260 research outputs found
Effect of Age at Diagnosis on Cervical Cancer Patient Prognoses in Georgia
The current incidence of cervical cancer varies around 17.0/100,000 women per year. The study aims to describe the effect of age at diagnosis on CC patient prognosis in Georgia. Methods. Univariable and Multivariable survival analysis using Coxâs regression model was constructed. All women aged â€80 years, diagnosed with invasive CC (ICD10-site code C53) from 2015 to 2019,  were eligible for inclusion in the analysis. During analysis a hazard (mortality) ratio for the patients, who were diagnosed at different ages was estimated. Survival period was determined from the date of diagnosis until the date of death or the date of last follow up visit. High risk of death was defined as a mortality of CC patients whose survival period was less than 5 years.The level of statistical significance of the study findings is estimated by using p-value andthe 95% of confidence interval (95%CI). A p value < 0.05 was considered as statistically significant. In estimation of hazard ratio, the patients under 41 years were selected as a reference group. Data was analyzed using Statistical Package of SPSS version 23. Results.Totally 1646 CC patients were enrolled in the study. The median age at diagnosis was 54years and age range was 25 - 80 years. Univariable statistical analysis has revealed that cancer diagnosed over 60 years of age had a higher death hazard (HR=1.80, p<0.001), compared to cancer detected under 60 years (HR=3.30, p<0.001). Multivariable statistical analysis has detected that stage and age at diagnosis are independent, statistically significant predictors for high mortality in patients diagnosed with cervical cancer, while the role of histological grade has not been revealed. In addition, older age generally is related to a high prevalence of comorbidities. The reasons for the unfavourable cervical cancer prognosis in older patients that was detected during statistical analysis might be explained by tumor stage at diagnoses and with higher ratesof comorbidity among the elderly. Conclusions: Finally, our study results are in concordance with numerous studies, which confirm that the age of patients at the moment of diagnosis is an independent predictor for cervical cancer early mortality
Sensitivity analyses of a precerebellar neuron model predict a morphologic mechanism for plasticity of neuronal function
Massive migration from the steppe is a source for Indo-European languages in Europe
We generated genome-wide data from 69 Europeans who lived between 8,000-3,000
years ago by enriching ancient DNA libraries for a target set of almost four
hundred thousand polymorphisms. Enrichment of these positions decreases the
sequencing required for genome-wide ancient DNA analysis by a median of around
250-fold, allowing us to study an order of magnitude more individuals than
previous studies and to obtain new insights about the past. We show that the
populations of western and far eastern Europe followed opposite trajectories
between 8,000-5,000 years ago. At the beginning of the Neolithic period in
Europe, ~8,000-7,000 years ago, closely related groups of early farmers
appeared in Germany, Hungary, and Spain, different from indigenous
hunter-gatherers, whereas Russia was inhabited by a distinctive population of
hunter-gatherers with high affinity to a ~24,000 year old Siberian6 . By
~6,000-5,000 years ago, a resurgence of hunter-gatherer ancestry had occurred
throughout much of Europe, but in Russia, the Yamnaya steppe herders of this
time were descended not only from the preceding eastern European
hunter-gatherers, but from a population of Near Eastern ancestry. Western and
Eastern Europe came into contact ~4,500 years ago, as the Late Neolithic Corded
Ware people from Germany traced ~3/4 of their ancestry to the Yamnaya,
documenting a massive migration into the heartland of Europe from its eastern
periphery. This steppe ancestry persisted in all sampled central Europeans
until at least ~3,000 years ago, and is ubiquitous in present-day Europeans.
These results provide support for the theory of a steppe origin of at least
some of the Indo-European languages of Europe
Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995â2050
© 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categoriesâgovernment, out-of-pocket, and prepaid private health spendingâand estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89â4·12) annually, although it grew slower in per capita terms (2·72% [2·61â2·84]) and increased by less than 8·0 trillion (7·8â8·1) in 2016 (comprising 8·6% [8·4â8·7] of the global economy and 5252 (5184â5319) in high-income countries, 81 (74â89) in lower-middle-income countries, and 9·5 billion, 24·3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH (15·0 trillion (14·0â16·0) by 2050 (reaching 9·4% [7·6â11·3] of the global economy and $21·3 trillion [19·8â23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1·84% (1·68â2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0·6% (0·6â0·7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130·2 (122·9â136·9) in 2016 and is projected to remain at similar levels in 2050 (125·9 [113·7â138·1]). The decomposition analysis identified governmentsâ increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation: Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets. Funding: Bill & Melinda Gates Foundation
Variation in the COVID-19 infection-fatality ratio by age, time, and geography during the pre-vaccine era: a systematic analysis
Background The infection-fatality ratio (IFR) is a metric that quantifies the likelihood of an individual dying once infected with a pathogen. Understanding the determinants of IFR variation for COVID-19, the disease caused by the SARS-CoV-2 virus, has direct implications for mitigation efforts with respect to clinical practice, non-pharmaceutical interventions, and the prioritisation of risk groups for targeted vaccine delivery. The IFR is also a crucial parameter in COVID-19 dynamic transmission models, providing a way to convert a population's mortality rate into an estimate of infections.Methods We estimated age-specific and all-age IFR by matching seroprevalence surveys to total COVID-19 mortality rates in a population. The term total COVID-19 mortality refers to an estimate of the total number of deaths directly attributable to COVID-19. After applying exclusion criteria to 5131 seroprevalence surveys, the IFR analyses were informed by 2073 all-age surveys and 718 age-specific surveys (3012 age-specific observations). When seroprevalence was reported by age group, we split total COVID-19 mortality into corresponding age groups using a Bayesian hierarchical model to characterise the non-linear age pattern of reported deaths for a given location. To remove the impact of vaccines on the estimated IFR age pattern, we excluded age-specific observations of seroprevalence and deaths that occurred after vaccines were introduced in a location. We estimated age-specific IFR with a non-linear meta-regression and used the resulting age pattern to standardise all-age IFR observations to the global age distribution. All IFR observations were adjusted for baseline and waning antibody-test sensitivity. We then modelled age-standardised IFR as a function of time, geography, and an ensemble of 100 of the top-performing covariate sets. The covariates included seven clinical predictors (eg, age-standardised obesity prevalence) and two measures of health system performance. Final estimates for 190 countries and territories, as well as subnational locations in 11 countries and territories, were obtained by predicting age-standardised IFR conditional on covariates and reversing the age standardisation.Findings We report IFR estimates for April 15, 2020, to January 1, 2021, the period before the introduction of vaccines and widespread evolution of variants. We found substantial heterogeneity in the IFR by age, location, and time. Age-specific IFR estimates form a J shape, with the lowest IFR occurring at age 7 years (0-0023%, 95% uncertainty interval [UI] 0-0015-0-0039) and increasing exponentially through ages 30 years (0-0573%, 0-0418-0-0870), 60 years (1-0035%, 0-7002-1-5727), and 90 years (20-3292%, 14-6888-28-9754). The countries with the highest IFR on July 15, 2020, were Portugal (2-085%, 0-946-4-395), Monaco (1-778%, 1-265-2-915), Japan (1-750%, 1-302-2-690), Spain (1-710%, 0-991-2-718), and Greece (1-637%, 1-155-2-678). All-age IFR varied by a factor of more than 30 among 190 countries and territories.After age standardisation, the countries with the highest IFR on July 15, 2020, were Peru (0-911%, 0-636-1-538), Portugal (0-850%, 0-386-1-793), Oman (0-762%, 0-381-1-399), Spain (0-751%, 0-435-1-193), and Mexico (0-717%, 0-426-1-404). Subnational locations with high IFRs also included hotspots in the UK and southern and eastern states of the USA. Sub-Saharan African countries and Asian countries generally had the lowest all-age and age-standardised IFRs. Population age structure accounted for 74% of logit-scale variation in IFRs estimated for 39 in-sample countries on July 15, 2020. A post-hoc analysis showed that high rates of transmission in the care home population might account for higher IFRs in some locations. Among all countries and territories, we found that the median IFR decreased from 0-466% (interquartile range 0-223-0-840) to 0-314% (0-143-0-551) between April 15, 2020, and Jan 1, 2021.Interpretation Estimating the IFR for global populations helps to identify relative vulnerabilities to COVID-19. Information about how IFR varies by age, time, and location informs clinical practice and non-pharmaceutical interventions like physical distancing measures, and underpins vaccine risk stratification. IFR and mortality risk form a J shape with respect to age, which previous research, such as that by Glynn and Moss in 2020, has identified to be a common pattern among infectious diseases. Understanding the experience of a population with COVID-19 mortality requires consideration for local factors; IFRs varied by a factor of more than 30 among 190 countries and territories in this analysis. In particular, the presence of elevated age-standardised IFRs in countries with well resourced health-care systems indicates that factors beyond health-care capacity are important. Potential extenuating circumstances include outbreaks among care home residents, variable burdens of severe cases, and the population prevalence of comorbid conditions that increase the severity of COVID-19 disease. During the pre-vaccine period, the estimated 33% decrease in median IFR over 8 months suggests that treatment for COVID-19 has improved over time. Estimating IFR for the pre-vaccine era provides an important baseline for describing the progression of COVID-19 mortality patterns.Funding Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license
Promoting E2F1-mediated apoptosis in oestrogen receptor-α-negative breast cancer cells
Past, present, and future of global health financing : a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995-2050
Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4.00% (95% uncertainty interval 3.89-4.12) annually, although it grew slower in per capita terms (2.72% [2.61-2.84]) and increased by less than 8.0 trillion (7.8-8.1) in 2016 (comprising 8.6% [8.4-8.7] of the global economy and 5252 (5184-5319) in high-income countries, 81 (74-89) in lower-middle-income countries, and 9.5 billion, 24.3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6.27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ( 15.0 trillion (14.0-16.0) by 2050 (reaching 9.4% [7.6-11.3] of the global economy and $ 21.3 trillion [19.8-23.1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1.84% (1.68-2.02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0.6% (0.6-0.7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15.7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130.2 (122.9-136.9) in 2016 and is projected to remain at similar levels in 2050 (125.9 [113.7-138.1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.Peer reviewe
Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995â2050
Background: Comprehensive and comparable estimates of health spending in each country are a key input for health
policy and planning, and are necessary to support the achievement of national and international health goals. Previous
studies have tracked past and projected future health spending until 2040 and shown that, with economic development,
countries tend to spend more on health per capita, with a decreasing share of spending from development assistance
and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending,
with an emphasis on equity in spending across countries.
Methods: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three
categoriesâgovernment, out-of-pocket, and prepaid private health spendingâand estimated development assistance
for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear
mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050
and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and
revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data
were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private,
and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power
parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition
methods to assess a set of factors associated with changes in government health spending between 1995 and 2016
and to examine evidence to support the theory of the health financing transition. We projected two alternative future
scenarios based on higher government health spending to assess the potential ability of governments to generate
more resources for health.
Findings: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89â4·12)
annually, although it grew slower in per capita terms (2·72% [2·61â2·84]) and increased by less than 8·0 trillion (7·8â8·1) in 2016 (comprising 8·6% [8·4â8·7] of the global economy and 5252 (5184â5319) in high-income
countries, 81 (74â89) in lower-middle-income countries, and
9·5 billion, 24·3% of total DAH), although spending on other infectious diseases
(excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH
were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation).
For the first time, we included estimates of Chinaâs contribution to DAH (15·0 trillion (14·0â16·0) by 2050 (reaching 9·4% [7·6â11·3] of the global
economy and $21·3 trillion [19·8â23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of
1·84% (1·68â2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate
that 0·6% (0·6â0·7) of health spending will occur in currently low-income countries, despite these countries
comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in
high-income and low-income countries was 130·2 (122·9â136·9) in 2016 and is projected to remain at similar levels
in 2050 (125·9 [113·7â138·1]). The decomposition analysis identified governmentsâ increased prioritisation of the
health sector and economic development as the strongest factors associated with increases in government health
spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the
health sector and increased government spending, health spending per capita could more than double, with greater
impacts in countries that currently have the lowest levels of government health spending
Interpretation: Financing for global health has increased steadily over the past two decades and is projected to continue
increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health
spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income
countries. Many low-income countries are expected to remain dependent on development assistance, although with
greater government spending, larger investments in health are feasible. In the absence of sustained new investments
in health, increasing efficiency in health spending is essential to meet global health targets.
Funding: Bill & Melinda Gates Foundatio
BUILDING BRIDGES FOR INNOVATION IN AGEING : SYNERGIES BETWEEN ACTION GROUPS OF THE EIP ON AHA
The Strategic Implementation Plan of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) proposed six Action Groups. After almost three years of activity, many achievements have been obtained through commitments or collaborative work of the Action Groups. However, they have often worked in silos and, consequently, synergies between Action Groups have been proposed to strengthen the triple win of the EIP on AHA. The paper presents the methodology and current status of the Task Force on EIP on AHA synergies. Synergies are in line with the Action Groups' new Renovated Action Plan (2016-2018) to ensure that their future objectives are coherent and fully connected. The outcomes and impact of synergies are using the Monitoring and Assessment Framework for the EIP on AHA (MAFEIP). Eight proposals for synergies have been approved by the Task Force: Five cross-cutting synergies which can be used for all current and future synergies as they consider overarching domains (appropriate polypharmacy, citizen empowerment, teaching and coaching on AHA, deployment of synergies to EU regions, Responsible Research and Innovation), and three cross-cutting synergies focussing on current Action Group activities (falls, frailty, integrated care and chronic respiratory diseases).Peer reviewe
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