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111.
112.
Objective
To explore from a gender perspective the association with subjective health of the interaction between education and household arrangements within the framework of social determinants of health placed at the micro and mezzo levels.Methods
The data comes from the Spanish sample of the European Union Statistics on Income and Living Conditions for 2014. Independent logistic regression models for men and women were run to analyze the association with subjective health of the interaction between education and household arrangements. An additive model was run to assess possible advantages over the interaction approach.Results
The interaction models show a lower or even no significant effect on health of household arrangements usually negatively associated with health among individuals with high education, displaying specific patterns according to sex.Conclusions
Health profiles of women and men are more precisely drawn if both social determinants of health are combined. Among the women, the important role was confirmed of both social determinants of health in understanding their health inequalities. Among the men, mainly those with low educational achievement, the interaction revealed that the household was a more meaningful social determinant of health. This could enable the definition of more efficient public policies to reduce health and gender inequalities. 相似文献113.
114.
Grulois Daphné Tiavouane Josina Dumas Pascal Paul Fauvelot Cécile 《Conservation Genetics Resources》2015,7(1):73-75
Conservation Genetics Resources - Fifteen polymorphic microsatellite markers were developed for Tridacna maxima in order to assess self-recruitment and larval dispersal within and among MPAs in New... 相似文献
115.
J. Rodríguez-Carrio A. Martínez-Zapico I. Cabezas-Rodríguez L. Benavente Á.I. Pérez-Álvarez P. López J.B. Cannata-Andía M. Naves-Díaz A. Suárez 《Nutrition, metabolism, and cardiovascular diseases : NMCD》2019,29(2):135-143
Background and aims
Since accelerated atherosclerosis has been reported in systemic lupus erythematosus (SLE), predictive biomarkers of cardiovascular disease (CVD) are needed. Among non-traditional risk factors, bone mineral density (BMD) has been related to CVD. However, its role in SLE remains controversial. This study aims to analyze the associations of subclinical atherosclerosis with traditional and non-traditional CV risk factors.Methods and results
In a cross-sectional study, atherosclerosis burden was compared between 112 female SLE patients and 31 controls. Plaque number and carotid intima-media wall thickness (cIMT) were assessed by ultrasonography. In a retrospective study, BMD determinations obtained 5-years before the ultrasonography assessment were analyzed in a subgroup of 62 patients. Plaque frequency was increased in SLE, even in patients without CV events or carotid wall thickening. cIMT was increased in patients with CVD, positively correlated with body mass index (BMI). Interestingly, a paradoxical effect of BMI on carotid parameters was observed. Whereas underweight patients (BMI < 20) showed increased prevalence of carotid plaques with low cIMT, those with BMI > 30 showed higher cIMT and plaque burden. Overweight patients (25 < BMI<30) exhibited both elevated cIMT and plaque number. BMI was an independent predictor of BMD. In our retrospective study, patients with either clinical or subclinical CVD exhibited lower BMD levels than their CV-free counterparts. A low lumbar spine BMD independently predicted CVD development after adjusting for confounders.Conclusion
SLE was associated with a higher subclinical atherosclerosis burden, a bimodal effect being observed for BMI. Decreased BMD can be a CV risk biomarker in SLE. 相似文献116.
117.
Giorgio Gandaglia Guillaume Ploussard Massimo Valerio Agostino Mattei Cristian Fiori Nicola Fossati Armando Stabile Jean-Baptiste Beauval Bernard Malavaud Mathieu Roumiguié Daniele Robesti Paolo Dell’Oglio Marco Moschini Stefania Zamboni Arnas Rakauskas Francesco De Cobelli Francesco Porpiglia Francesco Montorsi Alberto Briganti 《European urology》2019,75(3):506-514
Background
Available models for predicting lymph node invasion (LNI) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP) might not be applicable to men diagnosed via magnetic resonance imaging (MRI)-targeted biopsies.Objective
To assess the accuracy of available tools to predict LNI and to develop a novel model for men diagnosed via MRI-targeted biopsies.Design, setting, and participants
A total of 497 patients diagnosed via MRI-targeted biopsies and treated with RP and extended pelvic lymph node dissection (ePLND) at five institutions were retrospectively identified.Outcome measurements and statistical analyses
Three available models predicting LNI were evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses. A nomogram predicting LNI was developed and internally validated.Results and limitations
Overall, 62 patients (12.5%) had LNI. The median number of nodes removed was 15. The AUC for the Briganti 2012, Briganti 2017, and MSKCC nomograms was 82%, 82%, and 81%, respectively, and their calibration characteristics were suboptimal. A model including PSA, clinical stage and maximum diameter of the index lesion on multiparametric MRI (mpMRI), grade group on targeted biopsy, and the presence of clinically significant PCa on concomitant systematic biopsy had an AUC of 86% and represented the basis for a coefficient-based nomogram. This tool exhibited a higher AUC and higher net benefit compared to available models developed using standard biopsies. Using a cutoff of 7%, 244 ePLNDs (57%) would be spared and a lower number of LNIs would be missed compared to available nomograms (1.6% vs 4.6% vs 4.5% vs 4.2% for the new nomogram vs Briganti 2012 vs Briganti 2017 vs MSKCC).Conclusions
Available models predicting LNI are characterized by suboptimal accuracy and clinical net benefit for patients diagnosed via MRI-targeted biopsies. A novel nomogram including mpMRI and MRI-targeted biopsy data should be used to identify candidates for ePLND in this setting.Patient summary
We developed the first nomogram to predict lymph node invasion (LNI) in prostate cancer patients diagnosed via magnetic resonance imaging-targeted biopsy undergoing radical prostatectomy. Adoption of this model to identify candidates for extended pelvic lymph node dissection could avoid up to 60% of these procedures at the cost of missing only 1.6% patients with LNI. 相似文献118.
Renaud Snanoudj Nassim Kamar Elisabeth Cassuto Sophie Caillard Marie Metzger Pierre Merville Antoine Thierry Isabelle Jollet Philippe Grimbert Dany Anglicheau Marc Hazzan Gabriel Choukroun Bruno Hurault De Ligny Bénedicte Janbon Vincent Vuiblet Anne Devys Yann Le Meur Michel Delahousse Jean-Luc Taupin 《Kidney international》2019,95(6):1471-1485
119.
Julie A. Schmidt Georgina K. Fensom Sabina Rinaldi Augustin Scalbert Paul N. Appleby David Achaintre Audrey Gicquiau Marc J. Gunter Pietro Ferrari Rudolf Kaaks Tilman Kühn Heiner Boeing Antonia Trichopoulou Anna Karakatsani Eleni Peppa Domenico Palli Sabina Sieri Rosario Tumino Bas Bueno-de-Mesquita Antonio Agudo Maria-Jose Sánchez María-Dolores Chirlaque Eva Ardanaz Nerea Larrañaga Aurora Perez-Cornago Nada Assi Elio Riboli Konstantinos K. Tsilidis Timothy J. Key Ruth C. Travis 《International journal of cancer. Journal international du cancer》2020,146(3):720-730
Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer. 相似文献
120.