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Spatial inequalities in cancer management have been evidenced by studies reporting lower quality of care or/and lower survival for patients living in remote or socially deprived areas. NETSARC+ is a national reference network implemented to improve the outcome of sarcoma patients in France since 2010, providing remote access to specialized diagnosis and Multidisciplinary Tumour Board (MTB). The IGéAS research program aims to assess the potential of this innovative organization, with remote management of cancers including rare tumours, to go through geographical barriers usually impeding the optimal management of cancer patients.
Using the nationwide NETSARC+ databases, the individual, clinical and geographical determinants of the access to sarcoma-specialized diagnosis and MTB were analysed. The IGéAS cohort (n = 20,590) includes all patients living in France with first sarcoma diagnosis between 2011 and 2014. Early access was defined as specialised review performed before 30 days of sampling and as firstn, designed to improve the access to specialized services and the quality of cancer management, can be considered as an interesting device to reduce social and spatial inequalities in cancer management. The potential of this organization must be confirmed by further studies, including survival analysis.
In the context of national organization driven by reference network, distance to reference centres slightly alters the early access to sarcoma specialized services and social deprivation has no impact on it. The reference networks' organization, designed to improve the access to specialized services and the quality of cancer management, can be considered as an interesting device to reduce social and spatial inequalities in cancer management. The potential of this organization must be confirmed by further studies, including survival analysis.
Survival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards (PH) across different covariates. PH assumptions should be assessed and handled if violated. Our aim was to investigate the reporting of the Cox regression model details and testing of the PH assumption in survival analysis in total joint arthroplasty (TJA) studies.
We conducted a review in the PubMed database on 28th August 2019. A total of 1154 studies were identified. The abstracts of these studies were screened for words "cox and "hazard*" and if either was found the abstract was read. The abstract had to fulfill the following criteria to be included in the full-text phase topic was knee or hip TJA surgery; survival analysis was used, and hazard ratio reported. If all the presented criteria were met, the full-text version of the article was then read. The full-tauses of non-proportionality, such as possible underlying pathomechanisms, are not considered and discussed.
The purpose of this study was to determine the validity of the ultrasound features as well as patient characteristics assigned to B3 (uncertain malignant potential) breast lesions before vacuum-assisted excision biopsy (VAEB).
This study population consisted of 2245 women with breast-nodular abnormalities, which were conducted ultrasound-guided VAEB (US-VAEB). Patient's clinical and anamnestic data and lesion-related ultrasonic feature variables of B3 captured before US-VAEB were compared with those of benign or malignant cases, using histopathological results as a benchmark.
The proportions of benign, B3 and malignant breast lesions diagnosed post-US-VAEB were 88.5, 8.2 and 3.4% respectively. B3 high frequent occurred in BI-RADS-US grade 3 (7.7%), grade 4a (11.0%) and grade 4b (9.1%). The overall malignancy underestimation rate of B3 was 4.4% (8/183). Malignant lesions were found mostly in the range of BI-RADS grade 4b (27.3%), grade 4c (33.3%) and grade 5 (100%). Multivariate binary logistic regressio to reduce malignancy underestimation of B3.
Identifying county-level characteristics associated with high coronavirus 2019 (COVID-19) burden can help allow for data-driven, equitable allocation of public health intervention resources and reduce burdens on health care systems.
Synthesizing data from various government and nonprofit institutions for all 3142 United States (US) counties, we studied county-level characteristics that were associated with cumulative and weekly case and death rates through 12/21/2020. We used generalized linear mixed models to model cumulative and weekly (40 repeated measures per county) cases and deaths. Cumulative and weekly models included state fixed effects and county-specific random effects. Weekly models additionally allowed covariate effects to vary by season and included US Census region-specific B-splines to adjust for temporal trends.
Rural counties, counties with more minorities and white/non-white segregation, and counties with more people with no high school diploma and with medical comorbidities were assoation policies to different US counties.
Encounters with rats in urban areas increase risk of human exposure to rat-associated zoonotic pathogens and act as a stressor associated with psychological distress. The frequency and nature of human-rat encounters may be altered by social distancing policies to mitigate the COVID-19 pandemic. For example, restaurant closures may reduce food availability for rats and promote rat activity in nearby residential areas, thus increasing public health risks during a period of public health crisis. CPYPP chemical structure In this study, we aimed to identify factors associated with increased perceived exposure to rats during a stay-at-home order, describe residents' encounters with rats relevant to their health and well-being, and identify factors associated with increased use of rodent control.
Urban residents in Chicago, a large city with growing concerns about rats and health disparities, completed an online questionnaire including fixed response and open-ended questions during the spring 2020 stay-at-home order. Analyses included ordinal multivariate regression, spatial analysis, and thematic analysis for open-ended responses.
