Low-risk Regions Research Articles

Gastric Cancer Risk among Immigrants and Socioeconomic Groups in the Netherlands.

Identification of groups at a high-risk of gastric cancer (GC) could facilitate targeted screening in countries with a low GC incidence. Our aim was to identify such high-risk groups, based on individual-level population data on migration history and socioeconomic status (SES) in the Netherlands. In this retrospective cohort study, patient data from the Netherlands cancer registry were linked to demographic data of Statistics Netherlands in the period 2010-2022. GC incidence rates in the 14 largest immigrant populations were compared to those born in the Netherlands. Odds ratios (ORs) were computed per birthplace and controlled for age, sex and SES. Additionally, we investigated GC risk among second-generation immigrants and by SES. Immigrant populations at a significantly higher GC risk compared to the general population were identified. Specifically, foreign-born first-generation immigrants from Bosnia-Herzegovina (OR: 2.42), Turkey (OR: 2.22) and China (OR: 1.92) showed elevated risk. While low SES increased the odds of developing GC, first-generation immigrants remained at higher risk even after controlling for SES. Second-generation immigrants did not have a significantly higher risk of developing GC. Certain first-generation immigrants remain at an elevated risk for GC despite migration to a low-risk region. Identification of these high-risk groups should be used to facilitate targeted GC prevention. Potential benefits of targeted Helicobacter pylori test-and-treat policy in immigrant populations should be explored in clinical and modelling studies. Primary care physicians should be cognizant of high-risk groups, facilitating the early-detection of cancer within these populations.

Estimation of individual lifetime cardiovascular disease risk and treatment benefit in patients with established atherosclerotic cardiovascular disease: the updated SMART-REACH2 model

Abstract Background The 2021 ESC Guidelines on Cardiovascular Disease (CVD) Prevention in Clinical Practice recommend using (lifetime) risk to guide preventive treatment intensification. Purpose Updating and systematically recalibrating the SMART-REACH lifetime prediction model for the estimation of lifetime risk of recurrent CVD in patients with established atherosclerotic CVD (ASCVD) to various European and international risk regions. Methods The updated SMART-REACH (i.e., SMART-REACH2) model was derived using data from 9,477 individuals between 40-90 years with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms included in the UCC-SMART cohort in whom 2,090 ASCVD events were observed during a median follow-up of 8.9 years (interquartile range 4.5–14.1). Coefficients for type of CVD, estimated glomerular filtration rate, non-high density lipoprotein cholesterol, systolic blood pressure, duration of CVD, C-reactive protein, current smoking, and presence of diabetes were derived using sex-stratified cause-specific Cox models with age as the time axis, adjusted for the competing risk of non-CVD mortality. Lifetables were used to estimate 10-year and lifetime CVD-risk and CVD-free life expectancy. The SMART-REACH2 model was externally validated in 121,701 patients from the NOR-COR, Nor-COAST, HUNT3, SWEDEHEART, Bialystok PLUS/Polaspire, REACH-EU, and REACH non-EU (Asia, Japan, Latin America, North America) covering 43 countries. The model was recalibrated to specific risk regions based on the expected-observed ratios from representative cohorts. Performance was assessed by calibration of predicted and observed risk and Harrel’s C-statistic for discrimination. Results 16,689ASCVD events were observed in the external validation cohorts. The model was visually well calibrated for the various risk regions. The pooled C-statistic across risk regions was 0.665 [95% confidence interval 0.640-0.691], with adequate performance in the separate regions (Figure 1). Using SMART-REACH2 to estimate potential gain in CVD-free life expectancy upon treatment initiation showed varying projections. For example, two comparable 55-year-old males from the low-risk region and very high-risk region would gain an estimated 2.2 and 3.9 CVD-free life years as a result of smoking cessation (Figure 2). Conclusion(s) By using larger and more contemporary data sources, considering geographical differences, and extending the age range, the updated SMART-REACH2 model provides an improved algorithm for the estimation of lifetime risk and CVD-free life expectancy for individuals with established ASCVD, facilitating shared decision-making for cardiovascular prevention as recommended by the 2021 ESC Prevention of CVD guidelines.C-statistics across global risk regionsCase vignette

Implications of five different risk models in primary prevention guidelines

Abstract Background A lack of consensus exists across guidelines as to which risk model should be used for the primary prevention of cardiovascular disease (CVD). Purpose The objective of this study was to determine potential improvements in the number needed to treat (NNT) with statins using different risk models in patients eligible for risk stratification. Methods A retrospective observational cohort was assembled from primary care patients in Ontario, Canada between January 1st, 2010, to December 31st, 2014 and followed for up to 5 years. Risk estimation was undertaken in patients 40-75 years of age, without CVD, diabetes, or chronic kidney disease using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCEs), a recalibrated FRS (R-FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and the low-risk region recalibrated SCORE2 (LR-SCORE2). Results The cohort consisted of 47,399 patients (59% women, mean age 54). The NNT at 5 years with statins was lowest for SCORE2 at 40, followed by LR-SCORE2 at 41, R-FRS at 43, PCEs at 55, and FRS at 65. Models that selected for individuals with a lower NNT recommended statins to fewer, but higher risk patients. For instance, SCORE2 recommended statins to 7.9% of patients (5-year CVD incidence 5.92%). The FRS, however, recommended statins to 34.6% of patients (5-year CVD incidence 4.01%; Figure). Conclusions Newer models such as SCORE2 may improve statin allocation to higher risk groups with a lower NNT.Figure

Expansion or retrenchment: Corporate investment reactions to external security risks

Intensifying power competition has raised the need to understand how corporations react to international security dynamic challenges. Using data on Chinese A-share listed companies from 2012 to 2022, we developed an index to measure external security risk and empirically study the influence of external security risks on corporate investment behavior. These findings indicate that corporations reduce real investment and increase financial asset allocation when external security risk is high. Meanwhile, corporations tend to expand overseas investments to enhance international diversification and turn toward low-risk regions. The technology and strategic emerging sectors exhibit a higher preference for real investment during periods of high external security risk. Furthermore, entrepreneurs’ family-nation sentiment can inhibit corporate financial investment and promote real investment. This study contributes to understanding how the external security environment shapes corporate investment strategies. It also demonstrates how entrepreneurial spirit can influence corporate investment decisions during periods of high security risk.

Assessment of coastal vulnerability using AHP and machine learning techniques

Vila Belmiro is a significant development in the coastal urban scenario and is nestled along the rugged cliffs of the southern coast of Brazil. Cyclones caused tremendous damage to the shore, destroying infrastructure, eroding the coast, flooding, and displacing people. Determining such low-lying regions' coastal vulnerability index is crucial for developing efficient mitigation strategies and enhancing readiness for calamities. In light of this viewpoint, the current study attempted to determine the Coastal Vulnerability Index (CVI) using the analytical hierarchical process (AHP). The study combined the Physical Vulnerability Index (PVI) and the Social Vulnerability Index (SVI) to create the Coastal Vulnerability Index. This study generated the LULC layer for Vila Belmiro using machine learning techniques and Random Forest based model. A component of the process was evaluating the parameters pairwise based on their importance and relevance to the study's objective. The CVI assessment classified 19.28 Sq.km of the coastline, including Solemar, São Vicente, Santo, and Ponta Da Praia, as very high risk. High-risk areas, such as São Vicente, Vila Caicara, and Guaruja, span 25.26 Sq.km. Medium risk was observed across 16.85 Sq.km, covering Praia Grande, Nova Mirim, and Balneario Praia. Low-risk regions, including Japui and Jarfim Guaiuba, extend over 13.54 Sq.km. Lastly, 10.78 Sq.km of the coastline, including Canto Do Forte, were classified as very low risk. These measurements highlight the varying levels of vulnerability along the coastline. The study concluded that coastal vulnerability zones were effectively identified and assessed, enhancing understanding and management of coastal risks. Planning and mitigating future cyclones can benefit from the identified vulnerable zones. The current study included machine learning, remote sensing, Geographic Information System (GIS), and advanced facilities that were spatially integrated with AHP approaches.

Prediction of individual lifetime cardiovascular risk and potential treatment benefit: development and recalibration of the LIFE-CVD2 model to four European risk regions.

The 2021 European Society of Cardiology prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding initiation of prevention. We aimed to update and systematically recalibrate the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model to four European risk regions for the estimation of lifetime CVD risk for apparently healthy individuals. The updated LIFE-CVD (i.e. LIFE-CVD2) models were derived using individual participant data from 44 cohorts in 13 countries (687 135 individuals without established CVD, 30 939 CVD events in median 10.7 years of follow-up). LIFE-CVD2 uses sex-specific functions to estimate the lifetime risk of fatal and non-fatal CVD events with adjustment for the competing risk of non-CVD death and is systematically recalibrated to four distinct European risk regions. The updated models showed good discrimination in external validation among 1 657 707 individuals (61 311 CVD events) from eight additional European cohorts in seven countries, with a pooled C-index of 0.795 (95% confidence interval 0.767-0.822). Predicted and observed CVD event risks were well calibrated in population-wide electronic health records data in the UK (Clinical Practice Research Datalink) and the Netherlands (Extramural LUMC Academic Network). When using LIFE-CVD2 to estimate potential gain in CVD-free life expectancy from preventive therapy, projections varied by risk region reflecting important regional differences in absolute lifetime risk. For example, a 50-year-old smoking woman with a systolic blood pressure (SBP) of 140 mmHg was estimated to gain 0.9 years in the low-risk region vs. 1.6 years in the very high-risk region from lifelong 10 mmHg SBP reduction. The benefit of smoking cessation for this individual ranged from 3.6 years in the low-risk region to 4.8 years in the very high-risk region. By taking into account geographical differences in CVD incidence using contemporary representative data sources, the recalibrated LIFE-CVD2 model provides a more accurate tool for the prediction of lifetime risk and CVD-free life expectancy for individuals without previous CVD, facilitating shared decision-making for cardiovascular prevention as recommended by 2021 European guidelines.

Implications of Five Different Risk Models In Primary Prevention Guidelines.

A lack of consensus exists across guidelines as to which risk model should be used for the primary prevention of cardiovascular disease (CVD). Our objective was to determine potential improvements in the number needed to treat (NNT) and number of events prevented (NEP) using different risk models in patients eligible for risk stratification. A retrospective observational cohort was assembled from primary care patients in Ontario, Canada between January 1st, 2010, to December 31st, 2014 and followed for up to 5 years. Risk estimation was undertaken in patients 40-75 years of age, without CVD, diabetes, or chronic kidney disease using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCEs), a recalibrated FRS (R-FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and the low-risk region recalibrated SCORE2 (LR-SCORE2). The cohort consisted of 47,399 patients (59% women, mean age 54). The NNT with statins was lowest for SCORE2 at 40, followed by LR-SCORE2 at 41, R-FRS at 43, PCEs at 55, and FRS at 65. Models that selected for individuals with a lower NNT recommended statins to fewer, but higher risk patients. For instance, SCORE2 recommended statins to 7.9% of patients (5-year CVD incidence 5.92%). The FRS, however, recommended statins to 34.6% of patients (5-year CVD incidence 4.01%). Accordingly, the NEP was highest for the FRS at 406 and lowest for SCORE2 at 156. Newer models such as SCORE2 may improve statin allocation to higher risk groups with a lower NNT but prevent fewer events at the population level.

Integrating ecosystem service value in the disclosure of landscape ecological risk changes: a case study in Yangtze River Economic Belt, China

Urban expansion and inappropriate land uses have caused a decline in the regional ecosystem services capacity, which is contrary to United Nations’ Sustainable Development Goal (SDG) 15 aiming to protect and promote sustainable use of terrestrial ecosystems. Landscape ecological risk (LER) visually depicts the disturbances to ecosystem services and environmental shifts resulting from human activities. Consideration of ecosystem services in LER assessment has not been sufficiently researched. Here, we employed ecosystem service values (ESV) to define landscape vulnerability, and adopted an enhanced risk assessment framework, amalgamating landscape patterns and ecosystem processes, to evaluate the spatial-temporal shifts in ESV and LER in the Yangtze River Economic Belt (YREB) from 2000 to 2020. We attempted to analyze the relationship between LER and anthropogenic disturbances. The results showed that over the past 20 years, the general trend revealed a diminishing high-risk area, while medium and low-risk regions expanded. Notably, the urban agglomeration of the YREB experienced a marked surge in risk. Regarding migration direction, the low-risk category has expanded in the east–west direction, while the medium and high-risk categories have shown inward contraction mainly in the north–south direction. The findings highlight the complex changes between ecological processes and LER under anthropogenic disturbances, and can serve as a guide for sustainable risk management and the development of ecological security patterns.

Fully automatic mpMRI analysis using deep learning predicts peritumoral glioblastoma infiltration and subsequent recurrence.

Glioblastoma (GBM) is most aggressive and common adult brain tumor. The standard treatments typically include maximal surgical resection, followed adjuvant radiotherapy and chemotherapy. However, the efficacy of these treatment is often limited, as tumor often infiltrate into the surrounding brain tissue, often extending beyond the radiologically defined margins. This infiltration contributes to the high recurrence rate and poor prognosis associated with GBM patients, necessitating advanced methods for early and accurate detection of tumor infiltration. Despite the great promise traditional supervised machine learning shows in predicting tumor infiltration beyond resectable margins, these methods are heavily reliant on expert-drawn Regions of Interest (ROIs), which are used to construct multi-variate models of different Magnetic Resonance (MR) signal characteristics associated with tumor infiltration. This process is both time consuming and resource intensive. Addressing this limitation, our study proposes a novel integration of fully automatic methods for generating ROIs with deep learning algorithms to create predictive maps of tumor infiltration. This approach uses pre-operative multi-parametric MRI (mpMRI) scans, encompassing T1, T1Gd, T2, T2-FLAIR, and ADC sequences, to fully leverage the knowledge from previously drawn ROIs. Subsequently, a patch based Convolutional Neural Network (CNN) model is trained on these automatically generated ROIs to predict areas of potential tumor infiltration. The performance of this model was evaluated using a leave-one-out cross-validation approach. Generated predictive maps binarized for comparison against post-recurrence mpMRI scans. The model demonstrates robust predictive capability, evidenced by the average cross-validated accuracy of 0.87, specificity of 0.88, and sensitivity of 0.90. Notably, the odds ratio of 8.62 indicates that regions identified as high-risk on the predictive map were significantly more likely to exhibit tumor recurrence than low-risk regions. The proposed method demonstrates that a fully automatic mpMRI analysis using deep learning can successfully predict tumor infiltration in peritumoral region for GBM patients while bypassing the intensive requirement for expert-drawn ROIs.

Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018.

Large-scale outbreaks of scrub typhus combined with its emergence in new areas as a vector-borne rickettsiosis highlight the ongoing neglect of this disease. This study aims to explore the long-term changes and regional leading factors of scrub typhus in China, with the goal of providing valuable insights for disease prevention and control. This study utilized a Bayesian space-time hierarchical model (BSTHM) to examine the spatiotemporal heterogeneity of scrub typhus and analyze the relationship between environmental factors and scrub typhus in southern and northern China from 2006 to 2018. Additionally, a GeoDetector model was employed to assess the predominant influences of geographical and socioeconomic factors in both regions. Scrub typhus exhibits a seasonal pattern, typically occurring during the summer and autumn months (June to November), with a peak in October. Geographically, the high-risk regions, or hot spots, are concentrated in the south, while the low-risk regions, or cold spots, are located in the north. Moreover, the distribution of scrub typhus is influenced by environment and socio-economic factors. In the north and south, the dominant factors are the monthly normalized vegetation index (NDVI) and temperature. An increase in NDVI per interquartile range (IQR) leads to a 7.580% decrease in scrub typhus risk in northern China, and a 19.180% increase in the southern. Similarly, of 1 IQR increase in temperature reduces the risk of scrub typhus by 10.720% in the north but increases it by 15.800% in the south. In terms of geographical and socio-economic factors, illiteracy rate and altitude are the key determinants in the respective areas, with q-values of 0.844 and 0.882. These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus.

Nodal recurrence mapping and clinical target volumes after resection of intrahepatic cholangiocarcinoma or combined hepatocellular-cholangiocarcinoma

BackgroundScarce evidence exists for clinical target volume (CTV) definitions of regional lymph nodes (LNs) in intrahepatic cholangiocarcinoma (iCCA) or combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We investigated the mapping pattern of nodal recurrence after surgery for iCCA and cHCC-CCA and provided evidence for the nodal CTV definition. MethodsWe retrospectively reviewed the medical records of patients with iCCA or cHCC-CCA who underwent surgery between 2010 and 2020. Eligibility criteria included patients pathologically diagnosed with iCCA or cHCC-CCA after surgery and a first recurrent event in regional LNs during follow-up. All recurrent LNs were registered onto reference computed tomography images based on the vascular structures to reconstruct the node mapping. Fifty-three patients were eligible. LN regions were classified into four risk groups. ResultsHepatic hilar and portal vein-vena cava were the most common recurrent regions, with recurrence rates of 62.3 % and 39.6 % (high-risk regions), respectively. Recurrence rates in the left gastric, diaphragmatic, common hepatic, superior mesenteric vessels, celiac trunk, and paracardial regions ranged from 15.1 % to 30.2 % (intermediate-risk regions). There were fewer recurrences in the para-aortic (16a1, a2, b1) and splenic artery and hilum regions, with rates <10 % (low-risk regions). No LN recurrence was observed in the para-oesophageal or para-aortic region (16b2) (very low-risk regions). Based on node mapping, the CTV should include high- and intermediate-risk regions for pathologically negative LN patients during postoperative radiotherapy. Low-risk regions should be included for pathologically positive LN patients. ConclusionWe provide evidence for CTV delineation in patients with iCCA and cHCC-CCA based on recurrent LN mapping.

Novel Definitive Hypofractionated Accelerated Radiation Dose-painting (HARD) for Unresected Soft Tissue Sarcomas

PurposeSoft tissue sarcomas (STS) are historically radioresistant, with surgery being an integral component of their treatment. With their low α/β, STS may be more responsive to hypofractionated radiotherapy (RT), which is often limited by long-term toxicity risk to surrounding normal tissue. An isotoxic approach utilizing a hypofractionated accelerated radiation dose-painting (HARD) regimen, allows for dosing based on clinical risk, while sparing adjacent organs at risk. Methods and MaterialsWe retrospectively identified patients with unresected STS from 2019 to 2022, who received HARD with dose-painting to high, intermediate, and low risk regions of 3.0 Gy, 2.5 Gy, and 2.0 – 2.3 Gy, respectively, in 20 – 22 fractions. Clinical endpoints included local control, locoregional control, progression free survival, overall survival, and toxicity outcomes. ResultsTwenty-seven consecutive patients were identified and had a median age of 68 years and tumor size of 7.0 cm (range, 1.2 – 21.0 cm). Tumors were most often high grade (70%), stage IV (70%), located in the extremities (59%), and locally recurrent (52%). With a median follow-up of 33.4 months, there was a 3-year locoregional control rate of 100%. The 3-year overall and progression free survival were 44.9% and 23.3%, respectively. There were five (19%) acute and two (7%) late grade 3 toxicities, and there were no grade 4 or 5 toxicities at any point. ConclusionsThe HARD regimen is a safe method of dose escalating STS, with durable 3-year locoregional control. This approach is a promising alternative for unresected STS, though further follow up is required to determine long-term control and toxicity.

Eco-Environmental Risk Assessment and Its Precaution Partitions Based on a Knowledge Graph: A Case Study of Shenzhen City, China

The eco-environment is under constant pressure caused by the rapid pace of urbanization and changes in land use. Shenzhen is a typical “small-land-area, high-density” megalopolis facing various dilemmas and challenges; we must understand the eco-environmental risk (ER) of rapidly urbanizing regions and promote high-quality regional development. Therefore, with the help of the Python and Neo4j platforms, this study applies the theoretical foundation of knowledge graphs (KGs) and deep learning to form the KG of an ER; with this, we sort and establish an evaluation system in two dimensions, namely social and ecological, and introduce the Monte Carlo simulation to quantify the ER in Shenzhen City and its uncertainty from 2000 to 2020 to propose sub-regional programs and targeted measures for the prevention and control of the ER. The results are as follows: The eco-environmental risk index (ERI) of the study area as a whole showed a slight increase from 2000 to 2020; at the same time, the low-risk regions were mainly located in the east and southeast, while the high-risk regions were mainly located in the west–central and northwestern parts. In addition, three sample points (points A, B, and C) were selected using the Monte Carlo method to simulate the transfer of uncertainty from the indicator weights to the assessment results. Finally, based on the quantitative results, an accurate zoning scheme for ER prevention and control was provided to the decision makers, and appropriate countermeasures were proposed.

Generalities on a Delayed Spatiotemporal Host–Pathogen Infection Model with Distinct Dispersal Rates

We propose a general model to investigate the effect of the distinct dispersal coefficients infected and susceptible hosts in the pathogen dynamics. The mathematical challenge lies in the fact that the investigated model is partially degenerate and the solution map is not compact. The spatial heterogeneity of the model parameters and the distinct diffusion coefficients induce infection in the low-risk regions. In fact, as infection dispersal increases, the reproduction of the pathogen particles decreases. The dynamics of the investigated model is governed by the value of the basic reproduction number R0. If R0 ≤ 1, then the pathogen particles extinct, and for R0 &gt; 1 the pathogen particles persist, and there is at least one positive steady state. The asymptotic profile of the positive steady state is shown in the case when one or both diffusion coefficients for the host tends to zero or infinity.

Cardiovascular Risk Scales Association with Cerebrospinal Fluid Alzheimer's Disease Biomarkers in Cardiovascular Low Cardiovascular Risk Regions.

Cardiovascular risk factors are associated with Alzheimer's Disease (AD) development. However, few studies compare the overall cardiovascular risk with AD biomarkers, and when done, they are mainly performed in moderate cardiovascular risk regions. To determine whether cardiovascular risk in older adults is associated with pathological cerebrospinal fluid (CSF) biomarkers of AD in a low cardiovascular risk population. This is a cross-sectional study performed between 2017 and 2020. The present work included patients between 50 and 75 years old who were negative for CSF AD biomarkers and had minimum cognitive alterations (controls) and patients with positive CSF AD biomarkers and in early stages of AD (cases). CSF biomarkers included total tau, phosphorylated tau 181 and amyloid ß42 (Aß42). Analytical variables were obtained. ERICE, SCORE2 and Framingham scales were used to calculate the overall patient's cardiovascular risk. The Aß42/Aß40 ratio and neurofilaments were explored when available. Two hundred and thirty-three patients were included. Nearly 76% of the sample had AD. AD patients had higher cardiovascular risk than controls (p-value < 0.05). ERICE and SCORE2 were associated with AD presence. Framingham was not. A correlation between elevated cardiovascular risk and higher total tau and NfL levels was observed when adjusted by age. Cardiovascular risk assessment may be helpful in neurodegenerative disorders detection, as it is associated with CSF total tau and NfL. ERICE and SCORE2 may be useful scales in low cardiovascular risk regions to improve cardiovascular control and prevent neurodegenerative pathologies.

Geomorphologic risk zoning to anticipate tailings dams' hazards: A study in the Brumadinho's mining area, Minas Gerais, Brazil

The use of tailings dams in the mining industry is recurrent and a matter of concern given the risk of collapse. The planning of tailings dam's emplacement usually attends construction design criteria and site geotechnical properties, but often neglects the risk of installing the depositional facilities in potentially unstable landscapes, namely those characterized by steep slopes and(or) high drainage densities. In order to help bridging this gap, the present study developed a framework model whereby geomorphologic vulnerability is assessed by a set of morphometric parameters (e.g., drainage density; relief ratio; roughness coefficient). Using the Ribeirão Ferro-Carvão micro-basin (3265.16 ha) as test site, where six dams currently receive tailings from the mining of iron-ore deposits in the Brumadinho region (Minas Gerais, Brazil) and one has collapsed in 25 January 2019 (the B1 dam of Córrego do Feijão mine of Vale, S.A.), the risk of dam instability derived from geomorphologic vulnerability was assessed and alternative suitable locations were highlighted when applicable. The results made evident the location of five dams (including the collapsed B1) in high-risk regions and two in low-risk regions, which is preoccupying. The alternative locations represent 58 % of Ribeirão Ferro-Carvão micro-basin, which is a reasonable and workable share. Overall, the study exposed the fragility related with tailings dams' geography, which is not restricted to the studied micro-basin, because dozens of active tailings dams exist in the parent basin (the Paraopeba River basin) that can also be vulnerable to geomorphologically-dependent hydrologic hazards such as intensive erosion, valley incision or flash floods. Attention to this issue is therefore urgent to prevent future tragedies related with tailings dams' breaks, in the Paraopeba River basin or elsewhere, using the proposed framework model as guide.

Randomized Trial of FOLFOX 4 and FOLFIRI in The Treatment of Advance Colorectal Cancer

Colorectal cancer is a major global health concern, ranking third in prevalence and second in mortality. Developed countries have high incidence rates, while Pakistan is considered a low-risk region. Metastatic colorectal cancer requires targeted therapies like FOLFIRI and FOLFOX4, but their effectiveness in Pakistan is unknown. This study aims to provide insights, guide treatment decisions, and expand global understanding in the field. Objective: To compare therapeutic effects of FOLFOX4 and FOLFIRI for advanced colorectal cancer patients. Methods: The Medical Oncology Department of Jinnah Postgraduate and Medical Centre conducted a randomized controlled trial research from May 2022 to February 2023. Hundred patients of advanced colorectal cancer with a confirmed diagnosis of age 18 to 80 years, of either gender, were included. Randomly, 50 of these patients were in FOLFIRI group, and 50 in FOLFOX4 group. Both groups were compared for the treatment outcomes. Results: In the FOLFIRI group, the total response rate was 66%, whereas in the FOLFOX 4 group, it was 78%. In the FOLFIRI group, the median time to progression was 8 months, but in the FOLFOX 4 group, it was 9 months (p=0.06). In the FOLFIRI group, the total median survival time was 13 months, whereas in the FOLFOX 4 group, it was 14 months (p=0.280). Conclusions: The response rates between the two groups were similar, while FOLFOX 4 had a little higher rate of tumor control. FOLFIRI had a lower incidence of neutropenia, whereas FOLFOX 4 had a lower incidence of nausea and vomiting.

Epidemiology, risk areas and macro determinants of gastric cancer: a study based on geospatial analysis

BackgroundBoth incidence and mortality of gastric cancer in Gansu rank first in china, this study aimed to describe the recent prevalence of gastric cancer and explore the social and environmental determinants of gastric cancer in Gansu Province.MethodsThe incidence of gastric cancer in each city of Gansu Province was calculated by utilizing clinical data from patients with gastric cancer (2013–2021) sourced from the medical big data platform of the Gansu Province Health Commission, and demographic data provided by the Gansu Province Bureau of Statistics. Subsequently, we conducted joinpoint regression analysis, spatial auto-correlation analysis, space–time scanning analysis, as well as an exploration into the correlation between social and environmental factors and GC incidence in Gansu Province with Joinpoint_5.0, ArcGIS_10.8, GeoDa, SaTScanTM_10.1.1 and GeoDetector_2018.ResultsA total of 75,522 cases of gastric cancer were included in this study. Our findings suggested a significant upward trend in the incidence of gastric cancer over the past nine years. Notably, Wuwei, Zhangye and Jinchang had the highest incidence rates while Longnan, Qingyang and Jiayuguan had the lowest. In spatial analysis, we have identified significant high-high cluster areas and delineated two high-risk regions as well as one low-risk region for gastric cancer in Gansu. Furthermore, our findings suggested that several social and environmental determinants such as medical resource allocation, regional economic development and climate conditions exerted significant influence on the incidence of gastric cancer.ConclusionsGastric cancer remains an enormous threat to people in Gansu Province, the significant risk areas, social and environmental determinants were observed in this study, which may improve our understanding of gastric cancer epidemiology and help guide public health interventions in Gansu Province.

Impact of the stepwise approach to cardiovascular disease prevention in patients with established ASCVD from the 2021 ESC Prevention Guideline

Abstract Background The European Society of Cardiology (ESC) 2021 Guidelines on Cardiovascular Disease Prevention in Clinical Practice advocate a stepwise approach for the treatment of cardiovascular (CV) risk factors to reduce CV-risk in patients with established atherosclerotic cardiovascular disease (ASCVD). The aim of this study was to evaluate CV-risk reduction and residual risk for recurrent CV-events based on stepwise risk factor management. Methods In patients with established ASCVD in the UCC-SMART (n = 8,997) and European parts of the REACH registry (n = 18,364) receiving usual care, 10-year risk of recurrent major CV-events was calculated using the SMART2 risk score. The effect of guideline recommended step 1 and 2 treatment options on this risk was modelled using best available evidence from meta-analyses and trials. Step 1 treatment recommendations were smoking cessation, use an antithrombotic drug, LDL cholesterol &amp;lt;1.8 mmol/L, systolic blood pressure (SBP) &amp;lt;140 to 130 mmHg, and in people with type 2 diabetes mellitus a GLP1-receptor agonist/SGLT2-inhibitor. Step 2 treatment recommendations studied were LDL cholesterol &amp;lt;1.4 mmol/L, SBP &amp;lt;130 mmHg, dual pathway inhibition, colchicine, eicosapentaenoic acid (EPA), and in people with type 2 diabetes mellitus a GLP1-receptor agonist/SGLT2-inhibitor in people with type 2 diabetes. Two scenarios were evaluated: one with perfect attainment (ideal) and one with empiric attainment rates (realistic). Results The baseline median 10-year residual CV-risk was 26% [14-41%] overall, and 20%, 27%, and 54% in the low, moderate, and pooled high and very high European risk regions, respectively. Baseline risk was lowest in patients with only coronary artery disease and highest in patients with polyvascular disease or comorbid diabetes mellitus. In the ideal scenario, CV-risk was reduced to 14% [9-22%] overall and, 11%, 15%, and 29% following step 1 and 6% [4-10], 5%, 9%, and 12% following step 2. In the realistic scenario, CV-risk was reduced to 24% [16-36%], 20%, 24, and 47% following step 1 and 10% [7-16%], 9%, 9%, and 19% following step 2. In the ideal scenario, 43%, 22% and 4% achieved a residual risk of &amp;lt;10% following step 1 and 87%, 83% and 38% following step 2 in each respective risk region. In the realistic scenario this was 7%, 1%, and 0% after step 1 and 59%, 56%, and 13% after step 2 (Figure shows the realistic scenario for the low risk region &amp; moderate risk region). Conclusion Despite the current standard of care, patients with established ASCVD remain at high residual CV-risk across all European risk regions. Step 1 treatment targets may lower this risk substantially, but only if attainment rates are higher than empirically achieved. Intensified Step 2 treatment options result in marked further reduction of residual CV-risk and should be encouraged to be considered in all patients with established ASCVD.Realistic scenario low risk regionRealistic scenario moderate risk region

Validation of the European SCORE2 models in a Canadian primary care cohort.

Systematic Coronary Risk Evaluation Model 2 (SCORE2) was recently developed to predict atherosclerotic cardiovascular disease (ASCVD) in Europe. Whether these models could be used outside of Europe is not known. The objective of this study was to test the validity of SCORE2 in a large Canadian cohort. A primary care cohort of persons with routinely collected electronic medical record data from 1 January 2010 to 31 December 2014, in Ontario, Canada, was used for validation. The SCORE2 models for younger persons (YP) were applied to 57 409 individuals aged 40-69 while the models for older persons (OPs) were applied to 9885 individuals 70-89 years of age. Five-year ASCVD predictions from both the uncalibrated and low-risk region recalibrated SCORE2 models were evaluated. The C-statistic for SCORE2-YP was 0.74 in women and 0.69 in men. The uncalibrated SCORE2-YP overestimated risk by 17% in women and underestimated by 2% in men. In contrast, the low-risk region recalibrated model demonstrated worse calibration, overestimating risk by 100% in women and 36% in men. The C-statistic for SCORE2-OP was 0.64 and 0.62 in older women and men, respectively. The uncalibrated SCORE2-OP overestimated risk by more than 100% in both sexes. The low-risk region recalibrated model demonstrated improved calibration but still overestimated risk by 60% in women and 13% in men. The performance of SCORE2 to predict ASCVD risk in Canada varied by age group and depended on whether regional calibration was applied. This underscores the necessity for validation assessment of SCORE2 prior to implementation in new jurisdictions.