BACKGROUND:There is considerable scientific interest in associations between protracted low-dose exposure to ionizing radiation and the occurrence of specific types of cancer.
METHODS:Associations ...between ionizing radiation and site-specific solid cancer mortality were examined among 308,297 nuclear workers employed in France, the United Kingdom, and the United States. Workers were monitored for external radiation exposure and follow-up encompassed 8.2 million person-years. Radiation–mortality associations were estimated using a maximum-likelihood method and using a Markov chain Monte Carlo method, the latter used to fit a hierarchical regression model to stabilize estimates of association.
RESULTS:The analysis included 17,957 deaths attributable to solid cancer, the most common being lung, prostate, and colon cancer. Using a maximum-likelihood method to quantify associations between radiation dose- and site-specific cancer, we obtained positive point estimates for oral, esophagus, stomach, colon, rectum, pancreas, peritoneum, larynx, lung, pleura, bone and connective tissue, skin, ovary, testis, and thyroid cancer; in addition, we obtained negative point estimates for cancer of the liver and gallbladder, prostate, bladder, kidney, and brain. Most of these estimated coefficients exhibited substantial imprecision. Employing a hierarchical model for stabilization had little impact on the estimated associations for the most commonly observed outcomes, but for less frequent cancer types, the stabilized estimates tended to take less extreme values and have greater precision than estimates obtained without such stabilization.
CONCLUSIONS:The results provide further evidence regarding associations between low-dose radiation exposure and cancer.
Infections worsen survival in cirrhosis; however, simple predictors of survival in infection‐related acute‐on‐chronic liver failure (I‐ACLF) derived from multicenter studies are required in order to ...improve prognostication and resource allocation. Using the North American Consortium for Study of End‐stage Liver Disease (NACSELD) database, data from 18 centers were collected for survival analysis of prospectively enrolled cirrhosis patients hospitalized with an infection. We defined organ failures as 1) shock, 2) grade III/IV hepatic encephalopathy (HE), 3) need for dialysis and mechanical ventilation. Determinants of survival with these organ failures were analyzed. In all, 507 patients were included (55 years, 52% hepatitis C virus HCV, 15.8% nosocomial infection, 96% Child score ≥7) and 30‐day evaluations were available in 453 patients. Urinary tract infection (UTI) (28.5%), and spontaneous bacterial peritonitis (SBP) (22.5%) were the most prevalent infections. During hospitalization, 55.7% developed HE, 17.6% shock, 15.1% required renal replacement, and 15.8% needed ventilation; 23% died within 30 days and 21.6% developed second infections. Admitted patients developed none (38.4%), one (37.3%), two (10.4%), three (10%), or four (4%) organ failures. The 30‐day survival worsened with a higher number of extrahepatic organ failures, none (92%), one (72.6%), two (51.3%), three (36%), and all four (23%). I‐ACLF was defined as ≥2 organ failures given the significant change in survival probability associated at this cutoff. Baseline independent predictors for development of ACLF were nosocomial infections, Model for Endstage Liver Disease (MELD) score, low mean arterial pressure (MAP), and non‐SBP infections. Independent predictors of poor 30‐day survival were I‐ACLF, second infections, and admission values of high MELD, low MAP, high white blood count, and low albumin. Conclusion: Using multicenter study data in hospitalized decompensated infected cirrhosis patients, I‐ACLF defined by the presence of two or more organ failures using simple definitions is predictive of poor survival. (Hepatology 2014;60:250–256)
The registration data of local cancer registries in 2014 were collected by National Central Cancer Registry (NCCR)in 2017 to estimate the cancer incidence and mortality in China.
The data submitted ...from 449 registries were checked and evaluated, and the data of 339 registries out of them were qualified and selected for the final analysis. Cancer incidence and mortality were stratified by area, gender, age group and cancer type, and combined with the population data of 2014 to estimate cancer incidence and mortality in China. The age composition of standard population of Chinese census in 2000 and Segi's population were used for age-standardized incidence and mortality in China and worldwide, respectively.
Total covered population of 339 cancer registries (129 in urban and 210 in rural) in 2014 were 288 243 347 (144 061 915 in urban and 144 181 432 in rural areas). The mortality verified cases (MV%) were 68.01%. Among them, 2.19% cases were identified through death certifications only (DCO%), and the mortality
Summary Background Information about the distribution of causes of and time trends for child mortality should be periodically updated. We report the latest estimates of causes of child mortality in ...2010 with time trends since 2000. Methods Updated total numbers of deaths in children aged 0–27 days and 1–59 months were applied to the corresponding country-specific distribution of deaths by cause. We did the following to derive the number of deaths in children aged 1–59 months: we used vital registration data for countries with an adequate vital registration system; we applied a multinomial logistic regression model to vital registration data for low-mortality countries without adequate vital registration; we used a similar multinomial logistic regression with verbal autopsy data for high-mortality countries; for India and China, we developed national models. We aggregated country results to generate regional and global estimates. Findings Of 7·6 million deaths in children younger than 5 years in 2010, 64·0% (4·879 million) were attributable to infectious causes and 40·3% (3·072 million) occurred in neonates. Preterm birth complications (14·1%; 1·078 million, uncertainty range UR 0·916–1·325), intrapartum-related complications (9·4%; 0·717 million, 0·610–0·876), and sepsis or meningitis (5·2%; 0·393 million, 0·252–0·552) were the leading causes of neonatal death. In older children, pneumonia (14·1%; 1·071 million, 0·977–1·176), diarrhoea (9·9%; 0·751 million, 0·538–1·031), and malaria (7·4%; 0·564 million, 0·432–0·709) claimed the most lives. Despite tremendous efforts to identify relevant data, the causes of only 2·7% (0·205 million) of deaths in children younger than 5 years were medically certified in 2010. Between 2000 and 2010, the global burden of deaths in children younger than 5 years decreased by 2 million, of which pneumonia, measles, and diarrhoea contributed the most to the overall reduction (0·451 million 0·339–0·547, 0·363 million 0·283–0·419, and 0·359 million 0·215–0·476, respectively). However, only tetanus, measles, AIDS, and malaria (in Africa) decreased at an annual rate sufficient to attain the Millennium Development Goal 4. Interpretation Child survival strategies should direct resources toward the leading causes of child mortality, with attention focusing on infectious and neonatal causes. More rapid decreases from 2010–15 will need accelerated reduction for the most common causes of death, notably pneumonia and preterm birth complications. Continued efforts to gather high-quality data and enhance estimation methods are essential for the improvement of future estimates. Funding The Bill & Melinda Gates Foundation.
In the United States, regional variation in cardiovascular mortality is well-known but county-level estimates for all major cardiovascular conditions have not been produced.
To estimate ...age-standardized mortality rates from cardiovascular diseases by county.
Deidentified death records from the National Center for Health Statistics and population counts from the US Census Bureau, the National Center for Health Statistics, and the Human Mortality Database from 1980 through 2014 were used. Validated small area estimation models were used to estimate county-level mortality rates from all cardiovascular diseases, including ischemic heart disease, cerebrovascular disease, ischemic stroke, hemorrhagic stroke, hypertensive heart disease, cardiomyopathy, atrial fibrillation and flutter, rheumatic heart disease, aortic aneurysm, peripheral arterial disease, endocarditis, and all other cardiovascular diseases combined.
The 3110 counties of residence.
Age-standardized cardiovascular disease mortality rates by county, year, sex, and cause.
From 1980 to 2014, cardiovascular diseases were the leading cause of death in the United States, although the mortality rate declined from 507.4 deaths per 100 000 persons in 1980 to 252.7 deaths per 100 000 persons in 2014, a relative decline of 50.2% (95% uncertainty interval UI, 49.5%-50.8%). In 2014, cardiovascular diseases accounted for more than 846 000 deaths (95% UI, 827-865 thousand deaths) and 11.7 million years of life lost (95% UI, 11.6-11.9 million years of life lost). The gap in age-standardized cardiovascular disease mortality rates between counties at the 10th and 90th percentile declined 14.6% from 172.1 deaths per 100 000 persons in 1980 to 147.0 deaths per 100 000 persons in 2014 (posterior probability of decline >99.9%). In 2014, the ratio between counties at the 90th and 10th percentile was 2.0 for ischemic heart disease (119.1 vs 235.7 deaths per 100 000 persons) and 1.7 for cerebrovascular disease (40.3 vs 68.1 deaths per 100 000 persons). For other cardiovascular disease causes, the ratio ranged from 1.4 (aortic aneurysm: 3.5 vs 5.1 deaths per 100 000 persons) to 4.2 (hypertensive heart disease: 4.3 vs 17.9 deaths per 100 000 persons). The largest concentration of counties with high cardiovascular disease mortality extended from southeastern Oklahoma along the Mississippi River Valley to eastern Kentucky. Several cardiovascular disease conditions were clustered substantially outside the South, including atrial fibrillation (Northwest), aortic aneurysm (Midwest), and endocarditis (Mountain West and Alaska). The lowest cardiovascular mortality rates were found in the counties surrounding San Francisco, California, central Colorado, northern Nebraska, central Minnesota, northeastern Virginia, and southern Florida.
Substantial differences exist between county ischemic heart disease and stroke mortality rates. Smaller differences exist for diseases of the myocardium, atrial fibrillation, aortic and peripheral arterial disease, rheumatic heart disease, and endocarditis.
In China, diabetes prevalence has increased substantially in recent decades, but there are no reliable estimates of the excess mortality currently associated with diabetes.
To assess the proportional ...excess mortality associated with diabetes and estimate the diabetes-related absolute excess mortality in rural and urban areas of China.
A 7-year nationwide prospective study of 512 869 adults aged 30 to 79 years from 10 (5 rural and 5 urban) regions in China, who were recruited between June 2004 and July 2008 and were followed up until January 2014.
Diabetes (previously diagnosed or detected by screening) recorded at baseline.
All-cause and cause-specific mortality, collected through established death registries. Cox regression was used to estimate adjusted mortality rate ratio (RR) comparing individuals with diabetes vs those without diabetes at baseline.
Among the 512 869 participants, the mean (SD) age was 51.5 (10.7) years, 59% (n = 302 618) were women, and 5.9% (n = 30 280) had diabetes (4.1% in rural areas, 8.1% in urban areas, 5.8% of men, 6.1% of women, 3.1% had been previously diagnosed, and 2.8% were detected by screening). During 3.64 million person-years of follow-up, there were 24 909 deaths, including 3384 among individuals with diabetes. Compared with adults without diabetes, individuals with diabetes had a significantly increased risk of all-cause mortality (1373 vs 646 deaths per 100 000; adjusted RR, 2.00 95% CI, 1.93-2.08), which was higher in rural areas than in urban areas (rural RR, 2.17 95% CI, 2.07-2.29; urban RR, 1.83 95% CI, 1.73-1.94). Presence of diabetes was associated with increased mortality from ischemic heart disease (3287 deaths; RR, 2.40 95% CI, 2.19-2.63), stroke (4444 deaths; RR, 1.98 95% CI, 1.81-2.17), chronic liver disease (481 deaths; RR, 2.32 95% CI, 1.76-3.06), infections (425 deaths; RR, 2.29 95% CI, 1.76-2.99), and cancer of the liver (1325 deaths; RR, 1.54 95% CI, 1.28-1.86), pancreas (357 deaths; RR, 1.84 95% CI, 1.35-2.51), female breast (217 deaths; RR, 1.84 95% CI, 1.24-2.74), and female reproductive system (210 deaths; RR, 1.81 95% CI, 1.20-2.74). For chronic kidney disease (365 deaths), the RR was higher in rural areas (18.69 95% CI, 14.22-24.57) than in urban areas (6.83 95% CI, 4.73-9.88). Among those with diabetes, 10% of all deaths (16% rural; 4% urban) were due to definite or probable diabetic ketoacidosis or coma (408 deaths).
Among adults in China, diabetes was associated with increased mortality from a range of cardiovascular and noncardiovascular diseases. Although diabetes was more common in urban areas, it was associated with greater excess mortality in rural areas.
The Sustainable Development Goal (SDG) target 3.4 is to reduce premature mortality from non-communicable diseases (NCDs) by a third by 2030 relative to 2015 levels, and to promote mental health and ...wellbeing. We used data on cause-specific mortality to characterise the risk and trends in NCD mortality in each country and evaluate combinations of reductions in NCD causes of death that can achieve SDG target 3.4. Among NCDs, ischaemic heart disease is responsible for the highest risk of premature death in more than half of all countries for women, and more than three-quarters for men. However, stroke, other cardiovascular diseases, and some cancers are associated with a similar risk, and in many countries, a higher risk of premature death than ischaemic heart disease. Although premature mortality from NCDs is declining in most countries, for most the pace of change is too slow to achieve SDG target 3.4. To investigate the options available to each country for achieving SDG target 3.4, we considered different scenarios, each representing a combination of fast (annual rate achieved by the tenth best performing percentile of all countries) and average (median of all countries) declines in risk of premature death from NCDs. Pathways analysis shows that every country has options for achieving SDG target 3.4. No country could achieve the target by addressing a single disease. In at least half the countries, achieving the target requires improvements in the rate of decline in at least five causes for women and in at least seven causes for men to the same rate achieved by the tenth best performing percentile of all countries. Tobacco and alcohol control and effective health-system interventions—including hypertension and diabetes treatment; primary and secondary cardiovascular disease prevention in high-risk individuals; low-dose inhaled corticosteroids and bronchodilators for asthma and chronic obstructive pulmonary disease; treatment of acute cardiovascular diseases, diabetes complications, and exacerbations of asthma and chronic obstructive pulmonary disease; and effective cancer screening and treatment—will reduce NCD causes of death necessary to achieve SDG target 3.4 in most countries.
Objective
To determine mortality and causes of death in a multinational inception cohort of subjects with systemic sclerosis (SSc).
Methods
We quantified mortality as standardized mortality ratio ...(SMR), years of life lost, and percentage mortality in the first decade of disease. The inception cohort comprised subjects recruited within 4 years of disease onset. For comparison, we used a prevalent cohort, which included all subjects irrespective of disease duration at recruitment. We determined a single primary cause of death (SSc related or non–SSc related) using a standardized case report form, and we evaluated predictors of mortality using multivariable Cox regression.
Results
In the inception cohort of 1,070 subjects, there were 140 deaths (13%) over a median follow‐up of 3.0 years (interquartile range 1.0–5.1 years), with a pooled SMR of 4.06 (95% confidence interval 95% CI 3.39–4.85), up to 22.4 years of life lost in women and up to 26.0 years of life lost in men, and mortality in the diffuse disease subtype of 24.2% at 8 years. In the prevalent cohort of 3,218 subjects, the pooled SMR was lower at 3.39 (95% CI 3.06–3.71). In the inception cohort, 62.1% of the primary causes of death were SSc related. Malignancy, sepsis, cerebrovascular disease, and ischemic heart disease were the most common non–SSc‐related causes of death. Predictors of early mortality included male sex, older age at disease onset, diffuse disease subtype, pulmonary arterial hypertension, and renal crisis.
Conclusion
Early mortality in SSc is substantial, and prevalent cohorts underestimate mortality in SSc by failing to capture early deaths, particularly in men and those with diffuse disease.
The impact of chronic exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5)) on respiratory disease and lung cancer mortality is ...poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 and 2008, we examined the association between chronic PM2.5 exposure and cause-specific mortality. We evaluated confounding through adjustment for neighborhood behavioral covariates and decomposition of PM2.5 into 2 spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10-μg/m3 increase) with respiratory, chronic obstructive pulmonary disease, and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular and lung cancer mortality. Risk ratios generally increased with longer moving averages; for example, an elevation in 60-month moving average PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared with 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving average exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In this large cohort of US elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased mortality from respiratory disease, lung cancer, and cardiovascular disease.
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