Analysis of survival factors after hepatic resection for colorectal cancer liver metastases: Does the R1 margin matter?

IntroductionThe effect of liver margin on colorectal cancer liver metastases (CRLM) after hepatectomy has been controversial. In this study, we conducted a postoperative follow-up study of 205 patients with CRLM to clarify whether a positive margin is significant and to define the risk factors affecting CRLM survival.MethodsThe data of 205 patients with CRLM who underwent surgical treatment at the Third Hospital of Peking University in the Department of General Surgery from January 2009 to December 2020 were retrospectively analyzed. The general data, surgical data and postoperative follow-up of the patients were statistically analyzed.ResultsThere were 130 cases (63.4%) of R0 resection and 75 cases (36.6%) of R1 resection. There were 136 males and 69 females, age 61 ± 11 years, and body mass index (BMI 24.5 ± 3.3 kg/m2). The overall survival rates at 1, 3, and 5 years for the entire cohort were 93.4%, 68.4%, and 45.5% in the R0 resection group vs. 93.2%, 53.7%, and 42% in the R1 resection group, respectively, which were not statistically significant (P = 0.520). The 1-, 3-, and 5-year disease-free survival rates of 63.2%, 33.3%, and 29.7% were significantly better in the R0 resection group than in the R1 resection group of 47.9%, 22.7%, and 17.7% (P = 0.016), respectively. After multivariable analysis, carbohydrate antigen 19-9 (CA19-9) > 39 U/ml (HR = 2.29, 95% CI: 1.39–3.79, P = 0.001), primary tumor perineural invasion (HR = 1.78, 95% CI: 1.01–3.13, P = 0.047), and BMI > 24 kg/m2 (HR = 1.75, 95% CI: 1.05–2.93, P = 0.033) were independently associated with poorer overall patient survival. The number of liver metastases >2 (HR = 1.65, 95% CI: 1.10–2.47, P = 0.016), the maximum diameter of metastases ≥50 mm (HR = 1.67, 95% CI: 1.06–2.64, P = 0.026), and vascular invasion of the primary tumor (HR = 1.65, 95% CI: 1.03–2.64, P = 0.038) were also independently associated with poorer disease-free survival.ConclusionIn patients undergoing hepatectomy for CRLM, the negative effect of the R1 margin should be downplayed, and although the disease-free survival of the R1 margin is shorter than that of the R0 margin, it has no impact on overall survival. To improve overall survival, extra attention should be given to the factors of preoperative BMI, preoperative CA19-9, and the presence of perineural invasion of the primary tumor

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

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

Pure Laparoscopic Liver Resection for Malignant Liver Tumor: Anatomic Resection Versus Nonanatomic Resection

Background: Laparoscopic liver resection (LLR) has been considered to be safe and feasible. However, few studies focused on the comparison between the anatomic and nonanatomic LLR. Therefore, the purpose of this study was to compare the perioperative factors and outcomes of the anatomic and nonanatomic LLR, especially the area of liver parenchymal transection and blood loss per unit area. Methods: In this study, surgical and oncological data of patients underwent pure LLR procedures for malignant liver tumor were prospectively collected. Blood loss per unit area of liver parenchymal transection was measured and considered as an important parameter. All procedures were conducted by a single surgeon. Results: During nearly 5 years, 84 patients with malignant liver tumor received a pure LLR procedure were included. Among them, 34 patients received anatomic LLR and 50 received nonanatomic LLR, respectively. Patients of the two groups were similar in terms of demographic features and tumor characteristics, despite the tumor size was significantly larger in the anatomic LLR group than that in the nonanatomic LLR group (4.77 ± 2.57 vs. 2.87 ± 2.10 cm, P = 0.001). Patients who underwent anatomic resection had longer operation time (364.09 ± 131.22 vs. 252.00 ± 135.21 min, P < 0.001) but less blood loss per unit area (7.85 ± 7.17 vs. 14.17 ± 10.43 ml/cm 2 , P = 0.018). Nonanatomic LLR was associated with more blood loss when the area of parenchymal transection was equal to the anatomic LLR. No mortality occurred during the hospital stay and 30 days after the operation. Moreover, there was no difference in the incidence of postoperative complications. The disease-free and overall survival rates showed no significant differences between the anatomic LLR and nonanatomic LLR groups. Conclusions: Both anatomic and nonanatomic pure LLR are safe and feasible. Measuring the area of parenchymal transection is a simple and effective method to estimate the outcomes of the liver resection surgery. Blood loss per unit area is an important parameter which is comparable between the anatomic LLR and nonanatomic LLR groups

Spatial and Temporal Variations of Heat Waves in China from 1961 to 2010

Daily maximum temperatures from 753 stations across China and the heat wave indicators are used to study the temporal and spatial characteristics of heat wave intensity, frequency and heat wave days in China over the period of 1961–2010. The results show that high frequency, long duration and strong intensity of heat waves occurred in the Jianghuai area, Jiangnan area, and eastern Sichuan Basin. The highest frequency and the longest duration are located in northern Jiangxi and northern Zhejiang provinces, and the highest intensity in northern Zhejiang province is even more prominent. The frequency, heat wave days and intensity showed a general increasing trend in the past 50 years, while decadal characteristics are also observed with a decreasing trend from the 1960s to the early 1980s and increasing trend from the end of the 1980s to 2010. The regional variations demonstrate a significant increasing trend in the northern and western parts of North China, central-northern part of Northwest China, the central part of South China, the Yangtze River Delta and the southern Sichuan Basin, with an obvious decreasing trend in the southern Huanghuai area, northern Jianghuai area and Hanjiang River Basin. Citation: Ye, D.-X., Yin, J.-F.,Chen, Z.-H., et al., 2014. Spatial and temporal variations of heat waves in China from 1961 to 2010. Adv. Clim. Change Res. 5(2), doi: 10.3724/SP.J.1248.2014.066