Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Epidemiology and survival of colon cancer among Egyptians: a retrospective study

Introduction: Colorectal cancer is the 4th commonest cancer in the world. Studies had shown different tumor behavior depending on the site, pathology and stage. However the characters of Egyptian colon cancer patients are not well addressed. Method: Computerized registry of a tertiary cancer hospital in Egypt was searched for colon cancer cases. Demographic, pathologic and treatment data were collected and analyzed using SPSS program. Results: About 360 colon cancer patients attended our center in the last 12 years. Tumor characters showed great diverse from that of developed countries, with especially different prognosis and survival. Conclusion: Egyptians have unique tumor characters and behavior, and different compliance with treatment regimens. Multicenter prospective studies, as well as evolving Egyptian treatment guidelines are needed to address this. Resumo: Introdução: Câncer colorretal é a quarta neoplasia mais comum a nível mundial. Estudos demonstraram diferentes comportamentos do tumor, dependendo do local, da patologia e do estágio. Contudo, ainda não estão devidamente definidas as características dos pacientes egípcios com câncer de cólon. Métodos: Foi realizada pesquisa no registro computadorizado de um hospital terciário para pacientes com câncer, à busca de casos de câncer de cólon. Foi feita coleta de dados demográficos, patológicos e terapêuticos. Tais dados foram então submetidos à análise com o programa SPSS. Resultados: Nos últimos 12 anos, cerca de 360 pacientes portadores de câncer de cólon foram atendidos em nosso Centro. As características dos tumores demonstraram grandes diferenças em comparação com os achados de países desenvolvidos e, em especial, com relação ao prognóstico e à sobrevida. Conclusão: Os egípcios exibem características e comportamentos singulares com relação aos tumores, além de diferentes graus de cooperação com os regimes terapêuticos. Para que tais aspectos sejam sanados, há necessidade de mais estudos prospectivos multicêntricos, bem como de um aprimoramento das diretrizes terapêuticas para os egípcios. Keywords: Colon cancer, Registry, Incidence, Survival, Recurrence, Palavras-chave: Câncer de cólon, Registro, Incidência, Sobrevida, Recorrênci

Applying Ligands Profiling Using Multiple Extended Electron Distribution Based Field Templates and Feature Trees Similarity Searching in the Discovery of New Generation of Urea-Based Antineoplastic Kinase Inhibitors

<div><p>This study provides a comprehensive computational procedure for the discovery of novel urea-based antineoplastic kinase inhibitors while focusing on diversification of both chemotype and selectivity pattern. It presents a systematic structural analysis of the different binding motifs of urea-based kinase inhibitors and the corresponding configurations of the kinase enzymes. The computational model depends on simultaneous application of two protocols. The first protocol applies multiple consecutive validated virtual screening filters including SMARTS, support vector-machine model (ROC = 0.98), Bayesian model (ROC = 0.86) and structure-based pharmacophore filters based on urea-based kinase inhibitors complexes retrieved from literature. This is followed by hits profiling against different extended electron distribution (XED) based field templates representing different kinase targets. The second protocol enables cancericidal activity verification by using the algorithm of feature trees (Ftrees) similarity searching against NCI database. Being a proof-of-concept study, this combined procedure was experimentally validated by its utilization in developing a novel series of urea-based derivatives of strong anticancer activity. This new series is based on 3-benzylbenzo[d]thiazol-2(3H)-one scaffold which has interesting chemical feasibility and wide diversification capability. Antineoplastic activity of this series was assayed in vitro against NCI 60 tumor-cell lines showing very strong inhibition of GI₅₀ as low as 0.9 uM. Additionally, its mechanism was unleashed using KINEX™ protein kinase microarray-based small molecule inhibitor profiling platform and cell cycle analysis showing a peculiar selectivity pattern against Zap70, c-src, Mink1, csk and MeKK2 kinases. Interestingly, it showed activity on syk kinase confirming the recent studies finding of the high activity of diphenyl urea containing compounds against this kinase. Allover, the new series, which is based on a new kinase scaffold with interesting chemical diversification capabilities, showed that it exhibits its “emergent” properties by perturbing multiple unexplored kinase pathways.</p> </div

Classification of urea derivatives kinases complexes deposited in literature according to their families, subfamilies and groups and listing the PDB codes of each group.

<p>Classification of urea derivatives kinases complexes deposited in literature according to their families, subfamilies and groups and listing the PDB codes of each group.</p

Synthesis of target compound (13).

<p>Reagents and conditions: (a) CH₂Cl₂, r.t, overnight.</p

Heat map of twelve urea-based derivatives against a panel of 90 field templates representing urea –based kinases inhibitors complexed with their corresponding kinase enzymes as retrieved previously.

<p>The color codes used here is the red-yellow-green scale as indicative for decreasing similarity.</p

Pipeline pilot workflow used to carry out the SVM model using R statistics package.

<p>(A) Shows the usage of R-statistics node in pipeline pilot and its usage in learning the training set, after splitting, followed by giving the cross-validated ROC score via R plot viewer. (B) Shows the usage of the test set to validate the model using enrichment plot and R plot viewer.</p

Human cyclin dependent kinase 2 complexed with urea-based cdk4 kinase inhibitor (1GII):

<p>(A)The complex illustrated using the color codes that represent the different regions of the binding site: G-loop, Hyd1, alphaC, Hinge, HRD and DFG regions. The urea fragment binds to the Hinge region, (B) The corresponding field template derived from the complex. Color codes of the field template are listed in the supplementary data (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049284#pone.0049284.s002" target="_blank">Text S2</a>).</p