Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.Funding/Support: The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context of World Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042

Gender disparities in symptomology of COVID-19 among adults in Arkansas

Only a few studies and reports assessing the natural history and symptomatology for COVID-19 by gender have been reported in literature to date. Thus, the objective of this study was to examine patterns in symptomology of COVID-19 by gender among a diverse adult population in Arkansas. Data on COVID-19 symptoms was collected at day of testing, 7th day and 14th day among participants at UAMS mobile testing units throughout the state of Arkansas. Diagnosis for SARS-CoV-2 infection was confirmed via nasopharyngeal swab and RT-PCR methods. Data analysis was conducted using Chi-square test and Poisson regression to assess the differences in characteristics by gender. A total of 60,648 community members and patients of Arkansas received RT-PCR testing. Among adults testing positive, we observed a statistically significant difference for fever (p < 0.001) and chills (p = 0.04). Males were more likely to report having a fever (22.6% vs. 17.1%; p < 0.001) and chills (14.9% vs. 12.6%; p = 0.04) compared to females. Among adults testing negative, females were more likely to report each symptom than males. To conclude, we observed a greater prevalence of certain symptoms such as fever and chills among men testing positive for COVID-19, compared to women during the time of testing. These differences elucidate the important issue of rapidly emerging health disparities during the COVID-19 pandemic

Workplace interventions for treatment of occupational asthma

Background: The impact of workplace interventions on the outcome of occupational asthma is not well understood. Objectives: To evaluate the effectiveness of workplace interventions on occupational asthma. Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE (PubMed); EMBASE(Ovid); NIOSHTIC-2; and CISILO (CCOHS) up to July 31, 2019. Selection criteria: We included all eligible randomized controlled trials, controlled before and after studies and interrupted time-series of workplace interventions for occupational asthma. Data collection and analysis: Two authors independently assessed study eligibility and risk of bias, and extracted data. Main results: We included 26 non-randomized controlled before and after studies with 1,695 participants that reported on three comparisons: complete removal from exposure and reduced exposure compared to continued exposure, and complete removal from exposure compared to reduced exposure. Reduction of exposure was achieved by limiting use of the agent, improving ventilation, or using protective equipment in the same job; by changing to another job with intermittent exposure; or by implementing education programs. For continued exposure, 56 per 1000 workers reported absence of symptoms at follow-up, the decrease in forced expiratory volume in one second as a percentage of a reference value (FEV1 %) was 5.4% during follow-up, and the standardized change in non-specific bronchial hyperreactivity (NSBH) was -0.18. In 18 studies, authors compared removal from exposure to continued exposure. Removal may increase the likelihood of reporting absence of asthma symptoms, with risk ratio (RR) 4.80 (95% confidence interval (CI) 1.67 to 13.86), and it may improve asthma symptoms, with RR 2.47 (95% CI 1.26 to 4.84), compared to continued exposure. Change in FEV1 % may be better with removal from exposure, with a mean difference (MD) of 4.23 % (95% CI 1.14 to 7.31) compared to continued exposure. NSBH may improve with removal from exposure, with standardized mean difference (SMD) 0.43 (95% CI 0.03 to 0.82). In seven studies, authors compared reduction of exposure to continued exposure. Reduction of exposure may increase the likelihood of reporting absence of symptoms, with RR 2.65 (95% CI 1.24 to 5.68). There may be no considerable difference in FEV1 % between reduction and continued exposure, with MD 2.76 % (95% CI -1.53 to 7.04). No studies reported or enabled calculation of change in NSBH. In ten studies, authors compared removal from exposure to reduction of exposure. Following removal from exposure there may be no increase in the likelihood of reporting absence of symptoms, with RR 6.05 (95% CI 0.86 to 42.34), and improvement in symptoms, with RR 1.11 (95% CI 0.84 to 1.47), as well as no considerable change in FEV1 %, with MD 2.58 % (95% CI −3.02 to 8.17). However, with all three outcomes, there may be improved results for removal from exposure in the subset of patients exposed to low molecular weight agents. No studies reported or enabled calculation of change in NSBH. In two studies, authors reported that the risk of unemployment after removal from exposure may increase compared with reduction of exposure, with RR 14.28 (95% CI 2.06 to 99.16). Four studies reported a decrease in income of 20% to 50% after removal from exposure. The quality of the evidence is very low for all outcomes. Authors' conclusions: Both removal from exposure and reduction of exposure may improve asthma symptoms compared with continued exposure. Removal from exposure, but not reduction of exposure, may improve lung function compared to continued exposure. When we compared removal from exposure directly to reduction of exposure, the former may improve symptoms and lung function more among patients exposed to low molecular weight agents. Removal from exposure may also increase the risk of unemployment. Care providers should balance the potential clinical benefits of removal from exposure or reduction of exposure with potential detrimental effects of unemployment. Additional high-quality studies are needed to evaluate the effectiveness of workplace interventions for occupational asthma

Workplace interventions for treatment of occupational asthma

BackgroundThe impact of workplace interventions on the outcome of occupational asthma is not well understood.ObjectivesTo evaluate the effectiveness of workplace interventions on occupational asthma.Search methodsWe searched the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE (PubMed); EMBASE(Ovid); NIOSHTIC-2; and CISILO (CCOHS) up to July 31, 2019.Selection criteriaWe included all eligible randomized controlled trials, controlled before and after studies and interrupted time-series of workplace interventions for occupational asthma.Data collection and analysisTwo authors independently assessed study eligibility and risk of bias, and extracted data.Main resultsWe included 26 non-randomized controlled before and after studies with 1,695 participants that reported on three comparisons: complete removal from exposure and reduced exposure compared to continued exposure, and complete removal from exposure compared to reduced exposure. Reduction of exposure was achieved by limiting use of the agent, improving ventilation, or using protective equipment in the same job; by changing to another job with intermittent exposure; or by implementing education programs. For continued exposure, 56 per 1000 workers reported absence of symptoms at follow-up, the decrease in forced expiratory volume in one second as a percentage of a reference value (FEV1 %) was 5.4% during follow-up, and the standardized change in non-specific bronchial hyperreactivity (NSBH) was -0.18.In 18 studies, authors compared removal from exposure to continued exposure. Removal may increase the likelihood of reporting absence of asthma symptoms, with risk ratio (RR) 4.80 (95% confidence interval (CI) 1.67 to 13.86), and it may improve asthma symptoms, with RR 2.47 (95% CI 1.26 to 4.84), compared to continued exposure. Change in FEV1 % may be better with removal from exposure, with a mean difference (MD) of 4.23 % (95% CI 1.14 to 7.31) compared to continued exposure. NSBH may improve with removal from exposure, with standardized mean difference (SMD) 0.43 (95% CI 0.03 to 0.82).In seven studies, authors compared reduction of exposure to continued exposure. Reduction of exposure may increase the likelihood of reporting absence of symptoms, with RR 2.65 (95% CI 1.24 to 5.68). There may be no considerable difference in FEV1 % between reduction and continued exposure, with MD 2.76 % (95% CI -1.53 to 7.04) . No studies reported or enabled calculation of change in NSBH.In two studies, authors reported that the risk of unemployment after removal from exposure may increase compared with reduction of exposure, with RR 14.28 (95% CI 2.06 to 99.16). Four studies reported a decrease in income of 20% to 50% after removal from exposure.The quality of the evidence is very low for all outcomes.Authors' conclusions Both removal from exposure and reduction of exposure may improve asthma symptoms compared with continued exposure. Removal from exposure, but not reduction of exposure, may improve lung function compared to continued exposure. When we compared removal from exposure directly to reduction of exposure, the former may improve symptoms and lung function more among patients exposed to low molecular weight agents. Removal from exposure may also increase the risk of unemployment. Care providers should balance the potential clinical benefits of removal from exposure or reduction of exposure with potential detrimental effects of unemployment. Additional high-quality studies are needed to evaluate the effectiveness of workplace interventions for occupational asthma

Location of Receipt of Initial Treatment and Outcomes in Long-Term Breast Cancer Survivors

<div><p>Purpose</p><p>Cancer outcomes differ depending on where treatment is received. We assessed differences in outcomes in long-term breast cancer survivors at a specialty care hospital by location of their initial treatment.</p><p>Methods</p><p>We retrospectively examined a cohort of women diagnosed with invasive early-stage breast cancer who did not experience recurrence for at least 5 years after the date of diagnosis and were evaluated at The University of Texas MD Anderson Cancer Center between January 1997 and August 2008. The location of initial treatment was categorized as MD Anderson (MDA-treated) or other (OTH-treated). Outcomes analyzed included recurrence-free survival (RFS), distant relapse-free survival (DRFS), and overall survival (OS). The Kaplan-Meier product-limit method was used to compare outcomes between the two groups. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI).</p><p>Results</p><p>We identified 5,091 breast cancer survivors (median follow-up 8.6 years), of whom 89.1% were MDA-treated. The 10-year OS, RFS, and DRFS rates were 90.9%, 88.4%, and 89.0% in the MDA-treated group and 74.3%, 49.8%, and 52.7% in the OTH-treated group, respectively. We observed worse outcomes in the OTH-group in both the univariate analysis and the multivariable analysis (OS: HR = 4.8, 95% CI = 3.9–6.0; RFS: HR = 5.8, 95% CI = 4.8–7.0; DRFS: HR = 5.4, 95% CI = 4.5–6.6).</p><p>Conclusion</p><p>Long-term breast cancer survivors who initiated their treatment at MD Anderson had better outcomes. Location of initial treatment could be an independent risk factor for survival outcomes at specialty care hospitals. This analysis has limitations inherent to retrospective observational studies such as other unmeasured variables may be associated with worse prognosis.</p></div

Demographic and clinical characteristics of breast cancer survivors who received their initial treatment at our institution (MDA-treated) or elsewhere (OTH-treated).

<p>Demographic and clinical characteristics of breast cancer survivors who received their initial treatment at our institution (MDA-treated) or elsewhere (OTH-treated).</p

Kaplan-Meier curves for (A) recurrence-free survival (RFS), (B) distant relapse-free survival (DRFS), and (C) overall survival (OS) for breast cancer survivors who received their initial treatment at our institution (MDA-treated) or elsewhere (OTH-treated).

<p>Kaplan-Meier curves for (A) recurrence-free survival (RFS), (B) distant relapse-free survival (DRFS), and (C) overall survival (OS) for breast cancer survivors who received their initial treatment at our institution (MDA-treated) or elsewhere (OTH-treated).</p