Gezondheidseffectschatting voor Gezond Beleid

Gezondheidseffectschatting is teamsport. Spelers met gezondheidskundige en bestuurlijke functies en rollen leveren een gezamenlijke inspanning binnen een kader van spelregels, die door alle spelers worden erkend. De spelregels voor een GES bestaan uit gezondheidskundige regels, zoals validiteit en betrouwbaarheid van de effectschatting; en bestuurlijke regels, zoals haalbaarheid, nut, en aanvaardbaarheid van de beleidsalternatieven die uit de effectschatting worden afgeleid. Omdat de beleidsspelregels afhankelijk zijn van de specifieke context, worden die spelregels tijdens een GES afgesproken met betrokkenen. Daarom is GES een teamsport op ‘projectbasis’

Mononuclear cells contaminating acute lymphoblastic leukaemic samples tested for cellular drug resistance using the methyl-thiazol-tetrazolium assay.

The methyl-thiazol-tetrazolium (MTT) assay is a drug resistance assay which cannot discriminate between malignant and non-malignant cells. We previously reported that samples with > or = 80% leukaemic cells at the start of culture give similar results in the MTT assay and the differential staining cytotoxicity assay, in which a discrimination between malignant and non-malignant cells can be made. However, the percentage of leukaemic cells may change during culture, which might affect the results of the MTT assay. We studied 106 untreated childhood acute lymphoblastic leukemia (ALL) samples with > or = 80% leukaemic cells at the start of culture. This percentage decreased below 80% in 28%, and below 70% in 13%, of the samples after 4 days of culture. A decrease below 70% occurred more often in case of 80-89% leukaemic cells (9/29) than in case of > or = 90% leukaemic cells at the start of culture (5/77, P = 0.0009). Samples with < 70% leukaemic cells after culture were significantly more resistant to 6 out of 13 drugs, and showed a trend towards being more resistant to two more drugs, than samples with > or = 80% leukaemic cells. No such differences were seen between samples with 70-79% and samples with > or = 80% leukaemic cells after culture. We next studied in another 30 ALL samples whether contaminating mononuclear cells could be removed by using immunoamagnetic beads. Using a beads to target cell ratio of 10:1, the percentage of leukaemic cells increased from mean 72% (s.d. 9.3%) to mean 87% (s.d. 6.7%), with an absolute increase of 2-35%. The recovery of leukaemic cells was mean 82.1% (range 56-100%, s.d. 14.0%). The procedure itself did not influence the results of the MTT assay in three samples containing only leukaemic cells. We conclude that it is important to determine the percentage of leukaemic cells at the start and at the end of the MTT assay and similar drug resistance assays. Contaminating mononuclear cells can be successfully removed from ALL samples using immunomagnetic beads. This approach may increase the number of leukaemic samples which can be evaluated for cellular drug resistance with the MTT assay or a similar cell culture drug resistance assay

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding: Bill & Melinda Gates Foundation

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. Funding: Bill & Melinda Gates Foundation

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990�2015: a systematic analysis for the Global Burden of Disease Study 2015

Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors�the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25 over the same period. All risks jointly evaluated in 2015 accounted for 57·8 (95 CI 56·6�58·8) of global deaths and 41·2 (39·8�42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million 192·7 million to 231·1 million global DALYs), smoking (148·6 million 134·2 million to 163·1 million), high fasting plasma glucose (143·1 million 125·1 million to 163·5 million), high BMI (120·1 million 83·8 million to 158·4 million), childhood undernutrition (113·3 million 103·9 million to 123·4 million), ambient particulate matter (103·1 million 90·8 million to 115·1 million), high total cholesterol (88·7 million 74·6 million to 105·7 million), household air pollution (85·6 million 66·7 million to 106·1 million), alcohol use (85·0 million 77·2 million to 93·0 million), and diets high in sodium (83·0 million 49·3 million to 127·5 million). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Health impact assessment

Health impact assessment (HIA) seeks to predict the future consequences for health of possible decisions and, on that basis, to inform decision making. HIA takes a comprehensive approach to health. It can contribute to democratic decision making by informing decision makers and stakeholders and stimulate reflection and debate about intended or unintended health consequences of decisions. It contributes to equity by examining health effects on vulnerable subgroups in populations and to sustainable development. Given the potential for conflicts of interests and the wide diversity of methods and guidelines for HIA, ensuring the ethical use of evidence may pose challenges

Cellular drug resistance in childhood leukemia

The response to chemotherapy is determined essentially by two factors: first, pharmacokinetic factors, determining which concentration of drug reaches the malignant cells, and second, cellular drug resistance of these cells, determining how many of them will be killed by that concentration of drug. The study of cellular drug resistance has been stimulated by the development of short-term 'total cell kill' assays, such as the MTT assay, for use on patient samples. The drug resistance profiles differed markedly between ALL and ANLL, between immunophenotypic and karyotypic subgroups within ALL, and between initial and relapsed ALL. The results of the MTT assay showed a significant relation between the antileukemic activity of prednisolone in vitro and the clinical response to systemic monotherapy with that drug. At multivariate analysis including several well-known prognostic factors (WBC, age, immunophenotype) only the in vitro resistance to prednisolone, dexamethasone, l-asparaginase, and daunorubicin was significantly related to clinical outcome. At multiple regression analysis, combination of the results for prednisolone, l-asparaginase, and vincristine made it possible to distinguish between three patient groups with increasing levels of drug resistance and markedly different probabilities of 2-year disease-free survival: 100%, 83%, and 60%. These results show that in vitro drug resistance testing can give a correct prediction of prognosis, superior to that of currently used prognostic factors. Stratification of prognostic groups based on the results of drug resistance testing is feasible and should be introduced into new clinical trials. Many questions now remaining could be answered within carefully designed preclinical and clinical studies

Clinical relevance of in vitro drug resistance testing in childhood acute lymphoblastic leukemia: The state of the art

Nowadays about two‐thirds of children with acute lymphoblastic leukemia (ALL) can be cured with chemotherapy, but one‐third die from the disease. The clinical response of leukemic cells to chemotherapy is roughly due to two factors: the effective drug levels reaching the cells and the resistance of these cells to the drugs. The clinical value of cellular drug resistance in children with ALL is not known. We developed an in vitro assay to study drug resistance in these children. In this article, the main results obtained with this MTT assay on samples from 137 children with ALL are summarized: (1) patients whose cells are resistant to several drugs at initial diagnosis have a poor prognosis; (2) relapsed leukemias show a considerable drug resistance which might partly explain the poor prognosis. Relapsed cases differ in their type and degree of resistance; (3) the poor outcome of high risk groups as defined by age and immunophenotype can partly be explained by specific patterns of drug resistance; (4) P‐glycoprotein‐mediated multidrug resistance is not an important cause of resistance in childhood ALL; and (5) no relation exists between the activities of the purine enzymes HGPRT, 5′NT, ADA, and PNP and drug resistance in childhood ALL. The conclusion is that in vitro drug resistance data have clinical relevance and can be used to develop more effective and less toxic treatment strategies in childhood ALL. © 1994 Wiley‐Liss, Inc