Association of plasma proteomics with mortality in individuals with and without type 2 diabetes: Results from two population-based KORA cohort studies.

BACKGROUND: Protein biomarkers may contribute to the identification of vulnerable subgroups for premature mortality. This study aimed to investigate the association of plasma proteins with all-cause and cause-specific mortality among individuals with and without baseline type 2 diabetes (T2D) and evaluate their impact on the prediction of all-cause mortality in two prospective Cooperative Health Research in the Region of Augsburg (KORA) studies. METHODS: The discovery cohort comprised 1545 participants (median follow-up 15.6 years; 244 with T2D: 116 total, 62 cardiovascular, 31 cancer-related and 23 other-cause deaths; 1301 without T2D: 321 total, 114 cardiovascular, 120 cancer-related and 87 other-cause deaths). The validation cohort comprised 1031 participants (median follow-up 6.9 years; 203 with T2D: 76 total, 45 cardiovascular, 19 cancer-related and 12 other-cause deaths; 828 without T2D: 169 total, 74 cardiovascular, 39 cancer-related and 56 other-cause deaths). We used Cox regression to examine associations of 233 plasma proteins with all-cause and cause-specific mortality and Lasso regression to construct prediction models for all-cause mortality stratifying by baseline T2D. C-index, category-free net reclassification index (cfNRI), and integrated discrimination improvement (IDI) were conducted to evaluate the predictive performance of built prediction models. RESULTS: Thirty-five and 62 proteins, with 29 overlapping, were positively associated with all-cause mortality in the group with and without T2D, respectively. Out of these, in the group with T2D, 35, eight, and 26 were positively associated with cardiovascular, cancer-related, and other-cause mortality, while in the group without T2D, 55, 41, and 47 were positively associated with respective cause-specific outcomes in the pooled analysis of both cohorts. Regulation of insulin-like growth factor (IGF) transport and uptake by IGF-binding proteins emerged as a unique pathway enriched for all-cause and cardiovascular mortality in individuals with T2D. The combined model containing the selected proteins (five and 12 proteins, with four overlapping, in the group with and without T2D, respectively) and clinical risk factors improved the prediction of all-cause mortality by C-index, cfNRI, and IDI. CONCLUSIONS: This study uncovered shared and unique mortality-related proteins in persons with and without T2D and emphasized the role of proteins in improving the prediction of mortality in different T2D subgroups.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study.

BACKGROUND: Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D. METHODS: The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI). RESULTS: We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465). CONCLUSIONS: This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

A parametric additive hazard model for time-to-event analysis.

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

Estimation of mortality rate ratios for chronic conditions with misclassification of disease status at death.

Estimation of mortality rates and mortality rate ratios (MRR) of diseased and non-diseased individuals is a core metric of disease impact used in chronic disease epidemiology. Estimation of mortality rates is often conducted through retrospective linkage of information from nationwide surveys such as the National Health Interview Survey (NHIS) and death registries. These surveys usually collect information on disease status during only one study visit. This infrequency leads to missing disease information (with right censored survival times) for deceased individuals who were disease-free at study participation, and a possibly biased estimation of the MRR because of possible undetected disease onset after study participation. This occurrence is called "misclassification of disease status at death (MicDaD)" and it is a potentially common source of bias in epidemiologic studies. In this study, we conducted a simulation analysis with a high and a low incidence setting to assess the extent of MicDaD-bias in the estimated mortality. For the simulated populations, MRR for diseased and non-diseased individuals with and without MicDaD were calculated and compared. Magnitude of MicDaD-bias depends on and is driven by the incidence of the chronic disease under consideration; our analysis revealed a noticeable shift towards underestimation for high incidences when MicDaD is present. Impact of MicDaD was smaller for lower incidence (but associated with greater uncertainty in the estimation of MRR in general). Further research can consider the amount of missing information and potential influencers such as duration and risk factors of the disease.

Projecting the economic burden of type 1 and type 2 diabetes mellitus in Germany from 2010 until 2040.

BACKGROUND: The aim is to estimate age- and sex-specific direct medical costs related to diagnosed type 1 and type 2 diabetes in Germany between 2010 and 2040. METHODS: Based on nationwide representative epidemiological routine data from 2010 from the statutory health insurance in Germany (almost 80% of the population's insurance) we projected age- and sex-specific healthcare expenses for type 1 and 2 diabetes considering future demographic, disease-specific and cost trends. We combine per capita healthcare cost data (obtained from aggregated claims data from an almost 7% random sample of all German people with statutory health insurance) together with the demographic structure of the German population (obtained from the Federal Statictical Office), diabetes prevalence, incidence and mortality. Direct per capita costs, total annual costs, cost ratios for people with versus without diabetes and attributable costs were estimated. The source code for running the analysis is publicly available in the open-access repository Zenodo. RESULTS: In 2010, total healthcare costs amounted to more than €1 billion for type 1 and €28 billion for type 2 diabetes. Depending on the scenario, total annual expenses were projected to rise remarkably until 2040 compared to 2010, by 1-281% for type 1 (€1 to €4 billion) and by 8-364% for type 2 diabetes (€30 to €131 billion). In a relatively probable scenario total costs amount to about €2 and €79 billion for type 1 and type 2 diabetes in 2040, respectively. Depending on annual cost growth (1% p.a. as realistic scenario vs. 5% p.a. as very extreme setting), we estimated annual per capita costs of €6,581 to €12,057 for type 1 and €5,245 to €8,999 for type 2 diabetes in 2040. CONCLUSIONS: Diabetes imposes a large economic burden on Germany which is projected to increase substantially until 2040. Temporal trends in the incidence and cost growth are main drivers of this increase. This highlight the need for urgent action to prepare for the potential development and mitigate its consequences.

Safety of magnetic resonance imaging in patients with cardiac implantable electronic devices and abandoned or epicardial leads: a systematic review and meta-analysis.

AIMS: Persistent reluctance to perform magnetic resonance imaging (MRI) in patients with abandoned and/or epicardial leads of cardiac implantable electronic devices is related to in vitro studies reporting tip heating. While there is a plethora of data on the safety of MRI in conditional and non-conditional implantable devices, there is a clear lack of safety data in patients with abandoned and/or epicardial leads. METHODS AND RESULTS: Relevant literature was identified in Medline and CINAHL using the key terms 'magnetic resonance imaging' AND 'abandoned leads' OR 'epicardial leads'. Secondary literature and cross-references were supplemented. For reporting guidance, the Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 was used. International Prospective Register of Systematic Reviews (PROSPERO) registration number 465530. Twenty-one publications with a total of 656 patients with 854 abandoned and/or epicardial leads and 929 MRI scans of different anatomical regions were included. No scan-related major adverse cardiac event was documented, although the possibility of under-reporting of critical events in the literature should be considered. Furthermore, no severe device dysfunction or severe arrhythmia was reported. Mainly transient lead parameter changes were observed in 2.8% in the subgroup of patients with functional epicardial leads. As a possible correlate of myocardial affection, subjective sensations occurred mainly in the subgroup with abandoned epicardial leads (4.0%), but no change in myocardial biomarkers was observed. CONCLUSION: Existing publications did not report any relevant adverse events for MRI in patients with abandoned and/or epicardial leads if performed according to strict safety guidelines. However, a more rigorous risk-benefit calculation should be made for patients with epicardial leads.

Trends in incidence and mortality of early-onset cancer in Germany between 1999 and 2019.

Evidence on the recent temporal trend in the incidence and mortality of early-onset cancer, i.e., cancer diagnosed at ages of < 50 years, in Germany is scarce. To estimate the temporal trend in the incidence and mortality of early-onset cancer in Germany between 1999 and 2019. Input data were obtained from the Centre for Cancer Registry Data (Zentrum für Krebsregisterdaten, ZfKD). The analysis comprised all ages until 50 years and all types of cancer classified by the International Classification of Diseases (ICD-10)-codes C00-C97 (excl. C44). Temporal trends were estimated using negative binomial regression, differentiated by sex and cancer type. Between 1999 and 2019 in Germany, we observed stable or slightly increasing trends (0% and 1%) in the incidence of all early-onset cancers combined (C00-C97) for men and women, respectively, and strict declines in the mortality for both, men and women (-2% and - 3%). However, the trends differ largely with respect to sex and the individual cancer types. Early-onset cancer should be closely monitored to see whether stable and decreasing trends in the incidence and mortality continue. Knowing that despite decreasing incidence, the prevalence of a disease can rise due to their interplay with mortality, we recommend to maintain precise surveillance, efforts in prevention and early detection, as well as appropriate investments into healthcare resources, research and development.

Using the illness-death model to estimate age- and sex-standardized incidence rates of diabetes in Mexico from 2003 to 2015.

BACKGROUND: We aimed to estimate the age-specific and age-standardized incidence rate of diabetes for men and women in Mexico between 2003 and 2015, and to assess the relative change in incidence of diabetes between 2003 and 2015. METHODS: We use a partial differential equation describing the illness-death model to estimate the incidence rate (IR) of diabetes for the years 2003, 2009 and 2015 based on prevalence data from National Health Surveys conducted in Mexico, the mortality rate of the Mexican general population and plausible input values for age-specific mortality rate ratios associated with diabetes. RESULTS: The age-standardized IR of diabetes per 1000 person years (pryr) was similar among men (IRm) and women (IRw) in the year 2003 (IRm 6.1 vs. IRw 6.5 1000/pryr), 2009 (IRm: 7.0 vs. IRw: 8.4 1000/pryr), and in 2015 (IRm 8.0 vs. IRw 10.6 1000/pryr). The highest incident rates were observed among men and women in the 60-69 age group. CONCLUSIONS: Overall, the incidence rate of diabetes in Mexico between the years 2003 and 2015 remained stable. However, rates were markedly higher among women in the age group 40-49 and 50-59 in the year 2015 compared with rates in 2003.

A nonparametric proportional risk model to assess a treatment effect in time-to-event data.

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

Meta-Analysis of Diagnostic Accuracy Studies With Multiple Thresholds: Comparison of Approaches in a Simulation Study.

The development of methods for the meta-analysis of diagnostic test accuracy (DTA) studies is still an active area of research. While methods for the standard case where each study reports a single pair of sensitivity and specificity are nearly routinely applied nowadays, methods to meta-analyze receiver operating characteristic (ROC) curves are not widely used. This situation is more complex, as each primary DTA study may report on several pairs of sensitivity and specificity, each corresponding to a different threshold. In a case study published earlier, we applied a number of methods for meta-analyzing DTA studies with multiple thresholds to a real-world data example (Zapf et al., Biometrical Journal. 2021; 63(4): 699-711). To date, no simulation study exists that systematically compares different approaches with respect to their performance in various scenarios when the truth is known. In this article, we aim to fill this gap and present the results of a simulation study that compares three frequentist approaches for the meta-analysis of ROC curves. We performed a systematic simulation study, motivated by an example from medical research. In the simulations, all three approaches worked partially well. The approach by Hoyer and colleagues was slightly superior in most scenarios and is recommended in practice.

[Analysis of factors influencing outpatient paediatric antibiotic prescriptions in Bielefeld from 2015 to 2018]. / Analyse von Einflussfaktoren auf ambulante pädiatrische Antibiotikaverordnungen in Bielefeld 2015­2018.

BACKGROUND: There are significant regional differences in antibiotic prescribing behaviour. The reasons for this are still largely unknown. Beneath demographic and morbidity-related factors, doctor-specific or "cultural" factors may also play a role. A differentiated analysis including diagnostic data is needed to put these data into context. METHODS: A data analysis with secondary data available via the Westphalia-Lippe Association of Statutory Health Insurance Physicians (KVWL) was conducted on infection diagnoses and antibiotic prescriptions of outpatient paediatricians in the KV district of Bielefeld from 2015 to 2018. In addition, algorithmized 1:1 connections between diagnoses and prescriptions were performed. RESULTS: For 262,969 "medication patients" (AMP), 28,248 antibiotic prescriptions and 90,044 infection diagnoses were evaluated, from which 11,131 1:1 connections could be generated. Concerning the prescribing behaviour of individual paediatric GP offices, after adjusting for the denominator AMP and despite a comparable age and gender structure, there were some significant differences. This affected both the frequency of prescriptions and the qualitative composition of the substance groups prescribed. DISCUSSION: The differences in antibiotic prescribing behaviour, even at GP office level, cannot be adequately explained by the demographic composition or different morbidities of the respective clientele. Individual attitudes and local prescribing cultures are likely to play a relevant role. To address these offers an important approach for antibiotic stewardship (ABS). In addition to the area of outpatient paediatrics presented here, the methodology described can also be used as a model for more detailed analysis in other outpatient speciality groups.

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 .

Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study.

AIMS/HYPOTHESIS: This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development. METHODS: We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC. RESULTS: We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624). CONCLUSIONS/INTERPRETATION: We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.

Estimating incidence of type 1 and type 2 diabetes using prevalence data: the SEARCH for Diabetes in Youth study.

BACKGROUND: Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS: We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS: Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS: Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

Productivity-adjusted life years lost due to type 2 diabetes in Germany in 2020 and 2040.

AIMS/HYPOTHESIS: Type 2 diabetes can lead to reduced productivity during working age. We aimed to estimate productive life years lost associated with type 2 diabetes on the individual and population level in Germany in 2020 and 2040, while accounting for future trends in mortality. METHODS: Based on a mathematical projection model, we estimated age- and sex-specific productivity losses associated with type 2 diabetes during working age (20-69 years) in Germany in 2020 and 2040. Productivity losses in terms of excess mortality (years of life lost, YLL) and reductions in labour force participation, presenteeism and absenteeism (years of productivity lost, YPL) were summed to calculate productivity-adjusted life years (PALY) lost. Input data for the projection were based on meta-analyses, representative population-based studies and population projections to account for future trends in mortality. RESULTS: Compared with a person without type 2 diabetes, mean PALY lost per person with type 2 diabetes in 2020 was 2.6 years (95% CI 2.3, 3.0). Of these 2.6 years, 0.4 (95% CI 0.3, 0.4) years were lost due to YLL and 2.3 (95% CI 1.9, 2.6) years were lost due to YPL. Age- and sex-specific results show that younger age groups and women are expected to lose more productive life years than older age groups and men. Population-wide estimates suggest that 4.60 (95% CI 4.58, 4.63) million people with prevalent type 2 diabetes in 2020 are expected to lose 12.06 (95% CI 10.42, 13.76) million PALY (1.62 million years due to YLL and 10.44 million years due to YPL). In 2040, individual-level PALY lost are projected to slightly decrease due to reductions in YLL. In contrast, population-wide PALY lost are projected to increase to 15.39 (95% CI 13.19, 17.64) million due to an increase in the number of people with type 2 diabetes to 5.45 (95% CI 5.41, 5.50) million. CONCLUSIONS/INTERPRETATION: On the population level, a substantial increase in productivity burden associated with type 2 diabetes was projected for Germany between 2020 and 2040. Efforts to reduce the incidence rate of type 2 diabetes and diabetes-related complications may attenuate this increase.

Association between HIV infection and hypertension: a global systematic review and meta-analysis of cross-sectional studies.

BACKGROUND: Improved access to effective antiretroviral therapy has meant that people living with HIV (PLHIV) are surviving to older ages. However, PLHIV may be ageing differently to HIV-negative individuals, with dissimilar burdens of non-communicable diseases, such as hypertension. While some observational studies have reported a higher risk of prevalent hypertension among PLHIV compared to HIV-negative individuals, others have found a reduced burden. To clarify the relationship between HIV and hypertension, we identified observational studies and pooled their results to assess whether there is a difference in hypertension risk by HIV status. METHODS: We performed a global systematic review and meta-analysis of published cross-sectional studies that examined hypertension risk by HIV status among adults aged > 15 (PROSPERO: CRD42019151359). We searched MEDLINE, EMBASE, Global Health and Cochrane CENTRAL to August 23, 2020, and checked reference lists of included articles. Our main outcome was the risk ratio for prevalent hypertension in PLHIV compared to HIV-negative individuals. Summary estimates were pooled with a random effects model and meta-regression explored whether any difference was associated with study-level factors. RESULTS: Of 21,527 identified studies, 59 were eligible (11,101,581 participants). Crude global hypertension risk was lower among PLHIV than HIV-negative individuals (risk ratio 0.90, 95% CI 0.85-0.96), although heterogeneity between studies was high (I2 = 97%, p < 0.0001). The relationship varied by continent, with risk higher among PLHIV in North America (1.12, 1.02-1.23) and lower among PLHIV in Africa (0.75, 0.68-0.83) and Asia (0.77, 0.63-0.95). Meta-regression revealed strong evidence of a difference in risk ratios when comparing North American and European studies to African ones (North America 1.45, 1.21-1.74; Europe 1.20, 1.03-1.40). CONCLUSIONS: Our findings suggest that the relationship between HIV status and prevalent hypertension differs by region. The results highlight the need to tailor hypertension prevention and care to local contexts and underscore the importance of rapidly optimising integration of services for HIV and hypertension in the worst affected regions. The role of different risk factors for hypertension in driving context-specific trends remains unclear, so development of further cohorts of PLHIV and HIV-negative controls focused on this would also be valuable.

Diabetes free life expectancy and years of life lost associated with type 2 diabetes: projected trends in Germany between 2015 and 2040.

BACKGROUND: Type 2 diabetes (T2D) causes substantial disease burden and is projected to affect an increasing number of people in coming decades. This study provides projected estimates of life years free of type 2 diabetes (T2D) and years of life lost ([Formula: see text]) associated with T2D for Germany in the years 2015 and 2040. METHODS: Based on an illness-death model and the associated mathematical relation between prevalence, incidence and mortality, we projected the prevalence of diagnosed T2D using currently available data on the incidence rate of diagnosed T2D and mortality rates of people with and without diagnosed T2D. Projection of prevalence was achieved by integration of a partial differential equation, which governs the illness-death model. These projected parameters were used as input values to calculate life years free of T2D and [Formula: see text] associated with T2D for the German population aged 40 to 100 years in the years 2015 and 2040, while accounting for different assumptions on future trends in T2D incidence and mortality. RESULTS: Assuming a constant incidence rate, women and men at age 40 years in 2015 will live approximately 38 years and 33 years free of T2D, respectively. Up to the year 2040, these numbers are projected to increase by 1.0 years and 1.3 years. Assuming a decrease in T2D-associated excess mortality of 2% per year, women and men aged 40 years with T2D in 2015 will be expected to lose 1.6 and 2.7 years of life, respectively, compared to a same aged person without T2D. In 2040, these numbers would reduce by approximately 0.9 years and 1.6 years. This translates to 10.8 million and 6.4 million [Formula: see text] in the German population aged 40-100 years with prevalent T2D in 2015 and 2040, respectively. CONCLUSIONS: Given expected trends in mortality and no increase in T2D incidence, the burden due to premature mortality associated with T2D will decrease on the individual as well as on the population level. In addition, the expected lifetime without T2D is likely to increase. However, these trends strongly depend on future improvements of excess mortality associated with T2D and future incidence of T2D, which should motivate increased efforts of primary and tertiary prevention.

Meta-analysis of diagnostic accuracy studies with multiple thresholds: Comparison of different approaches.

Methods for standard meta-analysis of diagnostic test accuracy studies are well established and understood. For the more complex case in which studies report test accuracy across multiple thresholds, several approaches have recently been proposed. These are based on similar ideas, but make different assumptions. In this article, we apply four different approaches to data from a recent systematic review in the area of nephrology and compare the results. The four approaches use: a linear mixed effects model, a Bayesian multinomial random effects model, a time-to-event model and a nonparametric model, respectively. In the case study data, the accuracy of neutrophil gelatinase-associated lipocalin for the diagnosis of acute kidney injury was assessed in different scenarios, with sensitivity and specificity estimates available for three thresholds in each primary study. All approaches led to plausible and mostly similar summary results. However, we found considerable differences in results for some scenarios, for example, differences in the area under the receiver operating characteristic curve (AUC) of up to 0.13. The Bayesian approach tended to lead to the highest values of the AUC, and the nonparametric approach tended to produce the lowest values across the different scenarios. Though we recommend using these approaches, our findings motivate the need for a simulation study to explore optimal choice of method in various scenarios.

Association Between Urinary Catecholamine Excretion and Urine Volume.

Several confounders must be considered in the evaluation of urinary catecholamine excretion. However, literature is contradictory about potential confounders. The aim of the present study was to assess correlations between catecholamine excretion and anthropometric or clinical parameters with special attention to urine volume. A total of 967 24-h urinary catecholamine measurements were performed in 593 patients for diagnostic purposes. The indication for urine examination was suspicion of secondary hypertension, phaeochromocytoma, or paraganglioma. From the patients examined, 57% were females and 43% were males. The patients' age ranged between 15 and 87 years with a median [Q1; Q3] of 51 [39; 62] years. Seventy-eight percent of the patients suffered from hypertension. Seventy percent of patients took one or more antihypertensive drugs. The most commonly used drugs were ACE inhibitors (43%), while α-blockers (15%) were the least used drugs. Urinary excretion was between 500 and 11 950 ml/24 h with a median of 2200 [1600; 2685] ml/24 h. The median body mass index (BMI) was 26.7 [24.0; 30.4] kg/m2. The excretion of all catecholamines was greater in men than in women (all p<0.0001). Epinephrine (p=0.0026), dopamine (p<0.0001), and metanephrine (p=0.0106) excretion decreased with age. BMI was associated with urinary excretion of dopamine (p<0.0001), norepinephrine (p=0.0026), normetanephrine (p<0.0001), and homovanillylmandelic acid (HVMA; p=0.0251). Urine volume correlated with urinary dopamine (p=0.0127), metanephrine (p<0.0001), normetanephrine (p=0.0070), and HVMA (p<0.0028) excretion. In addition to the established associations between urinary catecholamine excretion and age, gender, and BMI in the present study, urinary catecholamine excretion correlated also with urine volume.

Analysing detection of chronic diseases with prolonged sub-clinical periods: modelling and application to hypertension in the U.S.

BACKGROUND: We recently introduced a system of partial differential equations (PDEs) to model the prevalence of chronic diseases with a possibly prolonged state of asymptomatic, undiagnosed disease preceding a diagnosis. Common examples for such diseases include coronary heart disease, type 2 diabetes or cancer. Widespread application of the new method depends upon mathematical treatment of the system of PDEs. METHODS: In this article, we study the existence and the uniqueness of the solution of the system of PDEs. To demonstrate the usefulness and importance of the system, we model the age-specific prevalence of hypertension in the US 1999-2010. RESULTS: The examinations of mathematical properties provide a way to solve the systems of PDEs by the method of characteristics. In the application to hypertension, we obtain a good agreement between modeled and surveyed age-specific prevalences. CONCLUSIONS: The described system of PDEs provides a practical way to examine the epidemiology of chronic diseases with a state of undiagnosed disease preceding a diagnosis.