A Surdez versus Violência
In: Utopia: revista anarquista de cultura e intervenção, Heft 22, S. 48-49
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In: Utopia: revista anarquista de cultura e intervenção, Heft 22, S. 48-49
In: Communications in statistics. Simulation and computation, Band 52, Heft 5, S. 2210-2230
ISSN: 1532-4141
In: Children and youth services review: an international multidisciplinary review of the welfare of young people, Band 112, S. 104923
ISSN: 0190-7409
In: Journal of the International AIDS Society, Band 15, Heft S4, S. 1-1
ISSN: 1758-2652
Purpose of the studyHIV infection and antiretroviral therapy (ART) have been associated with lipodystrophy (LD), but we unknown the effect of IFN/RBV on the body composition, mainly body fat, in HIV patients, already with a degree of LD. Our objective: to assess the body composition in HIV‐HCV patients that start treatment with IFN/RBV and the changes at its ending.Material and MethodsPilot and prospective study of HIV‐HCV patients. We performed (baseline and at the end of treatment) clinical and laboratory parameters, HIV and HCV‐related. Total and regional body fat contents were measured in the same periods with DEXA (dual‐energy X‐ray absorptiometry) scanners. For LD diagnostic we used the definition of fat/mass ratio (FMR): absence, <1, obvious >1.5, and between 1–1.5 it could have LD but is better to see the evolution. Data are expressed in median.ResultsWe included 10 male patients; age 45 yo; time on ART 115 months. HIV VL < 20 in 9; CD4 count 577/mm3. Genotype 1 in 8, and 3 in 2. Time on IFN/RBV: 10 months. At the end of the treatment we observed a decrease in the level of total, HDL and LDL‐cholesterol (expressed in percentage: 4, 16 and 1.5 respectively) and a slightly increase in the level of TGR (9%). The total body mass decreased 7% (from 76.2 kg to 70.6), the total body fat decreased 18.4% (from 21.060 g to 17.172) and the total lean mass decreased only 3%. Results expressed in percentage and by regional parts, we observed also a decrease in all the parameters: 11% in total body fat (from 26.3 to 23.4), 6% in the fat in arms (21.9 to 20.5), 10% in total fat in legs (22.5 to 20.3) and 12.5% in total trunk fat (30.3 to 26.5). The FMR also decreased from 1.5 to 1.4.ConclusionsTrend to LD at baseline, as the FMR was 1.5. After 10 months on treatment with IFN/RBV there was a decrease in the total body mass (7%), mainly due to the loss of total body fat and less in the lean mass. Regarding the percentage of fat loss, we observed the biggest decrease in the trunk fat and the lesser in the limb fat. So, the FMR also decreased. This effect does not get worse the baseline LD; on the contrary it improves it, although very slightly (decrease of 0.1 in FMR), and could serve to advise the patients and not to be afraid of a possible worsening of LD. The study is ongoing and the next objective will be to perform DXA one year after the end of treatment and to expand the cohort to study clinical or laboratory factors related with these results.
11 pages, 4 figures, 2 tables.-- This article is licensed under a Creative Commons Attribution 4.0 International License ; Climate change is already impacting fisheries with species moving across fishing areas, crossing institutional borders, and thus creating conflicts over fisheries management. In this scenario, scholars agree that adaptation to climate change requires that fisheries increase their social, institutional, and ecological resilience. The resilience or capacity of a fishery to be maintained without shifting to a different state (e.g., collapse) is at stake under climate change impacts and overexploitation. Despite this urgent need, applying the resilience concept in a spatially explicit and quantitative manner to inform policy remains unexplored. We take a resilience approach and operationalize the concept in industrial fisheries for two species that have been observed to significantly shift distribution in European waters: hake (Merluccius merluccius) and cod (Gadus morhua), in the context of the European Union institutional settings. With a set of resilience factors from the literature and by means of contemporary and historic data, we select indicators that are combined into an index that measures resilience on the ecologic, socioeconomic, and institutional dimensions of the fishery. We find that the resilience index varies among species and countries, with lower resilience levels in the socioeconomic dimension of the fisheries. We also see that resilience largely depends on the overexploitation status of the fishery. The results highlight the need to address social and institutional settings to enhance fisheries adaptation to climate change and allow to inform on climate resilient adaptation pathways for the fisheries ; This research is supported by the project CLOCK, under the European Horizon 2020 Program, ERC Starting Grant Agreement nº679812 funded by the European Research Council. E.O. thanks the Xunta the Galicia GAIN Oportunius programme and Consellería de Educación (Galicia, Spain) for additional financial support. I.F.-S. was funded by EU H2020 project ClimeFish (EU 677039). J.B.-P. was funded by EU H2020 (FutureMARES, contract no. 869300). ; Peer reviewed
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In: Journal of the International AIDS Society, Band 15, Heft S4, S. 1-1
ISSN: 1758-2652
Purpose of the studyATV/r or DRV/r plus TDF/FTC are recommended for first‐line therapy due at least in part to their clinical tolerability and scarce metabolic effects. We investigated whether both regimens might differ regarding plasma lipids, insulin resistance (HOMA‐IR), and estimated glomerular filtration rate (MDRD).MethodsMulticentre, randomized, clinical trial (ATADAR Study, NCT01274780). Primary end‐point: 24‐week change in total cholesterol. Secondary end‐points: changes in lipids other than total cholesterol, HOMA‐IR, and MDRD; clinical tolerability; and efficacy. We assumed that patients assigned to DRV/r would have an increase in plasma total cholesterol<21 mg/dL, which was the difference between lopinavir/r and ATV/r in CASTLE study. Fasting plasma lipids, glucose, insulin, and creatinine were measured at baseline, and 4, 12, and 24 weeks. Analyses were by intent‐to‐treat.Summary of results180 patients were randomized (ATV/r=91, DRV/r=89), 95% Caucasian, and 8% co‐infected with hepatitis C virus. At baseline (mean, SD): age 36 (9) years; plasma log HIV RNA 4.8 (0.7); CD4 334 (189) cells/mm3; triglycerides 107 (62), total cholesterol 158 (32), LDL cholesterol 97 (28), HDL cholesterol 39 (11) mg/dL, and glucose 84 (13) mg/dL; HOMA‐IR 2.47 (3.46); and MDRD 108 (21) mL/min/1.73 m2. At 24 weeks, total cholesterol (mean, SD) changed +7.26 (26.76) mg/dL with ATV/r and +11.47 (25.85) mg/dL with DRV/r (estimated difference ATV/r minus DRV/r −4.21 (95% CI−12.11 to +3.69), P=0.2944), thus confirming our primary hypothesis. Changes (mean, SD) in triglycerides were roughly similar: +16.29 (61.76) mg/dL with ATV/r and +18.40 (64.24) mg/dL with DRV/r (P=0.8261), but there were trends to more favourable changes in LDL (−2.14 [21.45] vs +3.14 [21.97] mg/dL, P=0.1160) and HDL cholesterol (+5.50 [10.36] vs +3.88 [8.42] mg/dL, P=0.2625), and total‐to‐HDL cholesterol ratio (−1.16 [6.38] vs −0.14 [0.86], P=0.0652) with ATV/r than with DRV/r. There were small, non‐significant decreases in HOMA‐IR (ATV/r −0.17 [2.48] vs DRV/r −0.70 [3.38], P=0.3785) and MDRD (ATV/r −7 [22] vs DRV/r −6 [15] mL/min/1.73 m2, P=0.6652). 6 ATV/r and 3 DRV/r patients had their study drugs discontinued because of adverse effects (P=0.4967). 7 additional patients in each arm had confirmed HIV RNA >50 copies.ConclusionsThere were trends to more favourable changes in LDL and HDL cholesterol and particularly total‐to‐HDL cholesterol ratio at 24 weeks with ATV/r than with DRV/r.
In: Journal of the International AIDS Society, Band 13, S. P43-P43
ISSN: 1758-2652
In: STOTEN-D-23-29969
SSRN
In: Journal of the International AIDS Society, Band 13, Heft S4
ISSN: 1758-2652
7‐11 November 2010, Tenth International Congress on Drug Therapy in HIV Infection, Glasgow, UK
In: Journal of the International AIDS Society, Band 13, Heft S4
ISSN: 1758-2652
7‐11 November 2010, Tenth International Congress on Drug Therapy in HIV Infection, Glasgow, UK
Background: The scale-up of tobacco control, especially after the adoption of the Framework Convention for Tobacco Control, is a major public health success story. Nonetheless, smoking remains a leading risk for early death and disability worldwide, and therefore continues to require sustained political commitment. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) offers a robust platform through which global, regional, and national progress toward achieving smoking-related targets can be assessed. Methods: We synthesised 2818 data sources with spatiotemporal Gaussian process regression and produced estimates of daily smoking prevalence by sex, age group, and year for 195 countries and territories from 1990 to 2015. We analysed 38 risk-outcome pairs to generate estimates of smoking-attributable mortality and disease burden, as measured by disability-adjusted life-years (DALYs). We then performed a cohort analysis of smoking prevalence by birth-year cohort to better understand temporal age patterns in smoking. We also did a decomposition analysis, in which we parsed out changes in all-cause smoking-attributable DALYs due to changes in population growth, population ageing, smoking prevalence, and risk-deleted DALY rates. Finally, we explored results by level of development using the Socio-demographic Index (SDI). Findings: Worldwide, the age-standardised prevalence of daily smoking was 25·0% (95% uncertainty interval [UI] 24·2–25·7) for men and 5·4% (5·1–5·7) for women, representing 28·4% (25·8–31·1) and 34·4% (29·4–38·6) reductions, respectively, since 1990. A greater percentage of countries and territories achieved significant annualised rates of decline in smoking prevalence from 1990 to 2005 than in between 2005 and 2015; however, only four countries had significant annualised increases in smoking prevalence between 2005 and 2015 (Congo [Brazzaville] and Azerbaijan for men and Kuwait and Timor-Leste for women). In 2015, 11·5% of global deaths (6·4 million [95% UI 5·7–7·0 million]) were attributable to smoking worldwide, of which 52·2% took place in four countries (China, India, the USA, and Russia). Smoking was ranked among the five leading risk factors by DALYs in 109 countries and territories in 2015, rising from 88 geographies in 1990. In terms of birth cohorts, male smoking prevalence followed similar age patterns across levels of SDI, whereas much more heterogeneity was found in age patterns for female smokers by level of development. While smoking prevalence and risk-deleted DALY rates mostly decreased by sex and SDI quintile, population growth, population ageing, or a combination of both, drove rises in overall smoking-attributable DALYs in low-SDI to middle-SDI geographies between 2005 and 2015. Interpretation: The pace of progress in reducing smoking prevalence has been heterogeneous across geographies, development status, and sex, and as highlighted by more recent trends, maintaining past rates of decline should not be taken for granted, especially in women and in low-SDI to middle-SDI countries. Beyond the effect of the tobacco industry and societal mores, a crucial challenge facing tobacco control initiatives is that demographic forces are poised to heighten smoking's global toll, unless progress in preventing initiation and promoting cessation can be substantially accelerated. Greater success in tobacco control is possible but requires effective, comprehensive, and adequately implemented and enforced policies, which might in turn require global and national levels of political commitment beyond what has been achieved during the past 25 years. Funding: Bill & Melinda Gates Foundation and Bloomberg Philanthropies.
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Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9–3·0) for men and 3·5 years (3·4–3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78–0·92) and 1·2 years (1·1–1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. Funding Bill & Melinda Gates Foundation. ; We would like to thank the countless individuals who have contributed to the Global Burden of Disease Study 2015 in various capacities. The data reported here have been supplied by the US Renal Data System (USRDS). Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Collection of these data was made possible by the US Agency for International Development (USAID) under the terms of cooperative agreement GPO-A-00-08-000_D3-00. Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. Parts of this material are based on data and information provided by the Canadian institute for Health Information. However, the analyses, conclusions, opinions and statements expressed herein are those of the author and not those of the Canadian Institute for Health information. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with license no SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law, 2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. This paper uses data from SHARE Waves 1, 2, 3 (SHARELIFE), 4 and 5 (DOIs: 10.6103/SHARE.w1.500, 10.6103/SHARE.w2.500, 10.6103/SHARE.w3.500, 10.6103/SHARE.w4.500, 10.6103/SHARE.w5.500), see Börsch-Supan and colleagues, 2013, for methodological details. The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: number 211909, SHARE-LEAP: number 227822, SHARE M4: number 261982). Additional funding from the German Ministry of Education and Research, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, and OGHA_04-064) and from various national funding sources is gratefully acknowledged. This study has been realised using the data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is financed by the Swiss National Science Foundation. The following individuals would like to acknowledge various forms of institutional support: Simon I Hay is funded by a Senior Research Fellowship from the Wellcome Trust (#095066), and grants from the Bill & Melinda Gates Foundation (OPP1119467, OPP1093011, OPP1106023 and OPP1132415). Amanda G Thrift is supported by a fellowship from the National Health and Medical Research Council (GNT1042600). Panniyammakal Jeemon is supported by the Wellcome Trust-DBT India Alliance, Clinical and Public Health, Intermediate Fellowship (2015–2020). Boris Bikbov, Norberto Percio, and Giuseppe Remuzzi acknowledge that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). Amador Goodridge acknowledges funding from Sistema Nacional de Investigadores de Panamá-SNI. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). Lijing L Yan is supported by the National Natural Sciences Foundation of China grants (71233001 and 71490732). Olanrewaju Oladimeji is an African Research Fellow at Human Sciences Research Council (HSRC) and Doctoral Candidate at the University of KwaZulu-Natal (UKZN), South Africa, and would like to acknowledge the institutional support by leveraging on the existing organisational research infrastructure at HSRC and UKZN. Nicholas Steel received funding from Public Health England as a Visiting Scholar in the Institute for Health Metrics and Evaluation in 2016. No individuals acknowledged received additional compensation for their efforts. ; Peer-reviewed ; Publisher Version
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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. ; We thank the countless individuals who have contributed to the Global Burden of Disease Study 2015 in various capacities. The data reported here have been supplied by the United States Renal Data System (USRDS). Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Collection of these data was made possible by USAID under the terms of cooperative agreement GPO-A-00-08-000_D3-00. Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. Parts of this material are based on data and information provided by the Canadian institute for Health Information. However, the analyses, conclusions, opinions and statements expressed herein are those of the author and not those of the Canadian Institute for Health information. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence number SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law–2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. The following individuals acknowledge various forms of institutional support. Simon I Hay is funded by a Senior Research Fellowship from the Wellcome Trust (#095066), and grants from the Bill & Melinda Gates Foundation (OPP1119467, OPP1093011, OPP1106023 and OPP1132415). Panniyammakal Jeemon is supported by a Clinical and Public Health Intermediate Fellowship from the Wellcome Trust-DBT India Alliance (2015–20). Luciano A Sposato is partly supported by the Edward and Alma Saraydar Neurosciences Fund, London Health Sciences Foundation, London, ON, Canada. George A Mensah notes that the views expressed in this Article are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute, National Institutes of Health, or the United States Department of Health and Human Services. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). Ana Maria Nogales Vasconcelos acknowledges that her team in Brazil received funding from Ministry of Health (process number 25000192049/2014-14). Rodrigo Sarmiento-Suarez receives institutional support from Universidad de Ciencias Aplicadas y Ambientales, UDCA, Bogotá, Colombia. Ulrich O Mueller and Andrea Werdecker gratefully acknowledge funding by the German National Cohort BMBF (grant number OIER 1301/22). Peter James was supported by the National Cancer Institute of the National Institutes of Health (Award K99CA201542). Brett M Kissela would like to acknowledge NIH/NINDS R-01 30678. Louisa Degenhardt is supported by an Australian National Health and Medical Research Council Principal Research fellowship. Daisy M X Abreu received institutional support from the Brazilian Ministry of Health (Proc number 25000192049/2014-14). Jennifer H MacLachlan receives funding support from the Australian Government Department of Health and Royal Melbourne Hospital Research Funding Program. Miriam Levi acknowledges institutional support received from CeRIMP, Regional Centre for Occupational Diseases and Injuries, Tuscany Region, Florence, Italy. Tea Lallukka reports funding from The Academy of Finland (grant 287488). No individuals acknowledged received additional compensation for their efforts. ; Peer-reviewed ; Publisher Version
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Background Surgery is the main modality of cure for solid cancers and was prioritised to continue during COVID-19 outbreaks. This study aimed to identify immediate areas for system strengthening by comparing the delivery of elective cancer surgery during the COVID-19 pandemic in periods of lockdown versus light restriction. Methods This international, prospective, cohort study enrolled 20 006 adult (≥18 years) patients from 466 hospitals in 61 countries with 15 cancer types, who had a decision for curative surgery during the COVID-19 pandemic and were followed up until the point of surgery or cessation of follow-up (Aug 31, 2020). Average national Oxford COVID-19 Stringency Index scores were calculated to define the government response to COVID-19 for each patient for the period they awaited surgery, and classified into light restrictions (index 60). The primary outcome was the non-operation rate (defined as the proportion of patients who did not undergo planned surgery). Cox proportional-hazards regression models were used to explore the associations between lockdowns and non-operation. Intervals from diagnosis to surgery were compared across COVID-19 government response index groups. This study was registered at ClinicalTrials.gov, NCT04384926. Findings Of eligible patients awaiting surgery, 2003 (10·0%) of 20 006 did not receive surgery after a median follow-up of 23 weeks (IQR 16–30), all of whom had a COVID-19-related reason given for non-operation. Light restrictions were associated with a 0·6% non-operation rate (26 of 4521), moderate lockdowns with a 5·5% rate (201 of 3646; adjusted hazard ratio [HR] 0·81, 95% CI 0·77–0·84; p<0·0001), and full lockdowns with a 15·0% rate (1775 of 11 827; HR 0·51, 0·50–0·53; p<0·0001). In sensitivity analyses, including adjustment for SARS-CoV-2 case notification rates, moderate lockdowns (HR 0·84, 95% CI 0·80–0·88; p<0·001), and full lockdowns (0·57, 0·54–0·60; p<0·001), remained independently associated with non-operation. Surgery beyond 12 weeks from diagnosis in patients without neoadjuvant therapy increased during lockdowns (374 [9·1%] of 4521 in light restrictions, 317 [10·4%] of 3646 in moderate lockdowns, 2001 [23·8%] of 11 827 in full lockdowns), although there were no differences in resectability rates observed with longer delays. Interpretation Cancer surgery systems worldwide were fragile to lockdowns, with one in seven patients who were in regions with full lockdowns not undergoing planned surgery and experiencing longer preoperative delays. Although short-term oncological outcomes were not compromised in those selected for surgery, delays and non-operations might lead to long-term reductions in survival. During current and future periods of societal restriction, the resilience of elective surgery systems requires strengthening, which might include protected elective surgical pathways and long-term investment in surge capacity for acute care during public health emergencies to protect elective staff and services. Funding National Institute for Health Research Global Health Research Unit, Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, Sarcoma UK, The Urology Foundation, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research.
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