Rural-Urban Residence and Stroke Risk and Severity in Postmenopausal Women: The Women's Health Initiative

Background: The impact of rural-urban residence on stroke risk and poor stroke outcomes among postmenopausal women is unknown. Methods: We used data from the Women's Health Initiative (WHI) (1993-2014; n = 155,186) to test the hypothesis that women who live in rural compared with urban areas have higher stroke risk and worse stroke outcomes than urban women. We used rural-urban commuting area codes to categorize geocoded participant addresses into urban, large rural, or small rural areas. Incident strokes during follow-up were adjudicated by neurologists who used standardized criteria for reviewing brain imaging reports and other medical records and determining stroke subtype. Stroke functional recovery was measured with the Glasgow Stroke Outcomes Scale ascertained from the hospital record. We used univariable and multivariable-adjusted Cox proportional hazards models as well as logistic regression models to test whether rural-urban residence predicted stroke risk and odds of poor stroke outcome. Results: Among the 155,186 women in our cohort, 2.3% (n = 3514) had an incident stroke. We observed a modest reduction in risk of incident stroke among women who lived in urban (adjusted hazard ratio [aHR]: 0.86, confidence interval [95% CI]: 0.71-1.05) and large rural areas (aHR: 0.79, 95% CI: 0.60-1.04) compared with women who lived in small rural areas. In contrast, women who lived in urban compared with large rural areas had a similarly modest increased risk of stroke (aHR: 1.09, 95% CI: 0.89-1.32). Women who lived in urban compared with large rural areas were more likely to have poor stroke outcome (odds ratio [OR]: 1.41, 95% CI: 1.06-1.88), but the association was attenuated after adjustment for covariates (adjusted OR [aOR]: 1.27, 0.93-1.74). Conclusions: Future studies should confirm and examine the potential pathways of the reported associations among postmenopausal women

Rural-urban residence and stage at breast cancer diagnosis among postmenopausal women: The women's health initiative

Background: Although social exposures have complex and dynamic relationships and interactions, the existing literature on the impact of rural-urban residence on stage at breast cancer diagnosis does not examine heterogeneity of effect. We examined the joint effect of social support, social relationship strain, and rural-urban residence on stage at breast cancer diagnosis. Methods: Using data from the Women's Health Initiative (WHI) (n = 161,808), we describe the distribution of social, behavioral, and clinical factors by rural-urban residence among postmenopausal women with incident breast cancer (n = 7,120). We used rural-urban commuting area (RUCA) codes to categorize baseline residential addresses as urban, large rural city/town, or small rural town, and the surveillance, epidemiology, and end results staging system to categorize breast cancer stage at diagnosis (dichotomized as early or late). We then used univariable and multivariable logistic regression to estimate odds ratios (ORs) and associated 95% confidence intervals (95% CI) for the relationship between rural-urban residence and stage at breast cancer diagnosis. We included separate interaction terms between rural-urban residence and social strain and social support to test for statistical interaction. Results: Of the social, behavioral, and clinical factors we examined, only younger age at WHI enrollment screening was significantly associated with late stage at breast cancer diagnosis (p = 0.003). Contrary to our hypothesis, rural-urban residence was not significantly associated with stage at breast cancer diagnosis among postmenopausal women ([adjusted OR, 95% CI] for urban compared with small town: 1.08 [0.76-1.53]; large town compared with small town: 1.16 [0.74-1.84]; and urban compared with large town: 0.93 [0.68-1.26]).The associations did not vary by social support or social strain (p for interaction between RUCA and social strain and social support, respectively: 0.99 and 0.17). Conclusions: Future studies should examine other potential effect modifiers to identify novel factors predictive or protective for late stage at breast cancer diagnosis associated with rural-urban residence

Reasoning About Systems with Transition Fairness

Abstract. Formal verification methods model systems by Kripke structures. In order to model live behaviors of systems, Kripke structures are augmented with fairness conditions. Such conditions partition the computations of the systems into fair computations, with respect to which verification proceeds, and unfair computations, which are ignored. Reasoning about Kripke structures augmented with fairness is typically harder than reasoning about non-fair Kripke structures. We consider the transition fairness condition, where a computation π is fair iff each transition that is enabled in π infinitely often is also taken in π infinitely often. Transition fairness is a natural and useful fairness condition. We show that reasoning about Kripke structures augmented with transition fairness is not harder than reasoning about non-fair Kripke structures. We demonstrate it for fair CTL and LTL model checking, and the problem of calculating the dominators and postdominators.

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival