biomarker for DSPN., (© 2022. The Author(s).)

Aims: Absolute treatment effects-i.e. numbers needed to treat (NNTs)-of novel antidiabetic drugs for cardiovascular outcomes have not been comprehensively evaluated. We aimed to perform a meta-analysis of digitalized individual patient outcomes to display and compare absolute treatment effects., Methods and Results: Individual patient time-to-event information from Kaplan-Meier plots of cardiovascular mortality (CM) and/or hospitalization for heart failure (HHF) endpoints from cardiovascular outcome trials (CVOTs) evaluating dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium glucose transporter 2 (SGLT2) inhibitors vs. placebo were digitalized using WebPlotDigitizer 4.2 and the R code of Guyot et al.; Weibull regression models were generated, validated, and used to estimate NNT for individual trials; random-effects meta-analysis generated Meta-NNT with 95% confidence intervals. Sixteen CVOTs reported time-to-event information (14 in primary diabetes and 2 in primary heart failure populations). Thirteen studies including 96 860 patients were meta-analysed for CM: At the median follow-up of 30 months, Meta-NNTs were 178 (64 to ∞ to -223) for DPP-4 inhibitors, 261 (158 to 745) for GLP-1 receptor agonists, and 118 (68 to 435) for SGLT2 inhibitors. Ten studies including 96 128 patients were meta-analysed for HHF: At the median follow-up of 29 months, estimated Meta-NNTs were -644 (229 to ∞ to -134) for DPP-4 inhibitors, 441 (184 to ∞ to -1100) for GLP-1 receptor agonists, and 126 (91 to 208) for SGLT2 inhibitors. SGLT2 inhibitors were especially effective for HHF in primary heart failure populations [Meta-NNT 25 (19 to 39)] vs. primary diabetes populations [Meta-NNT 233 (167 to 385)] at 16 months of follow-up., Conclusions: We found only modest treatment benefits of GLP-1 receptor agonists and SGLT2 inhibitors for CM and HHF in primary type 2 diabetes mellitus populations. In primary heart failure populations, SGLT2 inhibitor benefits were substantial and comparable in efficacy to established heart failure medication., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Impaired proinsulin-to-insulin processing in pancreatic β-cells is a key defective step in both type 1 diabetes and type 2 diabetes (T2D) (refs. 1 , 2 ), but the mechanisms involved remain to be defined. Altered metabolism of sphingolipids (SLs) has been linked to development of obesity, type 1 diabetes and T2D (refs. 3-8 ); nonetheless, the role of specific SL species in β-cell function and demise is unclear. Here we define the lipid signature of T2D-associated β-cell failure, including an imbalance of specific very-long-chain SLs and long-chain SLs. β-cell-specific ablation of CerS2, the enzyme necessary for generation of very-long-chain SLs, selectively reduces insulin content, impairs insulin secretion and disturbs systemic glucose tolerance in multiple complementary models. In contrast, ablation of long-chain-SL-synthesizing enzymes has no effect on insulin content. By quantitatively defining the SL-protein interactome, we reveal that CerS2 ablation affects SL binding to several endoplasmic reticulum-Golgi transport proteins, including Tmed2, which we define as an endogenous regulator of the essential proinsulin processing enzyme Pcsk1. Our study uncovers roles for specific SL subtypes and SL-binding proteins in β-cell function and T2D-associated β-cell failure., (© 2022. The Author(s).)

Background: Meta-analyses are used to summarise the results of several studies on a specific research question. Standard methods for meta-analyses, namely inverse variance random effects models, have unfavourable properties if only very few (2 - 4) studies are available. Therefore, alternative meta-analytic methods are needed. In the case of binary data, the "common-rho" beta-binomial model has shown good results in situations with sparse data or few studies. The major concern of this model is that it ignores the fact that each treatment arm is paired with a respective control arm from the same study. Thus, the randomisation to a study arm of a specific study is disrespected, which may lead to compromised estimates of the treatment effect. Therefore, we extended this model to a version that respects randomisation. The aim of this simulation study was to compare the "common-rho" beta-binomial model and several other beta-binomial models with standard meta-analyses models, including generalised linear mixed models and several inverse variance random effects models., Methods: We conducted a simulation study comparing beta-binomial models and various standard meta-analysis methods. The design of the simulation aimed to consider meta-analytic situations occurring in practice., Results: No method performed well in scenarios with only 2 studies in the random effects scenario. In this situation, a fixed effect model or a qualitative summary of the study results may be preferable. In scenarios with 3 or 4 studies, most methods satisfied the nominal coverage probability. The "common-rho" beta-binomial model showed the highest power under the alternative hypothesis. The beta-binomial model respecting randomisation did not improve performance., Conclusion: The "common-rho" beta-binomial appears to be a good option for meta-analyses of very few studies. As residual concerns about the consequences of disrespecting randomisation may still exist, we recommend a sensitivity analysis with a standard meta-analysis method that respects randomisation., (© 2022. The Author(s).)

Aims/hypothesis: The aim of this study was to analyze the incidence of type 1 diabetes in children and adolescents (<20 years of age) during the COVID-19 pandemic (3/2020 to 12/2021) in Germany., Methods: The present study was based on the IQVIA longitudinal prescription database (LRx), All persons (age ≤ 20 years) with new insulin prescriptions from 2016 to 2021 (index date) were selected and stratified by age group. Weekly (age-specific) data were used to forecast the prescription incidence for the pandemic period based on pre-pandemic data and to explore the relationship between weekly reported age-specific COVID-19 incidences and type 1 diabetes incidence and rate ratios of observed vs. predicted diabetes incidence respectively., Results: During the pre-pandemic period, there was a stable higher insulin prescription incidence during the winter period and a lower insulin prescription incidence during summer. During the pandemic period, there was less seasonal variation in incidence related to the finding that the observed incidence during summer in 2002 and 2021 was 44 % and 65 %, higher, respectively, than the expected incidence based on pre-pandemic year. We did not find any cross-correlations between the COVID-19 incidence and the type 1 diabetes incidence for any age group. Likewise, there were no cross-correlations between the COVID-19 incidence and the incidence rate ratios of observed incidences to predicted incidences., Conclusions/interpretation: During the COVID-19 pandemic, there was less seasonal variation in the incidence of type 1 diabetes (defined by new insulin prescriptions), with higher observed than expected incidences during summer. We found no evidence that the increase in type 1 diabetes incidence during the COVID-19 pandemic relates to direct effects of COVID-19 pandemic., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19-74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2-3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4-5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years., (© 2022. The Author(s).)

Aims: Treatment effects from the large cardiovascular outcome trials (CVOTs) of new antidiabetic drugs are almost exclusively communicated as hazard ratios, although reporting guidelines recommend to report treatment effects also on an absolute scale, e.g. as numbers needed to treat (NNT). We aimed to analyse NNTs in CVOTs comparing dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, or sodium-glucose cotransporter-2 (SGLT2) inhibitors to placebo., Methods: We digitalized individual time-to-event information for the primary outcome and all-cause mortality from 19 CVOTs that compared DPP-4 inhibitors, GLP-1 receptor agonists, or SGLT2 inhibitors to placebo. We estimated Weibull models for each trial and outcome and derived monthly NNTs. NNTs were summarized across all trials and within drug classes by random effects meta-analysis methods., Results: Treatment effects in the CVOTs appear smaller if they are reported as NNTs: Overall, 100 (95%-CI: 60, 303) patients have to be treated for 29 months (the median follow-up time across all trials) to avoid a single event of the primary outcome, and 128 (95%-CI: 85, 265) patients have to be treated for 39 months to avoid a single death. NNT time courses are very similar for GLP-1 receptor agonists and SGLT2 inhibitors, whereas treatment effects with DPP-4 inhibitors are smaller., Conclusions: We found that the respective treatment effects look less impressive when communicated on an absolute scale, as numbers needed to treat. For a valid overall picture of the benefit of new antidiabetic drugs, trial authors should also report treatment effects on an absolute scale., (© 2022. The Author(s).)

Aims: Hemoglobin A1c (HbA1c) has been repeatedly questioned as a valid surrogate marker, especially for patient-relevant outcomes. The aim of this study was to validate the HbA1c value as a surrogate for all-cause mortality in people with type 2 diabetes., Methods: The effect estimates for HbA1c lowering after treatment as well as reductions in all-cause mortality of randomized trials were extracted from a systematic review and updated. For the measurement of actual surrogacy, weighted linear regression models with a random intercept for the study effect were used with the all-cause mortality estimate (risk difference and log relative risk) as the outcome and the estimate for HbA1c difference as the covariate. Surrogacy was assessed according to the criteria of Daniels and Hughes., Results: A total of 346 HbA1c-mortality-pairs from 205 single randomized trials were included in the analysis. Regarding the risk difference of all-cause mortality, there was no evidence for surrogacy of the HbA1c value. For the log relative risk, a small positive association between HbA1c and the all-cause mortality estimate (slope 0.129 [95% confidence interval -0.043; 0.302]) was observed. However, there was no sign of valid surrogacy., Conclusions: Based on the results of more than 200 randomized trials, HbA1c is not a valid surrogate marker for all-cause mortality in people with type 2 diabetes., (© 2022. The Author(s).)

Background: The World Health Organization recommends 150 minutes of moderate to vigorous physical activity (PA), which translates to approximately 7000 to 10,000 steps per day for adults. In Germany, less than half of the population in this age range meets this recommendation, highlighting the need for population-based intervention approaches for promoting daily PA., Objective: The complex community-based PA intervention "10,000 Steps Ghent," which was originally developed in Belgium and was shown to be effective for PA promotion, has been adapted for implementation and evaluation in 2 German cities. The original Belgian study is currently being replicated, and we aim to examine the effectiveness of the adapted intervention among adults living in intervention city districts in Duesseldorf when compared with those living in control city districts in Wuppertal, over the course of 1 year., Methods: A controlled intervention trial examining the effects of an intervention addressing multiple levels (eg, individual level: website; organizational level: PA promotion in companies; community level: media campaigns and environmental changes) is being conducted. PA and various secondary outcomes will be assessed in 2 random samples of adults aged 25 to 75 years (n=399 in each city) at baseline and after 1 year., Results: Funding for this study was obtained in March 2020. Recruitment for this study and baseline data collection were conducted from May 2021 to March 2022 (as of March 2022, 626 participants were enrolled in the study). The intervention will be implemented in Duesseldorf for 1 year from April 2022 onward, and follow-up assessments will be conducted, starting in May 2023 (until September 2023). Data analysis will be performed in fall 2023, and the results will be published in spring 2024., Conclusions: To our knowledge, this is the first research project (currently underway in Germany) that is aimed at replicating the effects of a complex intervention for PA promotion that was previously shown to be effective in another European country., Trial Registration: German Clinical Trials Register DRKS00024873; https://tinyurl.com/4c9e8azh., International Registered Report Identifier (irrid): DERR1-10.2196/39175., (©Paula M Matos Fialho, Liane Günther, Elena Schmitz, Jannis Trümmler, Sorina Willemsen, Markus Vomhof, Andrea Icks, Alexander Lang, Oliver Kuss, Simone Weyers, Claudia R Pischke. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 21.09.2022.)

Objective: The aim of this study was to identify the occupational risk for a SARS-CoV-2 infection in a nationwide sample of German workers during the first wave of the COVID-19 pandemic (1 February-31 August 2020)., Methods: We used the data of 108 960 workers who participated in a COVID follow-up survey of the German National Cohort (NAKO). Occupational characteristics were derived from the German Classification of Occupations 2010 (Klassifikation der Berufe 2010). PCR-confirmed SARS-CoV-2 infections were assessed from self-reports. Incidence rates (IR) and incidence rate ratios (IRR) were estimated using robust Poisson regression, adjusted for person-time at risk, age, sex, migration background, study center, working hours, and employment relationship., Results: The IR was 3.7 infections per 1000 workers [95% confidence interval (CI) 3.3-4.1]. IR differed by occupational sector, with the highest rates observed in personal (IR 4.8, 95% CI 4.0-5.6) and business administration (IR 3.4, 95% CI 2.8-3.9) services and the lowest rates in occupations related to the production of goods (IR 2.0, 95% CI 1.5-2.6). Infections were more frequent among essential workers compared with workers in non-essential occupations (IRR 1.95, 95% CI 1.59-2.40) and among highly skilled compared with skilled professions (IRR 1.36, 95% CI 1.07-1.72)., Conclusions: The results emphasize higher infection risks in essential occupations and personal-related services, especially in the healthcare sector. Additionally, we found evidence that infections were more common in higher occupational status positions at the beginning of the pandemic.

Aims: To describe dispensation patterns of glucose-lowering drugs in newly diagnosed type 2 diabetes in Germany., Materials and Methods: Based on claims data from four statutory health insurances (German Pharmacoepidemiological Research Database,>25 million insurants), all individuals with newly diagnosed type 2 diabetes were identified. Eligible patients had a first diagnosis for type 2 diabetes between January 2012 and December 2016. We analyzed the dispensation patterns of first-line glucose-lowering therapies initiated in the year after diabetes diagnosis and patterns of second-line therapies dispensed one year after first-line treatment., Results: A total of 356,647 individuals with newly diagnosed type 2 diabetes were included (average age [SD]: 63.5 [13.4] years; 49.3% males). Of the 31.6% of individuals who were pharmacologically treated in the year after diagnosis, metformin monotherapy was most frequently dispensed (73.1%), followed by dual therapy of metformin and dipeptidyl peptidase-4 inhibitors (DPP-4is) (6.4%), and monotherapy with DPP-4is (2.9%). From 2012 through 2016, sulfonylurea dispensations were reduced by more than 50%. Dispensations for combination therapies with DPP-4is increased up to 10.6%. Glucagon-like peptide-1 receptor agonists and sodium-glucose co-transporter-2 inhibitors contributed to 2% of all treatments. After a median of 5 months, 20.0% of individuals on pharmacological therapy initiated second-line glucose-lowering treatment., Conclusions: Data from German statutory health insurances (2012 to 2016) showed that most individuals with newly diagnosed type 2 diabetes were dispensed metformin monotherapy in line with diabetes care guidelines. A substantial decrease in the use of sulfonylureas was observed after the introduction of DPP-4i and GLP-1 receptor agonists., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Aim: There is little evidence of the impact of diabetes risk scores on individual diabetes risk factors, motivation for behaviour changes and mental health. The aim of this study was to investigate the effect of applying a noninvasive diabetes risk score in primary care as component of routine health checks on physical activity and secondary outcomes., Methods: Cluster randomised trial, in which primary care physicians (PCPs), randomised (1:1) by minimisation, enrolled participants with statutory health insurance without known diabetes, ≥ 35 years of age with a body mass index ≥ 27.0 kg/m 2 . The German Diabetes Risk Score was applied as add-on to the standard routine health check, conducted in the controls. Primary outcome was the difference in participants' physical activity (International Physical Activity Questionnaire) after 12 months. Secondary outcomes included body mass index, perceived health, anxiety, depression, and motivation for lifestyle change. Analysis was by intention-to-treat principle using mixed models., Results: 36 PCPs were randomised; remaining 30 PCPs (intervention: n = 16; control: n = 14) recruited 315 participants (intervention: n = 153; controls: n = 162). A slight increase in physical activity was observed in the intervention group with an adjusted mean change of 388 (95% confidence interval: - 235; 1011) metabolic equivalents minutes per week. There were no relevant changes in secondary outcomes., Conclusions: The application of a noninvasive diabetes risk score alone is not effective in promoting physical activity in primary care., Clinical Trial Registration: ClinicalTrials.gov (NCT03234322, registration date: July 31, 2017)., (© 2022. The Author(s).)

Background and Aims: It is unclear whether socio-economic status (SES) is associated with glycaemic control in people with recently diagnosed diabetes. The aim was to investigate whether SES is related to haemoglobin A1c (HbA1c) during the first year after diagnosis in people with type 1 and type 2 diabetes and if metabolic, quality of care or mental factors may explain the association., Methods: In the German Diabetes Study, people with type 1 (n = 274, median age 36 [25th; 75th percentile: 28; 48] years) and type 2 diabetes (n = 424, 54 [47; 60] years) underwent detailed metabolic characterisation within the first year after diagnosis. SES was documented using a standardised questionnaire. Associations between SES and HbA1c were assessed using multivariable linear regression and restricted cubic spline regression analyses. Additional covariables were patient characteristics, laboratory measurements, health behaviour, quality of care and depression variables. Models were separately fitted for diabetes type, SES and its dimensions (income, education, occupation)., Results: Higher SES score was associated with lower HbA1c (-0.7 mmol/mol per unit increase in SES, 95% CI: -1.1; -0.2 mmol/mol [-0.1%, 95% CI: -0.1; 0.0%]) in people with type 1 diabetes. Included covariates did not attenuate this association. In people with type 2 diabetes, effect estimates were close to zero indicating no relevant difference., Conclusion: Socio-economic inequalities in HbA1c already exist during the first year after diagnosis in people with type 1 diabetes. The absence of association between glycaemic control and SES in type 2 diabetes could be due to the lower complexity of diabetes therapy compared to type 1 diabetes., (© 2022 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Aims/hypothesis: The aim of this work was to investigate diabetes incidence after infection with coronavirus disease-2019 (Covid-19). Individuals with acute upper respiratory tract infections (AURI), which are frequently caused by viruses, were selected as a non-exposed control group., Methods: We performed a retrospective cohort analysis of the Disease Analyzer, which comprises a representative panel of 1171 physicians' practices throughout Germany (March 2020 to January 2021: 8.8 million patients). Newly diagnosed diabetes was defined based on ICD-10 codes (type 2 diabetes: E11; other forms of diabetes: E12-E14) during follow-up until July 2021 (median for Covid-19, 119 days; median for AURI 161 days). Propensity score matching (1:1) for sex, age, health insurance, index month for Covid-19/AURI and comorbidity (obesity, hypertension, hyperlipidaemia, myocardial infarction, stroke) was performed. Individuals using corticosteroids within 30 days after the index dates were excluded. Poisson regression models were fitted to obtain incidence rate ratios (IRRs) for diabetes., Results: There were 35,865 individuals with documented Covid-19 in the study period. After propensity score matching, demographic and clinical characteristics were similar in 35,865 AURI controls (mean age 43 years; 46% female). Individuals with Covid-19 showed an increased type 2 diabetes incidence compared with AURI (15.8 vs 12.3 per 1000 person-years). Using marginal models to account for correlation of observations within matched pairs, an IRR for type 2 diabetes of 1.28 (95% CI 1.05, 1.57) was estimated. The IRR was not increased for other forms of diabetes., Conclusions/interpretation: Covid-19 confers an increased risk for type 2 diabetes. If confirmed, these results support the active monitoring of glucose dysregulation after recovery from mild forms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection., (© 2022. The Author(s).)

Objective: Continuous subcutaneous insulin infusion (CSII) in youths with type 1 diabetes (T1D) is often associated with lower HbA1c, lower total daily insulin dose (TDD), and lower body mass index (BMI) compared with multiple daily injections (MDI). Individual responses to CSII are diverse. The aim was to identify unique three-variate patterns of HbA1c, BMI standard deviation score (SDS), and TDD after switching to CSII., Methods: Five thousand one hundred and thirty-three youths (≤20 years; 48% boys; median age at pump start 12.5 years) with T1D duration ≥3 years at CSII initiation were selected from the multicenter DPV registry. We applied group-based multitrajectory modeling to identify groups of individuals following similar trajectories. Measurements were aggregated quarterly during a 3-year follow-up period. Trajectory variables were changes of HbA1c, BMI-SDS, and TDD from baseline (delta = quarterly aggregated values at each time point [i] minus the respective baseline value)., Results: Four groups of diverging Delta-HbA1c, Delta-BMI-SDS, and Delta-TDD patterns were identified. All showed improvements in HbA1c during the first 3 months. Group 1 (12%) was characterized by modest HbA1c increase thereafter, TDD reduction, and stable BMI-SDS. In Group 2 (39%), increasing HbA1c, decreasing BMI-SDS, and stable TDD were found. By contrast, sustainably improved HbA1c, increasing BMI-SDS, and stable TDD were observed in Group 3 (32%). Group 4 (17%) was characterized by increasing levels for HbA1c, BMI-SDS, and TDD. Between-group differences in baseline HbA1c, BMI-SDS, TDD as well as in sex ratio, age at diabetes onset and at pump start were observed., Conclusions: Definite trajectories of glycemic control, BMI, and TDD over 3 years after CSII initiation were identified in youths with T1D allowing a more personalized treatment recommendation., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

The German National Cohort (NAKO) is an ongoing, prospective multicenter cohort study, which started recruitment in 2014 and includes more than 205,000 women and men aged 19-74 years. The study data will be available to the global research community for analyses. Although the ultimate decision about the analytic methods will be made by the respective investigator, in this paper we provide the basis for a harmonized approach to the statistical analyses in the NAKO. We discuss specific aspects of the study (e.g., data collection, weighting to account for the sampling design), but also give general recommendations which may apply to other large cohort studies as well., (© 2022. The Author(s).)

Background: Numerous studies have reported an increase in mental disorders during the COVID-19 pandemic, but the exact reasons for this development are not well understood. In this study we investigate whether pandemic-related occupational and financial changes (e.g., reduced working hours, working from home, financial losses) were associated with increased symptoms of depression and anxiety compared with the situation before the pandemic., Methods: We analyzed data from the German National Cohort (NAKO) Study. Between May and November 2020, 161 849 study participants answered questions on their mental state and social circumstances. Their responses were compared with data from the baseline survey before the pandemic (2014-2019). Linear fixed-effects models were used to determine whether individual changes in the severity of symptoms of depression (PHQ-9) or anxiety (GAD-7) were associated with occupational/ financial changes (controlling for various covariates)., Results: The prevalence of moderate or severe symptoms of depression and anxiety increased by 2.4% and 1.5%, respectively, during the COVID-19 pandemic compared with the preceding years. The mean severity of the symptoms rose slightly. A pronounced increase in symptoms was observed among those who became unemployed during the pandemic (+ 1.16 points on the depression scale, 95% confidence interval [0.91; 1.41], range 0-27). Increases were also seen for reduced working hours with no short-time allowance, increased working hours, working from home, insecurity regarding employment, and financial strain. The deterioration in mental health was largely statistically explained by the occupational and financial changes investigated in the model., Conclusion: Depressive symptoms and anxiety disorders increased slightly in the study population during the first year of the COVID-19 pandemic. Occupational and financial difficulties were an essential contributory factor. These strains should be taken into account both in the care of individual patients and in the planning of targeted prevention measures.

Background: The findings of observational studies can be distorted by a number of factors. So-called confounders are well known, but distortion by collider bias (CB) has received little attention in medical research to date. The goal of this article is to present the principle of CB, and measures that can be taken to avoid it, by way of a few illustrative examples., Methods: The findings of a selective review of the literature on CB are explained with illustrative examples., Results: The simplest case of a collider variable is one that is caused by at least two other variables. An example of CB is the observation that, among persons with diabetes, obesity is associated with lower mortality, even though it is associated with higher mortality in the general population. The false protective association between obesity and mortality arises from the restriction of the study population to persons with diabetes., Conclusion: CB is a distortion that arises through restriction on or stratification by a collider variable, or through statistical adjustment for a collider variable in a regression model. CB can arise in many ways. The graphic representation of causal structures helps to identify potential sources of CB. It is important to distinguish confounders from colliders, as methods that serve to correct for confounding can themselves cause bias when applied to colliders. There is no generally applicable method for correcting CB.

Introduction: Diabetic sensorimotor polyneuropathy (DSPN) affects approximately 30% of people with diabetes, while around half of cases are symptomatic. Currently, there are only few pathogenetically oriented pharmacotherapies for DSPN, one of which is benfotiamine, a prodrug of thiamine with a high bioavailability and favourable safety profile. While benfotiamine has shown positive effects in preclinical and short-term clinical studies, no long-term clinical trials are available to demonstrate disease-modifying effects on DSPN using a comprehensive set of disease-related endpoints., Methods and Analysis: The benfotiamine on morphometric, neurophysiological and clinical measures in patients with type 2 diabetes trial is a randomised double-blind, placebo-controlled parallel group monocentric phase II clinical trial to assess the effects of treatment with benfotiamine compared with placebo in participants with type 2 diabetes and mild to moderate symptomatic DSPN. Sixty participants will be 1:1 randomised to treatment with benfotiamine 300 mg or placebo two times a day over 12 months. The primary endpoint will be the change in corneal nerve fibre length assessed by corneal confocal microscopy (CCM) after 12 months of benfotiamine treatment compared with placebo. Secondary endpoints will include other CCM measures, skin biopsy and function indices, variables from somatic and autonomic nerve function tests, clinical examination and questionnaires, general health, health-related quality of life, cost, safety and blood tests., Ethics and Dissemination: The trial was approved by the competent authority and the local independent ethics committee. Trial results will be published in peer-reviewed journals, conference abstracts, and via online and print media., Trial Registration Number: DRKS00014832., Competing Interests: Competing interests: DZ and GJB received honoraria from Wörwag Pharma for speaking and consulting activities. CH received a research grant from Sanofi-Aventis. CR and J-CW are employees of Wörwag Pharma., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Staphylococcus aureus bloodstream infection (SAB) is a common, life-threatening infection. The impact of immunosuppressive agents on the outcome of patients with SAB is incompletely understood., Methods: Data from 2 large prospective, international, multicenter cohort studies (Invasive Staphylococcus aureus Infections Cohort [INSTINCT] and International Staphylococcus aureus Collaboration [ISAC]) between 2006 and 2015 were analyzed. Patients receiving immunosuppressive agents were identified and a 1:1 propensity score-matched analysis was performed to adjust for baseline characteristics of patients. Overall survival and time to SAB-related late complications (SAB relapse, infective endocarditis, osteomyelitis, or other deep-seated manifestations) were analyzed by Cox regression and competing risk analyses, respectively. This approach was then repeated for specific immunosuppressive agents (corticosteroid monotherapy and immunosuppressive agents other than steroids [IMOTS])., Results: Of 3188 analyzed patients, 309 were receiving immunosuppressive treatment according to our definitions and were matched to 309 nonimmunosuppressed patients. After propensity score matching, baseline characteristics were well balanced. In the Cox regression analysis, we observed no significant difference in survival between the 2 groups (death during follow-up: 105/309 [33.9%] immunosuppressed vs 94/309 [30.4%] nonimmunosuppressed; hazard ratio [HR], 1.20 [95% confidence interval {CI}, .84-1.71]). Competing risk analysis showed a cause-specific HR of 1.81 (95% CI, .85-3.87) for SAB-related late complications in patients receiving immunosuppressive agents. The cause-specific HR was higher in patients taking IMOTS (3.69 [95% CI, 1.41-9.68])., Conclusions: Immunosuppressive agents were not associated with an overall higher mortality. The risk for SAB-related late complications in patients receiving specific immunosuppressive agents such as IMOTS warrants further investigations., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)