69 results found
Roca-Barceló A, Crabbe H, Ghosh R, et al., 2020, Temporal trends and demographic risk factors for hospital admissions due to carbon monoxide poisoning in England, Preventive Medicine, Vol: 136, ISSN: 0091-7435
Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning is a preventable cause of morbidity and mortality. Epidemiological data on UNFR CO poisoning can help monitor changes in the magnitude of this burden, particularly through comparisons of multiple countries, and to identify vulnerable sub-groups of the population which may be more at risk. Here, we collected data on age- and sex- specific number of hospital admissions with a primary diagnosis of UNFR CO poisoning in England (2002–2016), aggregated to small areas, alongside area-level characteristics (i.e. deprivation, rurality and ethnicity). We analysed temporal trends using piecewise log-linear models and compared them to analogous data obtained for Canada, France, Spain and the US. We estimated age-standardized rates per 100,000 inhabitants by area-level characteristics using the WHO standard population (2000–2025). We then fitted the Besag York Mollie (BYM) model, a Bayesian hierarchical spatial model, to assess the independent effect of each area-level characteristic on the standardized risk of hospitalization. Temporal trends showed significant decreases after 2010. Decreasing trends were also observed across all countries studied, yet France had a 5-fold higher risk. Based on 3399 UNFR CO poisoning hospitalizations, we found an increased risk in areas classified as rural (0.69, 95% CrI: 0.67; 0.80), highly deprived (1.77, 95% CrI: 1.66; 2.10) or with the largest proportion of Asian (1.15, 95% CrI: 1.03; 1.49) or Black population (1.35, 95% CrI: 1.20; 1.80). Our multivariate approach provides strong evidence for the identification of vulnerable populations which can inform prevention policies and targeted interventions.
Stromberg U, Parkes B, Holmen A, et al., Disease mapping of early- and late-stage cancer to monitor inequalities in early detection: a study of cutaneous malignant melanoma, European Journal of Epidemiology, ISSN: 0393-2990
We consider disease mapping of early- and late-stage cancer, in order to identify and monitor inequalities in early detection. Our method is demonstrated by mapping cancer incidence at high geographical resolution using data on 10,302 cutaneous malignant melanoma (CMM) cases within the 3.7 million population of South-West Sweden. The cases were geocoded into small-areas, each with a population size between 600 and 2600 and accessible socio-demographic data. Using the disease mapping application Rapid Inquiry Facility (RIF) 4.0, we produced regional maps to visualise spatial variations in stage I, II and III–IV CMM incidences, complemented by local maps to explore the variations within two urban areas. Pronounced spatial disparities in stage I CMM incidence were revealed by the regional and local maps. Stage I CMM incidence was markedly higher in wealthier small-areas, in particular within each urban area. A twofold higher stage I incidence was observed, on average, in the wealthiest small-areas (upper quintile) than in the poorest small-areas (lower quintile). We identified in the regional map of stage III–IV CMM two clusters of higher or lower than expected late-stage incidences which were quite distinct from those identified for stage I. In conclusion, our analysis of CMM incidences supported the use of this method of cancer stage incidence mapping for revealing geographical and socio-demographic disparities in cancer detection.
Oron A, Chao D, Ezeanolue E, et al., 2020, Caring for Africa’s Sickle Cell children: will we rise to the challenge?, BMC Medicine, Vol: 18, ISSN: 1741-7015
BackgroundMost of the world’s sickle cell disease (SCD) burden is in Africa, where it is a major contributor to child morbidity and mortality. Despite the low cost of many preventive SCD interventions, insufficient resources have been allocated, and progress in alleviating the SCD burden has lagged behind other public-health efforts in Africa. The recent announcement of massive new funding for research into curative SCD therapies is encouraging in the long term, but over the next few decades, it is unlikely to help Africa’s SCD children substantially.Main discussionA major barrier to progress has been the absence of large-scale early-life screening. Most SCD deaths in Africa probably occur before cases are even diagnosed. In the last few years, novel inexpensive SCD point-of-care test kits have become widely available and have been deployed successfully in African field settings. These kits could potentially enable universal early SCD screening. Other recent developments are the expansion of the pneumococcal conjugate vaccine towards near-universal coverage, and the demonstrated safety, efficacy, and increasing availability and affordability of hydroxyurea across the continent. Most elements of standard healthcare for SCD children that are already proven to work in the West, could and should now be implemented at scale in Africa. National and continental SCD research and care networks in Africa have also made substantial progress, assembling care guidelines and enabling the deployment and scale-up of SCD public-health systems. Substantial logistical, cultural, and awareness barriers remain, but with sufficient financial and political will, similar barriers have already been overcome in efforts to control other diseases in Africa.Conclusion and recommendationsDespite remaining challenges, several high-SCD-burden African countries have the political will and infrastructure for the rapid implementation and scale-up of comprehensive SCD childcare programs. A
Piel F, Implementing newborn screening for sickle cell disease as part of immunization programmes in Nigeria: a feasibility study, The Lancet Haematology, ISSN: 2352-3026
Hodgson S, Fecht D, Gulliver J, et al., 2020, Availability, access, analysis and dissemination of small area data, International Journal of Epidemiology, Vol: 49, Pages: i4-i14, ISSN: 1464-3685
In this era of ‘big data’, there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualisations, allowing small area data to be seen and understood by non-expert audiences are revolutionising public and researcher interactions with data. The UK Small Area Health Statistics Unit’s Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and ‘mash-ups’, and user generated inputs from social media, mobile devices, and wearable tech are new data streams which will find utility in future studies, and bring novel dimensions with respect to ethical use of small area data.
Piel FB, Cockings S, 2020, Using large and complex datasets for small-area environment-health studies: from theory to practice, International Journal of Epidemiology, Vol: 49, Pages: i1-i3, ISSN: 0300-5771
Fecht D, Piel F, Cockings S, et al., 2020, Advances in mapping population and demographic characteristics at small area levels, International Journal of Epidemiology, Vol: 49, Pages: i15-i25, ISSN: 1464-3685
Temporally and spatially highly resolved information on population characteristics, including demographic profile (e.g. age and sex), ethnicity and socio-economic status (e.g. income, occupation, education), are essential for observational health studies at the small-area level. Time-relevant population data are critical as denominators for health statistics, analytics and epidemiology, to calculate rates or risks of disease. Demographic and socio-economic characteristics are key determinants of health and important confounders in the relationship of environmental contaminants and health. In many countries, census data have long been the source of small-area population denominators and confounder information. A strength of the traditional census model has been its careful design and high level of population coverage, allowing high-quality detailed data to be released for small areas periodically, e.g. every ten years. The timeliness of data, however, becomes a challenge when temporally and spatially highly accurate annual (or even more frequent) data at high spatial resolution 31are needed, for example, for health surveillance and epidemiological studies. Additionally, the approach to collecting demographic population information is changing in the era of openand big data and may eventually evolve to using combinations of administrative and other data, supplemented by surveys. We discuss different approaches to address these challenges including a) the U. S. American Community Survey, a rolling sample of the U.S. population census, b) the use of spatial analysis techniques to compile temporally and spatially high-resolution demographic data, and c) the use of administrative and big data sources as proxies for demographic characteristics.
Blangiardo M, Boulieri A, Diggle P, et al., 2020, Advances in spatio-temporal models for non-communicable disease surveillance, International Journal of Epidemiology, Vol: 49, Pages: i26-i37, ISSN: 1464-3685
Surveillance systems are commonly used to provide early warning detection or to assess an impact of an intervention/policy. Traditionally, the methodological and conceptual frameworks for surveillance have been designed for infectious diseases, but the rising burden of non-communicable diseases (NCDs) worldwide suggests a pressing need for surveillance strategies to detect unusual patterns in the data and to help unveil important risk factors in this setting. Surveillance methods need to be able to detect meaningful departures from expectation and exploit dependencies within such data to produce unbiased estimates of risk as well as future forecasts. This has led to the increasing development of a range of space-time methods specifically designed for NCD surveillance.We present an overview of recent advances in spatio-temporal disease surveillance for NCDs using hierarchically specified models. This provides a coherent framework for modelling complex data structures, dealing with data sparsity, exploiting dependencies between data sources and propagating the inherent uncertainties present in both the data and the modelling process. We then focus on three commonly used models within the Bayesian Hierarchical Model (BHM) framework and through a simulation study we compare their performance.We also discuss some challenges faced by researchers when dealing with NCD surveillance, including how to account for false detection and the modifiable areal unit problem. Finally, we consider how to use and interpret the complex models, how model selection may vary depending on the intended user group and how best to communicate results to stakeholders and the general public.
Piel F, Fecht D, Hodgson S, et al., 2020, Small-area methods for investigation of environment and health, International Journal of Epidemiology, Vol: 49, Pages: 686-699, ISSN: 1464-3685
Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographic scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast growing computational capabilities permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered, and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.
Piel FB, Parkes B, Hambly P, et al., 2020, Software application profile: the Rapid Inquiry Facility 4.0: an open access tool for environmental public health tracking, International Journal of Epidemiology, Vol: 49, Pages: i38-i48, ISSN: 0300-5771
The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters and potential environmental hazards, whether localized (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear power plants.
Nnodu O, Isa H, Nwegbu M, et al., 2019, HemoTypeSC, a low-cost point-of-care testing device for sickle cell disease: promises and challenges, Blood Cells, Molecules, and Diseases, Vol: 78, Pages: 22-28, ISSN: 1079-9796
BackgroundSickle cell disease (SCD) is a neglected burden of growing importance. >312,000 births are affected annually by sickle cell anaemia (SCA). Early interventions such as newborn screening, penicillin prophylaxis and hydroxyurea can substantially reduce the mortality and morbidity associated with SCD. Nevertheless, their implementation in African countries has been mostly limited to pilot projects. Recent development of low-cost point-of-care testing (POCT) devices for sickle haemoglobin (HbS) could greatly facilitate the diagnosis of those affected.MethodsWe conducted the first multi-centre, real-world assessment of a low-cost POCT device, HemoTypeSC, in a low-income country. Between September and November 2017, we screened 1121 babies using both HemoTypeSC and HPLC and confirmed discordant samples by molecular diagnosis.FindingsWe found that, in optimal field conditions, the sensitivity and specificity of the test for SCA were 93.4% and 99.9%, respectively. All 14 carriers of haemoglobin C were successfully identified. Our study reveals an overall accuracy of 99.1%, but also highlights the importance of rigorous data collection, staff training and accurate confirmatory testing. It suggests that HPLC results might not be as reliable in a resource-poor setting as usually considered.InterpretationThe use of such a POCT device can be scaled up and routinely used across multiple healthcare centres in sub-Saharan Africa, which would offer great potential for the identification and management of vast numbers of individuals affected by SCD who are currently undiagnosed.
Hockham C, Gupta S, Penman B, et al., 2019, Estimating the burden of α-thalassaemia in Thailand using a comprehensive prevalence database for Southeast Asia, eLife, Vol: 8, ISSN: 2050-084X
Severe forms of α-thalassaemia, haemoglobin H disease and haemoglobin Bart’s hydrops fetalis, are an important public health concern in Southeast Asia. Yet information on the prevalence, genetic diversity and health burden of α-thalassaemia in the region remains limited. We compiled a geodatabase of α-thalassaemia prevalence and genetic diversity surveys and, using geostatistical modelling methods, generated the first continuous maps of α-thalassaemia mutations in Thailand and sub-national estimates of the number of newborns with severe forms in 2020. We also summarised the current evidence-base for α-thalassaemia prevalence and diversity for the region. We estimate that 3595 (95% credible interval 1,717–6,199) newborns will be born with severe α-thalassaemia in Thailand in 2020, which is considerably higher than previous estimates. Accurate, fine-scale epidemiological data are necessary to guide sustainable national and regional health policies for α-thalassaemia management. Our maps and newborn estimates are an important first step towards this aim.
De Franceschi L, Lux C, Piel FB, et al., 2019, Access to emergency department of acute events and identification of sickle cell disease in refugees, Blood, Vol: 133, Pages: 2100-2103, ISSN: 1528-0020
Piel F, Parkes B, Hambly P, et al., The Rapid Inquiry Facility 4.0: an open access tool for Environmental Public Health Tracking, International Journal of Epidemiology, ISSN: 1464-3685
The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters, and potential environmental hazards, whether localised (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing, and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear powerplants.
Hockham C, Bhatt S, Colah R, et al., 2018, The spatial epidemiology of sickle-cell anaemia in India, Scientific Reports, Vol: 8, ISSN: 2045-2322
Sickle-cell anaemia (SCA) is a neglected chronic disorder of increasing global health importance, with India estimated to have the second highest burden of the disease. In the country, SCA is particularly prevalent in scheduled populations, which comprise the most socioeconomically disadvantaged communities. We compiled a geodatabase of a substantial number of SCA surveys carried out in India over the last decade. Using generalised additive models and bootstrapping methods, we generated the first India-specific model-based map of sickle-cell allele frequency which accounts for the district-level distribution of scheduled and non-scheduled populations. Where possible, we derived state- and district-level estimates of the number of SCA newborns in 2020 in the two groups. Through the inclusion of an additional 158 data points and 1.3 million individuals, we considerably increased the amount of data in our mapping evidence-base compared to previous studies. Highest predicted frequencies of up to 10% spanned central India, whilst a hotspot of ~12% was observed in Jammu and Kashmir. Evidence was heavily biased towards scheduled populations and remained limited for non-scheduled populations, which can lead to considerable uncertainties in newborn estimates at national and state level. This has important implications for health policy and planning. By taking population composition into account, we have generated maps and estimates that better reflect the complex epidemiology of SCA in India and in turn provide more reliable estimates of its burden in the vast country. This work was supported by European Union’s Seventh Framework Programme (FP7//2007–2013)/European Research Council [268904 – DIVERSITY]; and the Newton-Bhabha Fund [227756052 to CH]
Piel FBJ, Brandon P, Hima D, et al., 2018, The challenge of opt-outs from NHS data: a small-area perspective, Journal of Public Health, Vol: 40, Pages: e594-e600, ISSN: 1741-3842
Roth GA, Abate D, Abate KH, et al., 2018, Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017, The Lancet, Vol: 392, Pages: 1736-1788, ISSN: 0140-6736
BackgroundGlobal development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017.MethodsThe causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries—Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised.FindingsAt the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest f
Lobitz S, Telfer P, Cela E, et al., 2018, Newborn screening for sickle cell disease in Europe: recommendations from a Pan‐European Consensus Conference, British Journal of Haematology, Vol: 183, Pages: 648-660, ISSN: 1365-2141
Sickle Cell Disease (SCD) is an increasing global health problem and presents significant challenges to European health care systems. Newborn screening (NBS) for SCD enables early initiation of preventive measures and has contributed to a reduction in childhood mortality from SCD. Policies and methodologies for NBS vary in different countries, and this might have consequences for the quality of care and clinical outcomes for SCD across Europe. A two-day Pan-European consensus conference was held in Berlin in April 2017 in order to appraise the current status of NBS for SCD and to develop consensus-based statements on indications and methodology for NBS for SCD in Europe. More than 50 SCD experts from 13 European countries participated in the conference. The aim of this paper is to summarise the discussions and present consensus recommendations which can be used to support development of NBS programmes in European countries where they do not yet exist, and to review existing programmes.
Hockham C, Ekwattanakit S, Bhatt S, et al., 2018, Estimating the burden of α-thalassaemia in Thailand using a comprehensive prevalence database for Southeast Asia, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>Severe forms of α-thalassaemia, haemoglobin H disease and haemoglobin Bart’s hydrops fetalis, are an important public health concern in Southeast Asia. Yet information on the prevalence, genetic diversity and health burden of α-thalassaemia in the region remains limited. We compiled a geodatabase of α-thalassaemia prevalence and genetic diversity surveys and, using geostatistical modelling methods, generated the first continuous maps of α-thalassaemia mutations in Thailand and sub-national estimates of the number of newborns with severe forms in 2020. We also summarised the current evidence-base for α-thalassaemia prevalence and diversity for the region. We estimate that 3,595 (95% credible interval 1,717 – 6,199) newborns will be born with severe α-thalassaemia in Thailand in 2020, which is considerably higher than previous estimates. Accurate, fine-scale epidemiological data are necessary to guide sustainable national and regional health policies for α-thalassaemia control. Our maps and newborn estimates are an important first step towards this aim.</jats:p><jats:sec><jats:title>Funding</jats:title><jats:p>This work was supported by European Union’s Seventh Framework Programme (FP7//2007-2013)/European Research Council [268904 – DIVERSITY]</jats:p></jats:sec>
GBD 2016 Healthcare Access and Quality Collaborators, 2018, Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016, Lancet, Vol: 391, Pages: 2236-2271, ISSN: 0140-6736
BACKGROUND: A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. METHODS: Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derive
Gregory K, Piel FBJ, Elliott V, 2018, Sickle cell disease, Nature Reviews Disease Primers, Vol: 4, ISSN: 2056-676X
Sickle cell disease (SCD) is a group of inherited disorders caused by mutations in HBB, which encodes haemoglobin subunit β. The incidence is estimated to be between 300,000 and 400,000 neonates globally each year, the majority in sub-Saharan Africa. Haemoglobin molecules that include mutant sickle β-globin subunits can polymerize; erythrocytes that contain mostly haemoglobin polymers assume a sickled form and are prone to haemolysis. Other pathophysiological mechanisms that contribute to the SCD phenotype are vaso-occlusion and activation of the immune system. SCD is characterized by a remarkable phenotypic complexity. Common acute complications are acute pain events, acute chest syndrome and stroke; chronic complications (including chronic kidney disease) can damage all organs. Hydroxycarbamide, blood transfusions and haematopoietic stem cell transplantation can reduce the severity of the disease. Early diagnosis is crucial to improve survival, and universal newborn screening programmes have been implemented in some countries but are challenging in low-income, high-burden settings.
Piel FBJ, Williams TN, 2017, Subphenotypes of sickle cell disease in Africa, Blood, Vol: 130, Pages: 2157-2158, ISSN: 1528-0020
Piel FBJ, Rigano P, De Francesci L, et al., 2017, Real-life experience with hydroxyurea in sickle cell disease: A multicenter study in a cohort of patients with heterogeneous descent, Blood Cells, Molecules and Diseases, Vol: 69, Pages: 82-89, ISSN: 1079-9796
We conducted the first nation-wide cohort study of sickle cell disease (SCD) in Italy, a Southern European country exposed to intense recent flux migration from endemic areas for SCD. We evaluate the impact of hydroxyurea on a total of 652 pediatric and adult patients from 33 Reference Centers for SCD (mean age 24.5 ± 15 years, 51.4% males). Hydroxyurea median treatment duration was 7 years (range: < 1 year to 29 years) at a mean therapeutic dose of 18 ± 4.7 mg/kg/day. Hydroxyurea was associated with a significant increase in mean total and fetal hemoglobin and a significant decrease in mean hemoglobin S, white blood and platelet counts, and lactate dehydrogenase levels. Hydroxyurea was associated with a significant reduction in the incidence of acute chest syndrome (− 29.3%, p < 0.001), vaso-occlusive crisis (− 34.1%, p < 0.001), hospitalization (− 53.2%, p < 0.001), and bone necrosis (− 6.9%, p < 0.001). New silent cerebral infarction (SCI) occurred during treatment (+ 42.4%, p < 0.001) but not stroke (+ 0.5%, p = 0.572). These observations were generally consistent upon stratification for age, descent (Caucasian or African), genotype (βS/βS, βS/β0 or βS/β+) and duration of treatment (< or ≥ 10 years). There were no new safety concerns observed compared to those commonly reported in the literature. Our study, conducted on a large population of patients with different descent and compound state supports the benefits of hydroxyurea therapy as a treatment option. Registered at clinical trials.gov (NCT02709681).
Wang H, Abajobir A, Abate KH, et al., 2017, Global, regional, and national under-5 mortality, adultmortality, age-specific mortality, and life expectancy,1970–2016: a systematic analysis for the Global Burden ofDisease Study 2016, The Lancet, Vol: 390, Pages: 1084-1150, ISSN: 0140-6736
BackgroundDetailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016.MethodsWe have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15–60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to
Piel FB, Steinberg MH, Rees DC, 2017, Sickle Cell Disease., N Engl J Med, Vol: 377, Pages: 305-305
Piel FB, Steinberg M, Rees D, 2017, Sickle Cell Disease (Reply Letter), New England Journal of Medicine, Vol: 377, Pages: 302-303, ISSN: 0028-4793
Piel FBJ, Steinberg MH, Rees DC, 2017, Sickle cell disease, New England Journal of Medicine, Vol: 376, Pages: 1561-1573, ISSN: 0028-4793
Sickle cell disease is an increasing global health problem. Estimates suggest that every year approximately 300,000 infants are born with sickle cell anemia, which is defined as homozygosity for the sickle hemoglobin (HbS) gene (i.e., for a missense mutation [Glu6Val, rs334] in the β-globin gene [HBB]) and that this number could rise to 400,000 by 2050.1 Although early diagnosis, penicillin prophylaxis, blood transfusion, transcranial Doppler imaging, hydroxyurea, and hematopoietic stem-cell transplantation can dramatically improve survival and quality of life for patients with sickle cell disease, our understanding of the role of genetic and nongenetic factors in explaining the remarkable phenotypic diversity of this mendelian disease is still limited. Better prediction of the severity of sickle cell disease could lead to more precise treatment and management. Beyond well-known modifiers of disease severity, such as fetal hemoglobin (HbF) levels and α-thalassemia, other genetic variants might affect specific subphenotypes. Similarly, although the influence of altitude and temperature has long been reflected in advice to patients with sickle cell disease, recent studies of nongenetic factors, including climate and air quality, suggest more complex associations between environmental factors and clinical complications.2 New treatments and management strategies accounting for these genetic and nongenetic factors could substantially and rapidly improve the quality of life and reduce health care costs for patients with sickle cell disease.
Piel FB, Tewari S, Brousse V, et al., 2017, Associations between environmental factors and hospital admissions for sickle cell disease, Haematologica, Vol: 102, Pages: 666-675, ISSN: 0390-6078
Sickle cell disease is an increasing global health burden. This inherited disease is characterized by a remarkable phenotypic heterogeneity, which can only partly be explained by genetic factors. Environmental factors are likely to play an important role but studies of their impact on disease severity are limited and their results are often inconsistent. This study investigated associations between a range of environmental factors and hospital admissions of young patients with sickle cell disease in London and in Paris between 2008 and 2012. Specific analyses were conducted for subgroups of patients with different genotypes and for the main reasons for admissions. Generalized additive models and distributed lag non-linear models were used to assess the magnitude of the associations and to calculate relative risks. Some environmental factors significantly influence the numbers of hospital admissions of children with sickle cell disease, although the associations identified are complicated. Our study suggests that meteorological factors are more likely to be associated with hospital admissions for sickle cell disease than air pollutants. It confirms previous reports of risks associated with wind speed (risk ratio: 1.06/stan-dard deviation; 95% confidence interval: 1.00-1.12) and also with rainfall (1.06/standard deviation; 95% confidence interval: 1.01-1.12). Maximum atmospheric pressure was found to be a protective factor (0.93/standard deviation; 95% confidence interval: 0.88-0.99). Weak or no associations were found with temperature. Divergent associations were identified for different genotypes or reasons for admissions, which could partly explain the lack of consistency in earlier studies. Advice to patients with sickle cell disease usually includes avoiding a range of environmental conditions that are believed to trigger acute complications, including extreme temperatures and high altitudes. Scientific evidence to support such advice is limited and sometimes con
Premawardhena A, Allen A, Piel FBJ, et al., 2016, The evolutionary and clinical implilcations of the uneven distribution of the frequency of the inherited haemoglobin variants over short geographical distances, British Journal of Haematology, Vol: 176, Pages: 475-484, ISSN: 1365-2141
Studies of the frequency of heterozygous carriers for common inheriteddiseases of haemoglobin in over 7500 adolescent children in 25 districts inSri Lanka have disclosed a highly significant variation over very short geo-graphical distances. A further analysis of these findings, including theirrelationship to the past frequency and distribution of malaria, climatic vari-ation, altitude, ethnic origin and consanguinity rates, have provided evi-dence regarding the evolutionary basis for the variable distribution of theseconditions over short distances. It is likely that the complex interplaybetween malaria and the environment, together with related ethnic andsocial issues, exists in many countries across the tropical belt. Hence, theseobservations emphasise the importance of micromapping heterozygote dis-tributions in high-frequency countries in order to define their true burdenand the facilities required for the prevention and management of thehomozygous and compound heterozygous disorders that result from theirinteraction.
Wang H, Naghavi M, Allen C, et al., 2016, Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015, Lancet, Vol: 388, Pages: 1459-1544, ISSN: 0140-6736
BackgroundImproving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.MethodsWe estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GB
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