An Empirical Approach to Derive Water T1 from Multiparametric MR Images Using an Automated Pipeline and Comparison With Liver Stiffness

BACKGROUND

Water T1 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 T1 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

T1 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 T1 based on automatic segmentation was compared to the T1 values based on manual segmentation. The association of T1 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 T1 values from automatic vs. manual segmentation. Pearson's r correlation coefficients for T1 with hepatic lipids and liver stiffness were determined. A P-value of 0.05 was considered statistically significant.

RESULTS

MOLLI T1 values after correction were found in better agreement with the 1 H-MRS-derived water T1 (ICC = 0.60 [0.37; 0.76]) in comparison with the uncorrected T1 values (ICC = 0.18 [-0.09; 0.44]). Automatic quantification yielded similar liver T1 values (ICC = 0.9995 [0.9991; 0.9997]) as with manual segmentation. A significant correlation of T1 with liver stiffness (r = 0.43 [0.11; 0.67]) was found. A marked and significant reduction in the correlation strength of T1 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 T1 in vivo.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1.

Mortality of type 2 diabetes in Germany: additional insights from Gompertz models

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.

Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials

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.

Analysis of type 2 diabetes heterogeneity with a tree-like representation: insights from the prospective German Diabetes Study and the LURIC cohort

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 (pdim1<0·0001, pdim2=0·00097) across the tree. Individuals in the region with the lowest insulin sensitivity had the highest hepatic lipid content (n=205, pdim1<0·0001, pdim2=0·037), pro-inflammatory biomarkers (IL-6: n=348, pdim1<0·0001, pdim2=0·013; IL-18: n=350, pdim1<0·0001, pdim2=0·38), and elevated cardiovascular risk (nevents=143, pdim1=0·14, pdim2<0·00081), whereas individuals positioned in the branch with the lowest insulin secretion were more prone to require insulin therapy (nevents=85, pdim1=0·032, pdim2=0·12) and had the highest risk of diabetic sensorimotor polyneuropathy (nevents=184, pdim1=0·012, pdim2=0·044) and cardiac autonomic neuropathy (nevents=118, pdim1=0·0094, pdim2=0·06). In the LURIC cohort, all-cause mortality was highest in the tree branch showing insulin resistance (nevents=488, pdim1=0·12, pdim2=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.

Absolute treatment effects of novel antidiabetic drugs on a composite renal outcome: meta-analysis of digitalized individual patient data

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 m2. 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.

Synergism between coexisting eye diseases and sex in increasing the prevalence of the dry eye syndrome

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.

Mediation Analysis in Medical Research

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.

Efficacy of automated insulin delivery (AID) systems in type 1 diabetes: protocol of a systematic review and network meta-analysis of outpatient randomised controlled trials

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.

The mediating role of obesity on the prospective association between urinary sucrose and diabetes incidence in a sub-cohort of the EPIC-Norfolk

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.

How amenable is type 2 diabetes treatment for precision diabetology? A meta-regression of glycaemic control data from 174 randomised trials

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 HbA1c 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 HbA1c 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 .

Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis

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), HbA1c (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 m2 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 1×109/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).

How hazardous are hazard ratios? An empirical investigation of individual patient data from 27 large randomized clinical trials

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.

Diabetes incidence before and after COVID-19 vaccination - Results from the German Disease Analyzer database

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.

Association of a lifestyle score with cardiometabolic markers among individuals with diabetes: a cross-sectional study

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.

Spatio-Temporal Trends in the Incidence of Type 2 Diabetes in Germany-Analysis of the Claims Data of 63 Million Persons With Statutory Health Insurance From 2014 to 2019

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. Ageand sex-adjusted trends were calculated for 401 administrative districts using a Bayesian spatiotemporal 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.

HbA1c trajectories over 3 years in people with type 2 diabetes starting second-line glucose-lowering therapy: The prospective global DISCOVER study

AIM

To identify distinct glycated haemoglobin (HbA_1c ) 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 HbA_1c trajectories.

RESULTS

After exclusions, 9295 participants were assessed. Four distinct HbA_1c trajectories were identified. Mean HbA_1c 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 likely 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. This article is protected by copyright. All rights reserved.

Serum neurofilament light chain: a novel biomarker for early diabetic sensorimotor polyneuropathy

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.

Performance of several types of beta-binomial models in comparison to standard approaches for meta-analyses with very few studies

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.

Meta-analysed numbers needed to treat of novel antidiabetic drugs for cardiovascular outcomes

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.

Type 1 diabetes incidence in children and adolescents during the COVID-19 pandemic in Germany

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.

Absolute treatment effects for the primary outcome and all-cause mortality in the cardiovascular outcome trials in type 2 diabetes: a meta-analysis of individual patient data

Background and purpose

Treatment effects from the large cardiovascular outcome trials (CVOTs) in diabetes 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 analyze NNT in CVOTs of novel oral antidiabetic drugs 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 and results

We extracted 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. Treatment effects in the CVOTs appear smaller if they are reported as NNTs: Overall, 60 (95%-CI: 40–124) 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 101 (95%-CI: 69–191) patients have to be treated for 39 months to avoid a single death.

Conclusion

We found that the respective treatment effects of novel oral antidiabetic drugs look less impressive when communicated on an absolute scale, as numbers needed to treat. For a valid overall picture of the benefit of these drugs, trial authors should thus also report treatment effects on an absolute scale.

Funding Acknowledgement

Type of funding sources: None.

Absolute treatment effects of novel oral antidiabetic drugs on cardiovascular mortality and hospitalization for heart failure: a meta-analysis of digitalized individual patient outcomes

Background and purpose

Absolute treatment effects of novel oral antidiabetic drugs for cardiovascular outcomes have thus far not been comprehensively evaluated. We thus aimed to perform a meta-analysis of digitalized individual patient data.

Methods and results

Individual patient outcomes 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 against placebo with time-to-event information for cardiovascular mortality (CM) and/or hospitalization for heart failure (HHF) endpoints were digitalized from Kaplan-Meier plots; Weibull regression models with random-effects meta-analysis were used to estimate numbers-needed-to-treat (NNT) and Meta-NNT with 95% confidence intervals (CI). Sixteen CVOTs reported time-to-event information (14 in primary diabetes, two in primary heart failure populations). Thirteen studies including 96,860 patients were meta-analyzed 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-analyzed 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.

Conclusion

We found modest treatment benefits of GLP-1 receptor agonists and SGLT2 inhibitors for CM and HHF in primary T2DM populations. In primary heart failure populations, however, SGLT2 inhibitor benefits were substantial and comparable to established heart failure medication.

Funding Acknowledgement

Type of funding sources: None.

Absolute treatment effects for the primary outcome and all-cause mortality in the cardiovascular outcome trials of new antidiabetic drugs: a meta-analysis of digitalized individual patient data

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.

Is HbA1c a valid surrogate for mortality in type 2 diabetes? Evidence from a meta-analysis of randomized trials

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.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany

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.

Impact of applying a diabetes risk score in primary care on change in physical activity: a pragmatic cluster randomised trial

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/m². 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).

Socio-economic inequalities in glycaemic control in recently diagnosed adults with type 1 and type 2 diabetes

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.

Incidence of newly diagnosed diabetes after Covid-19

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.

Three-variate trajectories of metabolic control, body mass index, and insulin dose: Heterogeneous response to initiation of pump therapy in youth with type 1 diabetes

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.

Collider Bias in Observational Studies: Consequences for Medical Research–Part 30 of a Series on Evaluation of Scientific Publications

BACKGROUND

The findings of observational studies can be distorted by a number of factors. Socalled 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.

BOND study: a randomised double-blind, placebo-controlled trial over 12 months to assess the effects of benfotiamine on morphometric, neurophysiological and clinical measures in patients with type 2 diabetes with symptomatic polyneuropathy

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.

Dispensation Patterns of Glucose-Lowering Drugs in Newly Diagnosed Type 2 Diabetes: Routine Data Analysis of Insurance Claims in Germany

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.

Impact of Left Atrial Appendage Amputation on Left Atrial Morphology and Rhythm after Off-Pump CABG

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.

Impact of Immunosuppressive Agents on Clinical Manifestations and Outcome of Staphylococcus aureus Bloodstream Infection: A Propensity Score-Matched Analysis in 2 Large, Prospectively Evaluated Cohorts

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.

Study protocol for a mixed methods exploratory investigation of aftercare services for gestational diabetes in women to develop a new patient-centred model in Germany: the GestDiNa_basic study

INTRODUCTION

Women with gestational diabetes mellitus (GDM) have a higher risk of developing type 2 diabetes mellitus compared with women who never had GDM. Consequently, the question of structured aftercare for GDM has emerged. In all probability, many women do not receive care according to the guidelines. In particular, the process and interaction between obstetrical, diabetic, gynaecological, paediatric and general practitioner care lacks clear definitions. Thus, our first goal is to analyse the current aftercare situation for women with GDM in Germany, for example, the participation rate in aftercare diabetes screening, as well as reasons and attitudes stated by healthcare providers to offer these services and by patients to participate (or not). Second, we want to develop an appropriate, effective and patient-centred care model.

METHODS AND ANALYSIS

This is a population-based mixed methods study using both quantitative and qualitative research approaches. In various working packages, we evaluate data of the GestDiab register, of the Association of Statutory Health Insurance Physicians of North Rhine and the participating insurance companies (AOK Rheinland/Hamburg, BARMER, DAK Gesundheit, IKK classic, pronova BKK). In addition, quantitative (postal surveys) and qualitative (interviews) surveys will be conducted with randomly selected healthcare providers (diabetologists, gynaecologists, paediatricians and midwives) and affected women, to be subsequently analysed. All results will then be jointly examined and evaluated.

ETHICS AND DISSEMINATION

The study was approved by the ethics committee of the Faculty of Medicine, Heinrich-Heine-University Düsseldorf (Ethics Committee No.: 2019-738). Participants of the postal surveys and interviews will be informed in detail about the study and the use of data as well as the underlying data protection regulations before voluntarily participating. The study results will be disseminated through peer-reviewed journals, conferences and public information.

TRIAL REGISTRATION NUMBER

DRKS00020283.

LUPUS-BEST-treat-to-target in systemic lupus erythematosus: study protocol for a three-armed cluster-randomised trial

INTRODUCTION

As chronic systemic autoimmune disease, which can affect every organ, SLE is creating significant burden and increased mortality. Despite better outcomes over the past decades by optimising standard of care, new interventions are needed for further improvements. Changing strategy to 'treat-to-target' (T2T) may be a promising concept proven successful in other chronic diseases.

METHODS AND ANALYSIS

In this cluster-randomised trial, SLE centres will be assigned 1:1:1 to standard of care (SoC), remission (no clinical disease activity+prednisolone ≤5 mg/day+Physician Global Assessment (PGA 0-3) <0.5±immunomodulatory treatment) or and Lupus Low Disease Activity State (LLDAS, low disease activity+prednisolone ≤7.5 mg/day+PGA ≤1+no new disease activity). Per arm, 424 patients will be included. Intervention centres receive a standardised training on T2T and shared decision-making (SDM). In intervention centres, patients not in target enter a phase of tight control with six weekly visits and treatment adjustments (at least four visits) or until the target is reached and maintained. Patients in target are reassessed every 12 weeks. In case of flare, they can enter tight control based on SDM. In the SoC arm, patients receive their usual three to six monthly controls and treatment adjustments according to the physician's discretion. Study duration is 120 weeks using change in damage and health-related quality of life (HRQoL) as major outcomes. The primary endpoint will be damage accrual at 120 weeks as measured by the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index and will by analysed by a mixed model.

CONCLUSIONS

This is the first trial to assess if the implementation of a T2T concept in clinical care minimises damage accrual and improves HRQoL in patients with SLE. Comparison of remission and LLDAS will help to identify the target with the best benefit-risk ratio concerning attainability, adverse events and damage. The emphasis on SDM will strengthen patient autonomy and will improve both their satisfaction and medical condition.

Risk phenotypes of diabetes and association with COVID-19 severity and death: a living systematic review and meta-analysis

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.

Impact of mixed meal tolerance test composition on measures of beta-cell function in type 2 diabetes

Background

Application of mixed meal tolerance tests (MMTT) to measure beta-cell function in long-term studies is limited by modification of the commercial products occurring over time. This study assessed the intra-individual reliability of MMTTs and compared the effects of liquid meals differing in macronutrient composition on the estimation of beta-cell function in type 2 diabetes (T2DM).

Methods

To test the reliability of MMTTs, 10 people with T2DM (age 58 ± 11 years, body mass index 30.0 ± 4.9 kg/m²) received Boost®high Protein 20 g protein three times. For comparing different meals, another 10 persons with T2DM (58 ± 5 years, 31.9 ± 5.3 kg/m²) ingested either Boost®high Protein 20 g protein or the isocaloric Boost®high Protein 15 g protein containing 35% less protein and 18% more carbohydrates. C-peptide, insulin and glucose release were assessed from the incremental area under the concentration time curve (iAUC) and the intra- and inter-individual variation of these parameters from the coefficients of variations (CV).

Results

Repetitive ingestion of one meal revealed intra-individual CVs for the iAUCs of C-peptide, insulin and glucose, which were at least 3-times lower than the inter-individual variation of these parameters (18.2%, 19.7% and 18.9% vs. 74.2%, 70.5% and 207.7%) indicating a good reliability. Ingestion of two different meals resulted in comparable intra-individual CVs of the iAUCs of C-peptide and insulin (16.9%, 20.5%).

Conclusion

MMTTs provide reliable estimation of beta-cell function in people with T2DM. Furthermore, moderate differences in the protein and carbohydrate contents in a standardized liquid meal do not result in relevant changes of C-peptide and insulin responses.

Trial registration: Clinicaltrials.gov, Identifier number: NCT01055093. Registered 22 January 2010 – Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/study/NCT01055093

Reversion from prediabetes to normoglycaemia after weight change in older persons: The KORA F4/FF4 study

BACKGROUND AND AIMS

In a non-interventional study of older persons, we assessed the impact of changes in BMI and waist circumference (WC) on reversion from glucose- and HbA1c-defined prediabetes to normoglycaemia (in short: reversion) and on persistence of normoglycaemia. Moreover, we studied whether reversion reduced cardiovascular risk.

METHODS AND RESULTS

From the population-based KORA S4/F4/FF4 cohort study conducted in Southern Germany, we utilized data from the second and third visit to the study center (median follow-up 6.5 years). We used two overlapping data sets, one with 563 persons with HbA1c<6.5% (mean age 69 years, 51.5% men), one with 510 persons with glucose-based prediabetes or normal glucose tolerance. We calculated proportions of reversion, and estimated adjusted relative risks for the association between initial BMI/WC and change of BMI/WC, respectively, and reversion (and persistence of normoglycaemia, respectively). We estimated 10-year cardiovascular risks using the Framingham 2008 score. Overall, 27.3% of persons with HbA1c-defined prediabetes and 9.2% of persons with glucose-based prediabetes returned to normoglycaemia during follow-up. Lower initial BMI/WC and reduction of BMI/WC were associated with larger probabilities of returning to normoglycaemia (e.g., for HbA1c 5.7-6.4%, RR = 1.24 (95% CI: 1.09-1.41) per 1 kg/m² decline of BMI). Moreover, reduction of BMI/WC increased probabilities of maintaining normoglycaemia (e.g., for glucose-based prediabetes, RR = 1.09 (1.02-1.16) per 1 kg/m² decline of BMI). 10-year cardiovascular risk was 5.6 (1.7-9.6) percentage points lower after reversion from glucose-based prediabetes to normoglycaemia.

CONCLUSION

In older adults, even moderate weight reduction contributes to reversion from prediabetes to normoglycaemia and to maintaining normoglycaemia.

No inexplicable disagreements between real-world data-based nonrandomized controlled studies and randomized controlled trials were found

OBJECTIVES

We assessed disagreements between nonrandomized controlled studies based on real-world data (NRCS-RWDs) and randomized controlled trials (RCTs).

STUDY DESIGN AND SETTING

We systematically searched for studies that compared treatment effect estimates from NRCS-RWDs and RCTs on the same clinical question. We assessed the potential difference between NRCS-RWDs and RCTs related to internal and external validity. We calculated various meta-epidemiological measures to assess agreement. In case of disagreements, we tried to identify the probable causes of disagreements.

RESULTS

We included 12 studies comparing 15 treatment effect estimates of NRCS-RWDs and RCTs. There were many potential causes of disagreement. Ninety-five percent confidence intervals overlapped for 12 of 15 treatment effect estimates. Our analysis on predicted vs. observed overlap showed that there were no more disagreements than expected by chance. We observed only two substantial differences between the 15 treatment effect estimates. In both cases, we identified risk of bias in the NRCS-RWDs as the most probable cause of disagreement.

CONCLUSION

Our findings suggest that there are clinical questions where the difference in risk of bias between a well-conducted NRCS-RWD and an RCT is negligible. In our analysis, threats to external validity appeared to have no or only a weak impact on the disagreements of treatment effect estimates.

Associations of area deprivation and urban/rural traits with the incidence of type 1 diabetes: analysis at the municipality level in North Rhine-Westphalia, Germany

AIM

To analyse the associations of area deprivation and urban/rural traits with the incidence of type 1 diabetes in the German federal state of North Rhine-Westphalia.

METHODS

Data of incident type 1 diabetes cases in children and adolescents aged <20 years between 2007 and 2014 were extracted from a population-based diabetes register. Population data, indicators of area deprivation and urban/rural traits at the municipality level (396 entities) were obtained from official statistics. Area deprivation was assessed in five groups based on quintiles of an index of multiple deprivation and its seven deprivation domains. Poisson regression accounting for spatial dependence was applied to investigate associations of area deprivation and urban/rural traits with type 1 diabetes incidence.

RESULTS

Between 2007 and 2014, 6143 incident cases were reported (99% completeness); the crude incidence was 22.3 cases per 100 000 person-years. The incidence decreased with increasing employment and environmental deprivation (relative risk of the most vs. the least deprived municipalities: 0.905 [95% CI: 0.813, 1.007] and 0.839 [0.752, 0.937], respectively) but was not associated with the composite deprivation index. The incidence was higher in more peripheral, rural, smaller and less densely populated municipalities, and the strongest association was estimated for the location trait (relative risk of peripheral/very peripheral compared with very central location: 1.231 [1.044, 1.452]).

CONCLUSIONS

The results suggest that the type 1 diabetes risk is higher in more remote, more rural, less densely populated and less deprived areas. Urban/rural traits were stronger predictors of type 1 diabetes risk than area deprivation indicators.

Association between per capita sugar consumption and diabetes prevalence mediated by the body mass index: results of a global mediation analysis

Purpose

The aim of this study was to examine the mediation of body mass index (BMI) on the association between per capita sugar consumption and diabetes prevalence using country-related data.

Research design and methods

In this ecological study, based on 192 countries, data on per capita sugar consumption were obtained from the Food and Agriculture Organization of the United Nations (FAO), on BMI from the World Health Organization and on diabetes prevalence from the International Diabetes Federation. Data on demography and economic factors were obtained from the Central Intelligence Agency, the United Nations and the FAO. Multiple linear regression analysis was performed to investigate the association between per capita sugar consumption and diabetes prevalence, and mediation analysis to detect the mediated percentage of BMI on this association.

Results

Each increase of 100 kcal/day per capita sugar consumption was associated with a 1.62% higher diabetes prevalence [adjusted β-estimator (95% CI): 1.62 (0.71, 2.53)]. Mediation analysis using BMI as the mediator demonstrated an adjusted direct association of 0.55 (95% CI: − 0.22, 1.32) and an adjusted indirect association of 1.07 (95% CI: 0.54, 1.68). Accordingly, the BMI explained 66% (95% CI: 34%, 100%) of the association between per capita sugar consumption on diabetes prevalence.

Conclusions

These findings indicate that the association between dietary sugar intake and the occurrence of diabetes is mediated by BMI to a large proportion. However, it seems that other mechanisms may explain the association between sugar consumption and development of type 2 diabetes.

Electronic supplementary material

The online version of this article (10.1007/s00394-020-02401-2) contains supplementary material, which is available to authorized users.

Age at diagnosis of Type 2 diabetes in Germany: a nationwide analysis based on claims data from 69 million people

AIM

For many European countries, including Germany, no valid estimates are available on age at diagnosis of Type 2 diabetes. Thus, we aimed to estimate the age at diagnosis in Germany.

METHODS

Age at diagnosis of Type 2 diabetes in Germany was estimated based on Type 2 diabetes prevalence and incidence and the age distribution of the German population. Age- and sex-specific incidence and prevalence in 2014/2015, based on claims data from statutory health insurance (n= 69 000 000, ~85% of the German population), and the age pyramid for Germany in 2015 were used for the calculation. Age at Type 2 diabetes diagnosis was stratified by sex. CIs were estimated using bootstrap methods. In addition, the age range in which 50% of the population received a diagnosis of Type 2 diabetes was calculated (the interquartile range).

RESULTS

The mean ± sd age at Type 2 diabetes diagnosis in 2015 was 61.0 ± 13.4 years (95% CI 60.9-61.0) in men. Women were diagnosed ~2 years later than men (mean age 63.4 ± 14.9 years; 95% CI 63.4-63.5). The age range in which 50% of the population was diagnosed with diabetes was 53-72 years for men and 54-76 years for women.

CONCLUSIONS

The sex differences are mainly attributable to a higher incidence of Type 2 diabetes in men than women during middle age and the higher absolute number of women in the older ages. The early age at diabetes diagnosis compared to average life expectancy means that the risk of diabetes-related complications is increased.

A proportional risk model for time-to-event analysis in randomized controlled trials

Regression models for continuous, binary, nominal, and ordinal outcomes almost completely rely on parametric models, whereas time-to-event outcomes are mainly analyzed by Cox's Proportional Hazards model, an essentially non-parametric method. This is done despite a long list of disadvantages that have been reported for the hazard ratio, and also for the odds ratio, another effect measure sometimes used for time-to-event modelling. In this paper, we propose a parametric proportional risk model for time-to-event outcomes in a two-group situation. Modelling explicitly a risk instead of a hazard or an odds solves the current interpretational and technical problems of the latter two effect measures. The model further allows for computing absolute effect measures like risk differences or numbers needed to treat. As an additional benefit, results from the model can also be communicated on the original time scale, as an accelerated or a prolongated failure time thus facilitating interpretation for a non-technical audience. Parameter estimation by maximum likelihood, while properly accounting for censoring, is straightforward and can be implemented in each statistical package that allows coding and maximizing a univariate likelihood function. We illustrate the model with an example from a randomized controlled trial on efficacy of a new glucose-lowering drug for the treatment of type 2 diabetes mellitus and give the results of a small simulation study.