Diagnostic and prognostic significance of systemic alkyl quinolones for P. aeruginosa in cystic fibrosis: a longitudinal study

Background Pulmonary P. aeruginosa infection is associated with poor outcomes in cystic fibrosis (CF) and early diagnosis is challenging, particularly in those who are unable to expectorate sputum. Specific P. aeruginosa 2-alkyl-4-quinolones are detectable in the sputum, plasma and urine of adults with CF, suggesting that they have potential as biomarkers for P. aeruginosa infection. Aim To investigate systemic 2-alkyl-4-quinolones as potential biomarkers for pulmonary P. aeruginosa infection. Methods A multicentre observational study of 176 adults and 68 children with CF. Cross-sectionally, comparisons were made between current P. aeruginosa infection using six 2-alkyl-4-quinolones detected in sputum, plasma and urine against hospital microbiological culture results. All participants without P. aeruginosa infection at baseline were followed up for one year to determine if 2-alkyl-4-quinolones were early biomarkers of pulmonary P. aeruginosa infection. Results Cross-sectional analysis: the most promising biomarker with the greatest diagnostic accuracy was 2-heptyl-4-hydroxyquinoline (HHQ). In adults, areas under the ROC curves (95% confidence intervals) for HHQ analyses were 0.82 (0.75–0.89) in sputum, 0.76 (0.69–0.82) in plasma and 0.82 (0.77–0.88) in urine. In children, the corresponding values for HHQ analyses were 0.88 (0.77–0.99) in plasma and 0.83 (0.68–0.97) in urine. Longitudinal analysis: Ten adults and six children had a new positive respiratory culture for P. aeruginosa in follow-up. A positive plasma HHQ test at baseline was significantly associated with a new positive culture for P. aeruginosa in both adults and children in follow-up (odds ratio (OR) = 6.67;-95% CI:-1.48–30.1;-p = 0.01 and OR = 70; 95% CI: 5–956;-p < 0.001 respectively). Conclusions AQs measured in sputum, plasma and urine may be used to diagnose current infection with P. aeruginosa in adults and children with CF. These preliminary data show that plasma HHQ may have potential as an early biomarker of pulmonary P. aeruginosa. Further studies are necessary to evaluate if HHQ could be used in clinical practice to aid early diagnosis of P. aeruginosa infection in the future

Safety and efficacy of vanzacaftor–tezacaftor–deutivacaftor in adults with cystic fibrosis: randomised, double-blind, controlled, phase 2 trials

Background Elexacaftor–tezacaftor–ivacaftor has been shown to be safe and efficacious in people with cystic fibrosis and at least one F508del allele. Our aim was to identify a novel cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination capable of further increasing CFTR-mediated chloride transport, with the potential for once-daily dosing. Methods We conducted two phase 2 clinical trials to assess the safety and efficacy of a once-daily combination of vanzacaftor–tezacaftor–deutivacaftor in participants with cystic fibrosis who were aged 18 years or older. A phase 2 randomised, double-blind, active-controlled study (VX18-561-101; April 17, 2019, to Aug 20, 2020) was carried out to compare deutivacaftor monotherapy with ivacaftor monotherapy in participants with CFTR gating mutations, following a 4-week ivacaftor monotherapy run-in period. Participants were randomly assigned to receive either ivacaftor 150 mg every 12 h, deutivacaftor 25 mg once daily, deutivacaftor 50 mg once daily, deutivacaftor 150 mg once daily, or deutivacaftor 250 mg once daily in a 1:1:2:2:2 ratio. The primary endpoint was absolute change in ppFEV1 from baseline at week 12. A phase 2 randomised, double-blind, controlled, proof-of-concept study of vanzacaftor–tezacaftor–deutivacaftor (VX18-121-101; April 30, 2019, to Dec 10, 2019) was conducted in participants with cystic fibrosis and heterozygous for F508del and a minimal function mutation (F/MF genotypes) or homozygous for F508del (F/F genotype). Participants with F/MF genotypes were randomly assigned 1:2:2:1 to receive either 5 mg, 10 mg, or 20 mg of vanzacaftor in combination with tezacaftor–deutivacaftor or a triple placebo for 4 weeks, and participants with the F/F genotype were randomly assigned 2:1 to receive either vanzacaftor (20 mg)–tezacaftor–deutivacaftor or tezacaftor–ivacaftor active control for 4 weeks, following a 4-week tezacaftor–ivacaftor run-in period. Primary endpoints for part 1 and part 2 were safety and tolerability and absolute change in ppFEV1 from baseline to day 29. Secondary efficacy endpoints were absolute change from baseline at day 29 in sweat chloride concentrations and Cystic Fibrosis Questionnaire-Revised (CFQ-R) respiratory domain score. These clinical trials are registered with ClinicalTrials.gov, NCT03911713 and NCT03912233, and are complete. Findings In study VX18-561-101, participants treated with deutivacaftor 150 mg once daily (n=23) or deutivacaftor 250 mg once daily (n=24) had mean absolute changes in ppFEV1 of 3·1 percentage points (95% CI –0·8 to 7·0) and 2·7 percentage points (–1·0 to 6·5) from baseline at week 12, respectively, versus –0·8 percentage points (–6·2 to 4·7) with ivacaftor 150 mg every 12 h (n=11); the deutivacaftor safety profile was consistent with the established safety profile of ivacaftor 150 mg every 12 h. In study VX18-121-101, participants with F/MF genotypes treated with vanzacaftor (5 mg)–tezacaftor–deutivacaftor (n=9), vanzacaftor (10 mg)–tezacaftor–deutivacaftor (n=19), vanzacaftor (20 mg)–tezacaftor–deutivacaftor (n=20), and placebo (n=10) had mean changes relative to baseline at day 29 in ppFEV1 of 4·6 percentage points (−1·3 to 10·6), 14·2 percentage points (10·0 to 18·4), 9·8 percentage points (5·7 to 13·8), and 1·9 percentage points (−4·1 to 8·0), respectively, in sweat chloride concentration of −42·8 mmol/L (–51·7 to –34·0), −45·8 mmol/L (95% CI –51·9 to –39·7), −49·5 mmol/L (–55·9 to –43·1), and 2·3 mmol/L (−7·0 to 11·6), respectively, and in CFQ-R respiratory domain score of 17·6 points (3·5 to 31·6), 21·2 points (11·9 to 30·6), 29·8 points (21·0 to 38·7), and 3·3 points (−10·1 to 16·6), respectively. Participants with the F/F genotype treated with vanzacaftor (20 mg)–tezacaftor–deutivacaftor (n=18) and tezacaftor–ivacaftor (n=10) had mean changes relative to baseline (taking tezacaftor–ivacaftor) at day 29 in ppFEV1 of 15·9 percentage points (11·3 to 20·6) and −0·1 percentage points (−6·4 to 6·1), respectively, in sweat chloride concentration of −45·5 mmol/L (−49·7 to −41·3) and −2·6 mmol/L (−8·2 to 3·1), respectively, and in CFQ-R respiratory domain score of 19·4 points (95% CI 10·5 to 28·3) and −5·0 points (−16·9 to 7·0), respectively. The most common adverse events overall were cough, increased sputum, and headache. One participant in the vanzacaftor–tezacaftor–deutivacaftor group had a serious adverse event of infective pulmonary exacerbation and another participant had a serious rash event that led to treatment discontinuation. For most participants, adverse events were mild or moderate in severity. Interpretation Once-daily dosing with vanzacaftor–tezacaftor–deutivacaftor was safe and well tolerated and improved lung function, respiratory symptoms, and CFTR function. These results support the continued investigation of vanzacaftor–tezacaftor–deutivacaftor in phase 3 clinical trials compared with elexacaftor–tezacaftor–ivacaftor. Funding Vertex Pharmaceuticals

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, 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

Background Improving 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. Methods We 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 GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95 uncertainty interval 61·4�61·9) in 1980 to 71·8 years (71·5�72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7�17·4), to 62·6 years (56·5�70·2). Total deaths increased by 4·1 (2·6�5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0 (15·8�18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1 (12·6�16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1 (11·9�14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1, 39·1�44·6), malaria (43·1, 34·7�51·8), neonatal preterm birth complications (29·8, 24·8�34·9), and maternal disorders (29·1, 19·3�37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146�000 deaths, 118�000�183�000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393�000 deaths, 228�000�532�000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost YLLs) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

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

Background Improving 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. Methods We 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 GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95 uncertainty interval 61·4�61·9) in 1980 to 71·8 years (71·5�72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7�17·4), to 62·6 years (56·5�70·2). Total deaths increased by 4·1 (2·6�5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0 (15·8�18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1 (12·6�16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1 (11·9�14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1, 39·1�44·6), malaria (43·1, 34·7�51·8), neonatal preterm birth complications (29·8, 24·8�34·9), and maternal disorders (29·1, 19·3�37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146�000 deaths, 118�000�183�000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393�000 deaths, 228�000�532�000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost YLLs) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens