Bayesian Meta-regression Model Research Articles

Do all individuals benefit equally from non-surgical periodontal therapy? Secondary analyses of systematic review data.

This study aimed to assess the variability and treatment effect heterogeneity in response to non-surgical periodontal therapy (NSPT). Data from randomized controlled trials included in two recent systematic reviews on the effect of NSPT on mean clinical attachment loss (CAL), mean probing pocket depth (PPD), percentage of sites with bleeding on probing (%BOP), PPD ≤3 mm (%PD ≤3 mm), and C-reactive protein levels (CRP) at 3-12-month follow-up among adults with systemic diseases or conditions were used. In these trials, the control arms received no treatment, hygiene advice, or supragingival scaling. The Bayesian meta-regression models were utilized to assess the variability ratios between NSPT and control groups. Data from 36 trials on mean PPD, 32 trials on mean CAL, eight trials on %PD ≤3 mm, 31 trials on %BOP and 19 trials on CRP were used. Variability in mean CAL and CRP was approximately 10% higher in the NSPT arms than in the control arms, hinting that there may be room for treatment effect heterogeneity. Instead, variability in mean PPD, %BOP, and %PD ≤3 mm was lower in the NSPT arms than in the control arms. Potential treatment effect heterogeneity in response to NSPT was observed for CRP and mean CAL. However, substantial measurement error in CAL and natural variation in CRP may contribute to these findings. Conversely, treatment effect heterogeneity appears less pronounced for mean PPD, %BOP, and %PD ≤3 mm, potentially due to greater treatment effects in patients with more severe periodontitis and reduced measurement error in these parameters.

Trends in adverse effects of medical treatment in Paediatric populations in the United States: A global burden of disease study, 2000-2019.

Adverse effects of medical treatment (AEMT) pose significant risks to paediatric patients. However, the mortality trends associated with AEMT in this population have been unclear. We aimed to clarify the trends in the incidence, disability-adjusted life years (DALYs) and mortality rates of AEMT for children in the US from 2000 to 2019. Data were retrieved from the Global Burden of Disease study 2019. We estimated age-standardized incidence, DALYs and mortality rates of paediatric AEMT per 100,000 children in the US using a Bayesian meta-regression model. We also analysed incidence, DALYs and mortality in different age groups, and employed Joinpoint regression models to assess the age- and sex-specific trends. The number of deaths due to AEMT in children, the number of cases, and DALYs were 105.1, 551,076 and 145,555 in 2019, decreased by 37.5%, 6% and 28% from those in 2000, respectively. Age-standardized mortality rates decreased across all age groups, while the incidence increased across all age groups with an average annual percentage change (AAPC) of 2.2% in those children <1 year and 4.5% in 5-9 years of age. The increases in DALYs over time was higher in children aged 1-4 years (AAPC: 0.51, 95% CI: 0.47, 0.62) and 5-9 years (AAPC: 0.33, 95% CI: 0.15, 0.50), with the 1-4 year age group being the highest. The study reveals declining AEMT mortality but rising incidence and DALYs, emphasizing a disproportionate burden in <1, 1-4 and 5-9 years. To develop effective mitigation strategies, future research is warranted to identify the causes of increased AEMT in children, especially young males.

Global, regional, and national burden of gout, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

Gout is an inflammatory arthritis manifesting as acute episodes of severe joint pain and swelling, which can progress to chronic tophaceous or chronic erosive gout, or both. Here, we present the most up-to-date global, regional, and national estimates for prevalence and years lived with disability (YLDs) due to gout by sex, age, and location from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, as well as forecasted prevalence to 2050. Gout prevalence and YLDs from 1990 to 2020 were estimated by drawing on population-based data from 35 countries and claims data from the USA and Taiwan (province of China). Nested Bayesian meta-regression models were used to estimate prevalence and YLDs due to gout by age, sex, and location. Prevalence was forecast to 2050 with a mixed-effects model. In 2020, 55·8 million (95% uncertainty interval 44·4-69·8) people globally had gout, with an age-standardised prevalence of 659·3 (525·4-822·3) per 100 000, an increase of 22·5% (20·9-24·2) since 1990. Globally, the prevalence of gout in 2020 was 3·26 (3·11-3·39) times higher in males than in females and increased with age. The total number of prevalent cases of gout is estimated to reach 95·8 million (81·1-116) in 2050, with population growth being the largest contributor to this increase and only a very small contribution from the forecasted change in gout prevalence. Age-standardised gout prevalence in 2050 is forecast to be 667 (531-830) per 100 000 population. The global age-standardised YLD rate of gout was 20·5 (14·4-28·2) per 100 000 population in 2020. High BMI accounted for 34·3% (27·7-40·6) of YLDs due to gout and kidney dysfunction accounted for 11·8% (9·3-14·2). Our forecasting model estimates that the number of individuals with gout will increase by more than 70% from 2020 to 2050, primarily due to population growth and ageing. With the association between gout disability and high BMI, dietary and lifestyle modifications focusing on bodyweight reduction are needed at the population level to reduce the burden of gout along with access to interventions to prevent and control flares. Despite the rigour of the standardised GBD methodology and modelling, in many countries, particularly low-income and middle-income countries, estimates are based on modelled rather than primary data and are also lacking severity and disability estimates. We strongly encourage the collection of these data to be included in future GBD iterations. Bill & Melinda Gates Foundation and the Global Alliance for Musculoskeletal Health.

Towards optimized methodological parameters for maximizing the behavioral effects of transcranial direct current stimulation.

Transcranial direct current stimulation (tDCS) administers low-intensity direct current electrical stimulation to brain regions via electrodes arranged on the surface of the scalp. The core promise of tDCS is its ability to modulate brain activity and affect performance on diverse cognitive functions (affording causal inferences regarding regional brain activity and behavior), but the optimal methodological parameters for maximizing behavioral effects remain to be elucidated. Here we sought to examine the effects of 10 stimulation and experimental design factors across a series of five cognitive domains: motor performance, visual search, working memory, vigilance, and response inhibition. The objective was to identify a set of optimal parameter settings that consistently and reliably maximized the behavioral effects of tDCS within each cognitive domain. We surveyed tDCS effects on these various cognitive functions in healthy young adults, ultimately resulting in 721 effects across 106 published reports. Hierarchical Bayesian meta-regression models were fit to characterize how (and to what extent) these design parameters differentially predict the likelihood of positive/negative behavioral outcomes. Consistent with many previous meta-analyses of tDCS effects, extensive variability was observed across tasks and measured outcomes. Consequently, most design parameters did not confer consistent advantages or disadvantages to behavioral effects-a domain-general model suggested an advantage to using within-subjects designs (versus between-subjects) and the tendency for cathodal stimulation (relative to anodal stimulation) to produce reduced behavioral effects, but these associations were scarcely-evident in domain-specific models. These findings highlight the urgent need for tDCS studies to more systematically probe the effects of these parameters on behavior to fulfill the promise of identifying causal links between brain function and cognition.

Global, regional, and national burden of rheumatoid arthritis, 1990-2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021.

Rheumatoid arthritis is a chronic autoimmune inflammatory disease associated with disability and premature death. Up-to-date estimates of the burden of rheumatoid arthritis are required for health-care planning, resource allocation, and prevention. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, we provide updated estimates of the prevalence of rheumatoid arthritis and its associated deaths and disability-adjusted life-years (DALYs) by age, sex, year, and location, with forecasted prevalence to 2050. Rheumatoid arthritis prevalence was estimated in 204 countries and territories from 1990 to 2020 using Bayesian meta-regression models and data from population-based studies and medical claims data (98 prevalence and 25 incidence studies). Mortality was estimated from vital registration data with the Cause of Death Ensemble model (CODEm). Years of life lost (YLL) were calculated with use of standard GBD lifetables, and years lived with disability (YLDs) were estimated from prevalence, a meta-analysed distribution of rheumatoid arthritis severity, and disability weights. DALYs were calculated by summing YLLs and YLDs. Smoking was the only risk factor analysed. Rheumatoid arthritis prevalence was forecast to 2050 by logistic regression with Socio-Demographic Index as a predictor, then multiplying by projected population estimates. In 2020, an estimated 17·6 million (95% uncertainty interval 15·8-20·3) people had rheumatoid arthritis worldwide. The age-standardised global prevalence rate was 208·8 cases (186·8-241·1) per 100 000 population, representing a 14·1% (12·7-15·4) increase since 1990. Prevalence was higher in females (age-standardised female-to-male prevalence ratio 2·45 [2·40-2·47]). The age-standardised death rate was 0·47 (0·41-0·54) per 100 000 population (38 300 global deaths [33 500-44 000]), a 23·8% (17·5-29·3) decrease from 1990 to 2020. The 2020 DALY count was 3 060 000 (2 320 000-3 860 000), with an age-standardised DALY rate of 36·4 (27·6-45·9) per 100 000 population. YLDs accounted for 76·4% (68·3-81·0) of DALYs. Smoking risk attribution for rheumatoid arthritis DALYs was 7·1% (3·6-10·3). We forecast that 31·7 million (25·8-39·0) individuals will be living with rheumatoid arthritis worldwide by 2050. Rheumatoid arthritis mortality has decreased globally over the past three decades. Global age-standardised prevalence rate and YLDs have increased over the same period, and the number of cases is projected to continue to increase to the year 2050. Improved access to early diagnosis and treatment of rheumatoid arthritis globally is required to reduce the future burden of the disease. Bill & Melinda Gates Foundation, Institute of Bone and Joint Research, and Global Alliance for Musculoskeletal Health.

Estimating Patient-Specific Relative Benefit of Adding Biologics to Conventional Rheumatoid Arthritis Treatment

Current evidence remains ambiguous regarding whether biologics should be added to conventional treatment of rheumatoid arthritis for specific patients, which may cause potential overuse or treatment delay. To estimate the benefit of adding biologics to conventional antirheumatic drugs for the treatment of rheumatoid arthritis given baseline characteristics. Cochrane CENTRAL, Scopus, MEDLINE, and the World Health Organization International Clinical Trials Registry Platform were searched for articles published from database inception to March 2, 2022. Randomized clinical trials comparing certolizumab plus conventional antirheumatic drugs with placebo plus conventional drugs were selected. Individual participant data of the prespecified outcomes and covariates were acquired from the Vivli database. A 2-stage model was fitted to estimate patient-specific relative outcomes of adding certolizumab vs conventional drugs only. Stage 1 was a penalized logistic regression model to estimate the baseline expected probability of the outcome regardless of treatment using baseline characteristics. Stage 2 was a bayesian individual participant data meta-regression model to estimate the relative outcomes for a particular baseline expected probability. Patient-specific results were displayed interactively on an application based on a 2-stage model. The primary outcome was low disease activity or remission at 3 months, defined by 3 disease activity indexes (ie, Disease Activity Score based on the evaluation of 28 joints, Clinical Disease Activity Index, or Simplified Disease Activity Index). Individual participant data were obtained from 3790 patients (2996 female [79.1%] and 794 male [20.9%]; mean [SD] age, 52.7 [12.3] years) from 5 large randomized clinical trials for moderate to high activity rheumatoid arthritis with usable data for 22 prespecified baseline covariates. Overall, adding certolizumab was associated with a higher probability of reaching low disease activity. The odds ratio for patients with an average baseline expected probability of the outcome was 6.31 (95% credible interval, 2.22-15.25). However, the benefits differed in patients with different baseline characteristics. For example, the estimated risk difference was smaller than 10% for patients with either low or high baseline expected probability. In this individual participant data meta-analysis, adding certolizumab was associated with more effectiveness for rheumatoid arthritis in general. However, the benefit was uncertain for patients with low or high baseline expected probability, for whom other evaluations were necessary. The interactive application displaying individual estimates may help with treatment selection.

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Bill & Melinda Gates Foundation.

A meta-analysis of GFR slope as a surrogate endpoint for kidney failure.

Glomerular filtration rate (GFR) decline is causally associated with kidney failure and is a candidate surrogate endpoint for clinical trials of chronic kidney disease (CKD) progression. Analyses across a diverse spectrum of interventions and populations is required for acceptance of GFR decline as an endpoint. In an analysis of individual participant data, for each of 66 studies (total of 186,312 participants), we estimated treatment effects on the total GFR slope, computed from baseline to 3 years, and chronic slope, starting at 3 months after randomization, and on the clinical endpoint (doubling of serum creatinine, GFR < 15 ml min-1 per 1.73 m2 or kidney failure with replacement therapy). We used a Bayesian mixed-effects meta-regression model to relate treatment effects on GFR slope with those on the clinical endpoint across all studies and by disease groups (diabetes, glomerular diseases, CKD or cardiovascular diseases). Treatment effects on the clinical endpoint were strongly associated with treatment effects on total slope (median coefficient of determination (R2) = 0.97 (95% Bayesian credible interval (BCI) 0.82-1.00)) and moderately associated with those on chronic slope (R2 = 0.55 (95% BCI 0.25-0.77)). There was no evidence of heterogeneity across disease. Our results support the use of total slope as a primary endpoint for clinical trials of CKD progression.

Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021.

Low back pain is highly prevalent and the main cause of years lived with disability (YLDs). We present the most up-to-date global, regional, and national data on prevalence and YLDs for low back pain from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021. Population-based studies from 1980 to 2019 identified in a systematic review, international surveys, US medical claims data, and dataset contributions by collaborators were used to estimate the prevalence and YLDs for low back pain from 1990 to 2020, for 204 countries and territories. Low back pain was defined as pain between the 12th ribs and the gluteal folds that lasted a day or more; input data using alternative definitions were adjusted in a network meta-regression analysis. Nested Bayesian meta-regression models were used to estimate prevalence and YLDs by age, sex, year, and location. Prevalence was projected to 2050 by running a regression on prevalence rates using Socio-demographic Index as a predictor, then multiplying them by projected population estimates. In 2020, low back pain affected 619 million (95% uncertainty interval 554-694) people globally, with a projection of 843 million (759-933) prevalent cases by 2050. In 2020, the global age-standardised rate of YLDs was 832 per 100 000 (578-1070). Between 1990 and 2020, age-standardised rates of prevalence and YLDs decreased by 10·4% (10·9-10·0) and 10·5% (11·1-10·0), respectively. A total of 38·8% (28·7-47·0) of YLDs were attributed to occupational factors, smoking, and high BMI. Low back pain remains the leading cause of YLDs globally, and in 2020, there were more than half a billion prevalent cases of low back pain worldwide. While age-standardised rates have decreased modestly over the past three decades, it is projected that globally in 2050, more than 800 million people will have low back pain. Challenges persist in obtaining primary country-level data on low back pain, and there is an urgent need for more high-quality, primary, country-level data on both prevalence and severity distributions to improve accuracy and monitor change. Bill and Melinda Gates Foundation.

Estimating national-level measles case–fatality ratios in low-income and middle-income countries: an updated systematic review and modelling study

To understand the current measles mortality burden, and to mitigate the future burden, it is crucial to have robust estimates of measles case fatalities. Estimates of measles case-fatality ratios (CFRs) that are specific to age, location, and time are essential to capture variations in underlying population-level factors, such as vaccination coverage and measles incidence, which contribute to increases or decreases in CFRs. In this study, we updated estimates of measles CFRs by expanding upon previous systematic reviews and implementing a meta-regression model. Our objective was to use all information available to estimate measles CFRs in low-income and middle-income countries (LMICs) by country, age, and year. For this systematic review and meta-regression modelling study, we searched PubMed on Dec 31, 2020 for all available primary data published from Jan 1, 1980 to Dec 31, 2020, on measles cases and fatalities occurring up to Dec 31, 2019 in LMICs. We included studies that previous systematic reviews had included or which contained primary data on measles cases and deaths from hospital-based, community-based, or surveillance-based reports, including outbreak investigations. We excluded studies that were not in humans, or reported only data that were only non-primary, or on restricted populations (eg, people living with HIV), or on long-term measles mortality (eg, death from subacute sclerosing panencephalitis), and studies that did not include country-level data or relevant information on measles cases and deaths, or were for a high-income country. We extracted summary data on measles cases and measles deaths from studies that fitted our inclusion and exclusion criteria. Using these data and a suite of covariates related to measles CFRs, we implemented a Bayesian meta-regression model to produce estimates of measles CFRs from 1990 to 2019 by location and age group. This study was not registered with PROSPERO or otherwise. We identified 2705 records, of which 208 sources contained information on both measles cases and measles deaths in LMICS and were included in the review. Between 1990 and 2019, CFRs substantially decreased in both community-based and hospital-based settings, with consistent patterns across age groups. For people aged 0-34 years, we estimated a mean CFR for 2019 of 1·32% (95% uncertainty interval [UI] 1·28-1·36) among community-based settings and 5·35% (5·08-5·64) among hospital-based settings. We estimated the 2019 CFR in community-based settings to be 3·03% (UI 2·89-3·16) for those younger than 1 year, 1·63% (1·58-1·68) for age 1-4 years, 0·84% (0·80-0·87) for age 5-9 years, and 0·67% (0·64-0·70) for age 10-14 years. Although CFRs have declined between 1990 and 2019, there are still large heterogeneities across locations and ages. One limitation of this systematic review is that we were unable to assess measles CFR among particular populations, such as refugees and internally displaced people. Our updated methodological framework and estimates could be used to evaluate the effect of measles control and vaccination programmes on reducing the preventable measles mortality burden. Bill & Melinda Gates Foundation; Gavi, the Vaccine Alliance; and the US National Institutes of Health.

Synthesizing cross-design evidence and cross-format data using network meta-regression.

In network meta-analysis (NMA), we synthesize all relevant evidence about health outcomes with competing treatments. The evidence may come from randomized clinical trials (RCT) or non-randomized studies (NRS) as individual participant data (IPD) or as aggregate data (AD). We present a suite of Bayesian NMA and network meta-regression (NMR) models allowing for cross-design and cross-format synthesis. The models integrate a three-level hierarchical model for synthesizing IPD and AD into four approaches. The four approaches account for differences in the design and risk of bias (RoB) in the RCT and NRS evidence. These four approaches variously ignoring differences in RoB, using NRS to construct penalized treatment effect priors and bias-adjustment models that control the contribution of information from high RoB studies in two different ways. We illustrate the methods in a network of three pharmacological interventions and placebo for patients with relapsing-remitting multiple sclerosis. The estimated relative treatment effects do not change much when we accounted for differences in design and RoB. Conducting network meta-regression showed that intervention efficacy decreases with increasing participant age. We also re-analysed a network of 431 RCT comparing 21 antidepressants, and we did not observe material changes in intervention efficacy when adjusting for studies' high RoB. We re-analysed both case studies accounting for different study RoB. In summary, the described suite of NMA/NMR models enables the inclusion of all relevant evidence while incorporating information on the within-study bias in both observational and experimental data and enabling estimation of individualized treatment effects through the inclusion of participant characteristics.

Burden of Diabetes Mellitus in Nepal: An Analysis of Global Burden of Disease Study 2019.

Globally, the number of people living with diabetes mellitus (DM) increased by 62% between 1990 and 2019, affecting 463 million people in 2019, and is projected to increase further by 51% by 2045. The increasing burden of DM that requires chronic care could have a considerable cost implication in the health system, particularly in resource constraint settings like Nepal. In this context, this study attempts to present the burden of DM in terms of prevalence, mortality, and disability adjusted life years (DALYs). The study is based on the Global Burden of Disease Study 2019, a multinational collaborative research, led by the Institute for Health Metrics and Evaluations. In the study, the overall prevalence of DM was estimated using DisMod MR-2.1, a Bayesian metaregression model. DALYs were estimated summing years of life lost due to premature death and years lived with disability. There were a total of 1,412,180 prevalent cases of DM, 3,474 deaths and 189,727 DALYs, due to DM in 2019. All-age prevalence rate and the age-standardized prevalence rate of DM stood at 4,642.83 (95% uncertainty interval (UI): 4,178.58-5,137.74) and 5,735.58 (95% UI: 5,168.74-6327.73) cases per 100,000 population, respectively, in 2019. In 2019, 1.8% (95% UI: 1.54, 2.07) of total deaths were from DM, which is a more than three-fold increase from the proportion of deaths attributed in 1990 (0.43%, 95% UI: 0.36, 0.5) with most of these deaths being from DM type 2. In 2019, a total of 189,727 disability adjusted life years (DALYs) were attributable to DM of which 105,950 DALYs were among males, and the remaining 83,777 DALYs were among females. Overall, between 1990 and 2019, the DALYs, attributable to Type 1 and 2 DM combined and for Type 2 DM only, have increased gradually across both sexes. However, the DALYs per 100,000 attributable to DM have slightly reduced across both sexes in that time. There is a high burden of DM in Nepal in 2019 with a steep increase in the proportion of deaths attributable to DM in Nepal which could pose a serious challenge to the health system. Primary prevention of DM requires collaborative efforts from multiple sectors. Meanwhile, the current federal structure could be an opportunity for integrated, locally tailored public health and clinical interventions for the prevention of the disease and its consequences.

Phylogeny explains capture mortality of sharks and rays in pelagic longline fisheries: a global meta-analytic synthesis

Apex and mesopredators such as elasmobranchs are important for maintaining ocean health and are the focus of conservation efforts to mitigate exposure to fishing and other anthropogenic hazards. Quantifying fishing mortality components such as at-vessel mortality (AVM) is necessary for effective bycatch management. We assembled a database for 61 elasmobranch species and conducted a global meta-synthesis to estimate pelagic longline AVM rates. Evolutionary history was a significant predictor of AVM, accounting for up to 13% of variance in Bayesian phylogenetic meta-regression models for Lamniformes and Carcharhiniformes clades. Phylogenetically related species may have a high degree of shared traits that explain AVM. Model-estimated posterior mean AVM rates ranged from 5% (95% HDI 0.1%–16%) for pelagic stingrays and 76% (95% HDI 49%–90%) for salmon sharks. Measures that reduce catch, and hence AVM levels, such as input controls, bycatch quotas and gear technology to increase selectivity are appropriate for species with higher AVM rates. In addition to reducing catchability, handling-and-release practices and interventions such as retention bans in shark sanctuaries and bans on shark finning and trade hold promise for species with lower AVM rates. Robust, and where applicable, phylogenetically-adjusted elasmobranch AVM rates are essential for evidence-informed bycatch policy.

The global, regional, and national burden of benign prostatic hyperplasia in 204 countries and territories from 2000 to 2019: a systematic analysis for the Global Burden of Disease Study 2019

Benign prostatic hyperplasia is a common urological disease affecting older men worldwide, but comprehensive data about the global, regional, and national burden of benign prostatic hyperplasia and its trends over time are scarce. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated global trends in, and prevalence of, benign prostatic hyperplasia and disability-adjusted life-years (DALYs) due to benign prostatic hyperplasia, in 21 regions and 204 countries and territories from 2000 to 2019. This study was conducted with GBD 2019 analytical and modelling strategies. Primary prevalence data came from claims from three countries and from hospital inpatient encounters from 45 locations. A Bayesian meta-regression modelling tool, DisMod-MR version 2.1, was used to estimate the age-specific, location-specific, and year-specific prevalence of benign prostatic hyperplasia. Age-standardised prevalence was calculated by the direct method using the GBD reference population. Years lived with disability (YLDs) due to benign prostatic hyperplasia were estimated by multiplying the disability weight by the symptomatic proportion of the prevalence of benign prostatic hyperplasia. Because we did not estimate years of life lost associated with benign prostatic hyperplasia, disability-adjusted life-years (DALYs) equalled YLDs. The final estimates were compared across Socio-demographic Index (SDI) quintiles. The 95% uncertainty intervals (UIs) were estimated as the 25th and 975th of 1000 ordered draws from a bootstrap distribution. Globally, there were 94·0 million (95% UI 73·2 to 118) prevalent cases of benign prostatic hyperplasia in 2019, compared with 51·1 million (43·1 to 69·3) cases in 2000. The age-standardised prevalence of benign prostatic hyperplasia was 2480 (1940 to 3090) per 100 000 people. Although the global number of prevalent cases increased by 70·5% (68·6 to 72·7) between 2000 and 2019, the global age-standardised prevalence remained stable (-0·770% [-1·56 to 0·0912]). The age-standardised prevalence in 2019 ranged from 6480 (5130 to 8080) per 100 000 in eastern Europe to 987 (732 to 1320) per 100 000 in north Africa and the Middle East. All five SDI quintiles observed an increase in the absolute DALY burden between 2000 and 2019. The most rapid increases in the absolute DALY burden were seen in the middle SDI quintile (94·7% [91·8 to 97·6]), the low-middle SDI quintile (77·3% [74·1 to 81·2]), and the low SDI quintile (77·7% [72·9 to 83·2]). Between 2000 and 2019, age-standardised DALY rates changed less, but the three lower SDI quintiles (low, low-middle, and middle) saw small increases, and the two higher SDI quintiles (high and high-middle SDI) saw small decreases. The absolute burden of benign prostatic hyperplasia is rising at an alarming rate in most of the world, particularly in low-income and middle-income countries that are currently undergoing rapid demographic and epidemiological changes. As more people are living longer worldwide, the absolute burden of benign prostatic hyperplasia is expected to continue to rise in the coming years, highlighting the importance of monitoring and planning for future health system strain. Bill & Melinda Gates Foundation. For the Amharic translation of the abstract see Supplementary Materials section.

Estimation of the exposure response relation by combining epidemiological, human biomarker and animal data in a Bayesian meta-regression model

Estimation of the exposure response relation by combining epidemiological, human biomarker and animal data in a Bayesian meta-regression model

Selected Articles from This Issue

There is consensus that benzene exposure is causally related to acute myeloid leukemia (AML), but accurate description of the AML-benzene exposure response curve (ERC) is still needed for risk assessment. Scholten and colleagues hypothesized that using data from both human and animal studies could increase precision of the estimated ERC for benzene induced AML. The authors found that risk estimates based on the complete dataset (23 experimental and observation studies) were more precise, but also that harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation.Screening reduces lung cancer mortality, but the low specificity of current eligibility criteria has blocked implementation. Risk biomarkers (e.g. AHRR methylation of leukocyte DNA) might mitigate this. Jacobsen and colleagues utilized the Copenhagen City Heart Study which included >9,200 individuals with detailed smoking information and >20 years of lung cancer follow-up. AHRR methylation was added to 7 established eligibility criteria. NLST criteria plus AHRR methylation <55% led to a 22% lower predicted screening burden and a specificity for 5-year lung cancer of 84.0%. AHRR hypomethylation provides predictive lung cancer risk information on top of detailed smoking history and might be useful in lung cancer screening.Policy models used to examine the effectiveness of colorectal cancer screening and surveillance assume colonoscopy is very sensitive for detection of adenomas. This simulation study by Rutter and colleagues examined these assumptions and found evidence that colonoscopy sensitivity circa 1990 was lower than generally assumed for adenomas smaller than 10mm, and potentially much lower for adenomas smaller than 6mm. These findings highlight the importance of evaluating model assumptions. Colonoscopy is a highly effective screening and diagnostic test, though it may have been less effective for colorectal cancer prevention than previously estimated.Oncotype DX recurrence score (ODX- RS) is a prognostic biomarker for early-stage, node-negative, estrogen receptor-positive (ER+) breast cancer. Using data from the clinical oncology National Cancer Database, this study of 227,259 eligible breast cancer cases by Moore and colleagues found that white patients were more likely to receive an ODX RS test compared with Black, Hispanic, and Asian American patients. Furthermore, black patients had higher proportions of high-risk scores compared with non-black patients. ODX RS was similarly predictive for total mortality across all races/ethnicities. These findings emphasize the importance of developing strategies to increase ODX RS uptake among racial/ethnic minorities and call for more investigations on potential racial/ethnic differences in breast cancer biology.

The Burden of Childhood Asthma by Age Group, 1990-2019: A Systematic Analysis of Global Burden of Disease 2019 Data.

BackgroundAsthma is a common respiratory disease in children. We aimed to update information about the incidence and mortality and disability-adjusted life years (DALYs) of childhood asthma and provide evidence-based recommendations for childhood asthma prevention.MethodsData were obtained from the Global Burden of Disease (GBD) study, which was conducted from 1990 to 2019 in 204 countries. First, we estimated incidence, mortality and DALY rates of childhood asthma using a Bayesian meta-regression model. Second, we analyzed the relationship between the sociodemographic index (SDI) and DALYs in different age groups. Third, we studied changes in trends of the age-standardized DALY rate between 1990 and 2019 based on age group, SDI, and risk factors.ResultsGlobally, the number of deaths due to childhood asthma and the incidence and DALY rates were 12.9 thousand (95% UI 10.6 to 15.7), 22 million (95% UI 15 to 31), and 5.1 million (95% UI 3.4 to 7.5) in 2019, decreasing by 65.1% (95% UI 47.6 to 72.4), 5.3% (95% UI 2.6 to 8.8) and 30% (95% UI 18 to 41) from those in 1990, respectively. With the exception of high-SDI regions, the age-standardized DALY rate in all age groups in all SDI regions declined. In 2019, the age-standardized DALY rate in 1- to 4-year-old individuals was highest in low-SDI regions and that of 5- to 19-year-old individuals was highest in high-SDI regions. In contrast to low-SDI regions, individuals in high-SDI regions had a higher risk of DALYs due to asthma, except in those aged 1 to 4 years. A high body mass index (BMI) was a stronger risk factor than occupational asthmagens for childhood asthma.ConclusionOur findings provide insight into asthma prevention and treatment through the identification of key factors related to childhood asthma. Based on the data available, different risk factors according to age group and region/country suggest different prevention strategies, which is key for preventing childhood asthma.

Estimation of the Exposure-Response Relation between Benzene and Acute Myeloid Leukemia by Combining Epidemiologic, Human Biomarker, and Animal Data.

Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure-response curve (ERC) modeling when data across the exposure range are sparse. We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies. A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [<40 parts per million (ppm)-years] from this model were comparable, but more precise when the ERC was derived using all available data than when using AML data only. Allowing for between-study heterogeneity, RRs and 95% prediction intervals (95% PI) at 5 ppm-years were 1.58 (95% PI, 1.01-3.22) and 1.44 (95% PI, 0.85-3.42), respectively. Integrating the available epidemiologic, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation. By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.See related commentary by Keil, p. 695.

Extracellular Buffering Supplements to Improve Exercise Capacity and Performance: A Comprehensive Systematic Review and Meta-analysis.

Extracellular buffering supplements [sodium bicarbonate (SB), sodium citrate (SC), sodium/calcium lactate (SL/CL)] are ergogenic supplements, although questions remain about factors which may modify their effect. To quantify the main effect of extracellular buffering agents on exercise outcomes, and to investigate the influence of potential moderators on this effect using a systematic review and meta-analytic approach. This study was designed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three databases were searched for articles that were screened according to inclusion/exclusion criteria. Bayesian hierarchical meta-analysis and meta-regression models were used to investigate pooled effects of supplementation and moderating effects of a range of factors on exercise and biomarker responses. 189 articles with 2019 participants were included, 158 involving SB supplementation, 30 with SC, and seven with CL/SL; four studies provided a combination of buffering supplements together. Supplementation led to a mean estimated increase in blood bicarbonate of + 5.2mmol L-1 (95% credible interval (CrI) 4.7-5.7). The meta-analysis models identified a positive overall effect of supplementation on exercise capacity and performance compared to placebo [ES0.5 = 0.17 (95% CrI 0.12-0.21)] with potential moderating effects of exercise typeand duration, training status and when the exercise test was performed following prior exercise. The greatest ergogenic effects were shown for exercise durations of 0.5-10min [ES0.5 = 0.18 (0.13-0.24)] and > 10min [ES0.5 = 0.22 (0.10-0.33)]. Evidence of greater effects on exercise were obtained when blood bicarbonate increases were medium (4-6mmol L-1) and large (> 6mmol L-1) compared with small (≤ 4mmol L-1) [βSmall:Medium = 0.16 (95% CrI 0.02-0.32), βSmall:Large = 0.13 (95% CrI - 0.03 to 0.29)]. SB (192 outcomes) was more effective for performance compared to SC (39 outcomes) [βSC:SB = 0.10 (95% CrI - 0.02 to 0.22)]. Extracellular buffering supplements generate large increases in blood bicarbonate concentration leading to positive overall effects on exercise, with sodium bicarbonate being most effective. Evidence for several group-level moderating factors were identified. These data can guide an athlete's decision as to whether supplementation with buffering agents might be beneficial for their specific aims.

Incidence and prevalence of tuberculosis in incarcerated populations: a systematic review and meta-analysis

SummaryBackgroundPrisons are recognised as high-risk environments for tuberculosis, but there has been little systematic investigation of the global and regional incidence and prevalence of tuberculosis, and its determinants, in prisons. We did a systematic review and meta-analysis to assess the incidence and prevalence of tuberculosis in incarcerated populations by geographical region.MethodsIn this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Knowledge, and the LILACS electronic database from Jan 1, 1980, to Nov 15, 2020, for cross-sectional and cohort studies reporting the incidence of Mycobacterium tuberculosis infection, incidence of tuberculosis, or prevalence of tuberculosis among incarcerated individuals in all geographical regions. We extracted data from individual studies, and calculated pooled estimates of incidence and prevalence through hierarchical Bayesian meta-regression modelling. We also did subgroup analyses by region. Incidence rate ratios between prisons and the general population were calculated by dividing the incidence of tuberculosis in prisons by WHO estimates of the national population-level incidence.FindingsWe identified 159 relevant studies; 11 investigated the incidence of M tuberculosis infection (n=16 318), 51 investigated the incidence of tuberculosis (n=1 858 323), and 106 investigated the prevalence of tuberculosis (n=6 727 513) in incarcerated populations. The overall pooled incidence of M tuberculosis infection among prisoners was 15·0 (95% credible interval [CrI] 3·8–41·6) per 100 person-years. The incidence of tuberculosis (per 100 000 person-years) among prisoners was highest in studies from the WHO African (2190 [95% CrI 810–4840] cases) and South-East Asia (1550 [240–5300] cases) regions and in South America (970 [460–1860] cases), and lowest in North America (30 [20–50] cases) and the WHO Eastern Mediterranean region (270 [50–880] cases). The prevalence of tuberculosis was greater than 1000 per 100 000 prisoners in all global regions except for North America and the Western Pacific, and highest in the WHO South-East Asia region (1810 [95% CrI 670–4000] cases per 100 000 prisoners). The incidence rate ratio between prisons and the general population was much higher in South America (26·9; 95% CrI 17·1–40·1) than in other regions, but was nevertheless higher than ten in the WHO African (12·6; 6·2–22·3), Eastern Mediterranean (15·6; 6·5–32·5), and South-East Asia (11·7; 4·1–27·1) regions.InterpretationGlobally, people in prison are at high risk of contracting M tuberculosis infection and developing tuberculosis, with consistent disparities between prisons and the general population across regions. Tuberculosis control programmes should prioritise preventive interventions among incarcerated populations.FundingUS National Institutes of Health.