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BackgroundResearch suggests that geographic location may affect ovarian cancer (OC) outcomes. Insurance status often remains an important predictor of outcomes. The Affordable Care Act was enacted in 2010 to expand access to affordable health insurance. Our objective was to examine spatiotemporal trends in OC treatment nonadherence and disease-specific mortality in California (USA) among women diagnosed with OC.MethodsNewly diagnosed epithelial OC cases between 1996 and 2017 were identified from the California Cancer Registry. Spatiotemporal trends in adherence to treatment guidelines were examined using generalized additive models and OC-specific mortality using Cox proportional hazards additive models. Prediction grids covering California were used to display the odds ratios (ORs) and hazard ratios of location using the median value for the study area as the referent value. Seven overlapping 5-year periods and 2 larger ones (pre- and post-2013) were assessed. Analyses were stratified according to stage (early vs advanced) and used P = .05 to determine statistical significance.ResultsStatistically significant spatial patterns in treatment nonadherence were observed for every time period examined (P

ObjectiveTo examine whether exposure to ambient ozone, particulate matter with diameter less than 2.5 μm (PM2.5), nitrogen dioxide (NO2), and distance to major roadways (DTR) impact ovarian cancer-specific survival, while considering differences by stage, race/ethnicity, and socioeconomic status.MethodsWomen diagnosed with epithelial ovarian cancer from 1996 to 2014 were identified through the California Cancer Registry and followed through 2016. Women's geocoded addresses were linked to pollutant exposure data and averaged over the follow-up period. Pollutants were considered independently and in multi-pollutant models. Cox proportional hazards models assessed hazards of disease-specific death due to environmental exposures, controlling for important covariates, with additional models stratified by stage at diagnosis, race/ethnicity and socioeconomic status.ResultsPM2.5 and NO2, but not ozone or DTR, were significantly associated with survival in univariate models. In a multi-pollutant model for PM2.5, ozone, and DTR, an interquartile range increase in PM2.5 (Hazard Ratio [HR], 1.45; 95% Confidence Interval [CI], 1.41-1.49) was associated with worse prognosis. Similarly, in the multi-pollutant model with NO2, ozone, and DTR, women with higher NO2 exposures (HR for 20.0-30.0 ppb, 1.30; 95% CI, 1.25-1.36 and HR for >30.0 ppb, 2.48; 95% CI, 2.32-2.66) had greater mortality compared to the lowest exposed (

BackgroundEvidence suggests that geographic location may independently contribute to ovarian cancer survival. We aimed to investigate how the association between residential location and ovarian cancer-specific survival in California varies by race/ethnicity and socioeconomic status.MethodsAdditive Cox proportional hazard models were used to predict hazard ratios (HRs) and 95% confidence intervals (CI) for the association between geographic location throughout California and survival among 29,844 women diagnosed with epithelial ovarian cancer between 1996 and 2014. We conducted permutation tests to determine a global P-value for significance of location. Adjusted analyses considered distance traveled for care, distance to closest high-quality-of-care hospital, and receipt of National Comprehensive Cancer Network guideline care. Models were also stratified by stage, race/ethnicity, and socioeconomic status.ResultsLocation was significant in unadjusted models (P = 0.009 among all stages) but not in adjusted models (P = 0.20). HRs ranged from 0.81 (95% CI: 0.70, 0.93) in Southern Central Valley to 1.41 (95% CI: 1.15, 1.73) in Northern California but were attenuated after adjustment (maximum HR = 1.17, 95% CI: 1.08, 1.27). Better survival was generally observed for patients traveling longer distances for care. Associations between survival and proximity to closest high-quality-of-care hospitals were null except for women of lowest socioeconomic status living furthest away (HR = 1.22, 95% CI: 1.03, 1.43).ConclusionsOverall, geographic variations observed in ovarian cancer-specific survival were due to important predictors such as receiving guideline-adherent care. Improving access to expert care and ensuring receipt of guideline-adherent treatment should be priorities in optimizing ovarian cancer survival.

ObjectiveTo validate the observed/expected ratio for adherence to ovarian cancer treatment guidelines as a risk-adjusted measure of hospital quality care, and to identify patient characteristics associated with disparities in access to high-performing hospitals.MethodsThis was a retrospective population-based study of stage I-IV invasive epithelial ovarian cancer reported to the California Cancer Registry between 1996 and 2014. A fit logistic regression model, which was risk-adjusted for patient and disease characteristics, was used to calculate the observed/expected ratio for each hospital, stratified by hospital annual case volume. A Cox proportional hazards model was used for survival analyses, and a multivariable logistic regression model was used to identify independent predictors of access to high-performing hospitals.ResultsThe study population included 30,051 patients who were treated at 426 hospitals: low observed/expected ratio (n=304) 23.5% of cases; intermediate observed/expected ratio (n=92) 57.8% of cases; and high observed/expected ratio (n=30) 18.7% of cases. Hospitals with high observed/expected ratios were significantly more likely to deliver guideline-adherent care (53.3%), compared with hospitals with intermediate (37.8%) and low (27.5%) observed/expected ratios (P

BACKGROUND:More than 14,000 women in the United States die of ovarian cancer (OC) every year. Disparities in survival have been observed by race and socioeconomic status (SES), and vary spatially even after adjusting for treatment received. This study aimed to determine the impact of geographic location on receiving treatment adherent to the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for OC, independent of other predictors. PATIENTS AND METHODS:Women diagnosed with all stages of epithelial OC (1996-2014) were identified through the California Cancer Registry. Generalized additive models, smoothing for residential location, were used to calculate adjusted odds ratios (ORs) and 95% CIs for receiving nonadherent care throughout California. We assessed the impact of distance traveled for care, distance to closest high-quality hospital, race/ethnicity, and SES on receipt of quality care, adjusting for demographic and cancer characteristics and stratifying by disease stage. RESULTS:Of 29,844 patients with OC, 11,419 (38.3%) received guideline-adherent care. ORs for nonadherent care were lower in northern California and higher in Kern and Los Angeles counties. Magnitudes of associations with location varied by stage (OR range, 0.45-2.19). Living farther from a high-quality hospital increased the odds of receiving nonadherent care (OR, 1.18; 95% CI, 1.07-1.29), but travel >32 km to receive care was associated with decreased odds (OR, 0.76; 95% CI, 0.70-0.84). American Indian/other women were more likely to travel greater distances to receive care. Women in the highest SES quintile, those with Medicare insurance, and women of non-Hispanic black race were less likely to travel far. Patients who were Asian/Pacific Islander lived the closest to a high-quality hospital. CONCLUSIONS:Among California women diagnosed with OC, living closer to a high-quality center was associated with receiving adherent care. Non-Hispanic black women were less likely to receive adherent care, and women with lower SES lived farthest from high-quality hospitals. Geographic location in California is an independent predictor of adherence to NCCN Guidelines for OC.

Ovarian cancer survival varies geographically throughout California. The objective of this study is to determine the impact of living in disadvantaged communities on spatial patterns of survival disparities. Including a bivariate spatial smooth of geographic location within the Cox proportional hazard models is an effective approach for spatial analyses of cancer survival. Women diagnosed with advanced Stage IIIC/IV epithelial ovarian cancer (1996-2006) were identified from the California Cancer Registry. The impact of living in disadvantaged communities, as measured by the California Office of Environmental Health Hazard Assessment cumulative CalEnviroScreen 2.0 score, on geographic disparities in survival was assessed while controlling for age, tumor characteristics, quality of care, and race. Community-level air quality indicators and socioeconomic status (SES) were also independently examined in secondary analyses. The Cox proportional hazard spatial methods are available in the MapGAM package implemented in R. An increase in the community disadvantage from the 5th (less disadvantage) to the 95th percentile (more disadvantage) was significantly associated with poorer ovarian cancer survival (hazard ratio [HR], 1.16; 95% confidence interval [CI], 1.07-1.26). Ozone levels and SES were the most influential indicators on geographic disparities that warrant further investigation. The use of a bivariate smoother of location within the survival model allows for more advanced spatial analyses for exploring potential air quality-related predictors of geographic disparities.

Palliative care has demonstrated effectiveness in alleviating the biological, emotional, social, and spiritual symptoms that accompany serious illness, and improving quality of life for seriously ill individuals and their family members. Despite increasing availability, there are significant disparities in access to and utilization of palliative care, particularly among diverse, low-income, and community-dwelling older adults with chronic illness. Training frontline service providers is a novel approach to expanding access to palliative care among underserved elders. This article presents a process and outcome evaluation of a palliative care curriculum that was developed and piloted for geriatric case managers in a large urban area. We describe the background, planning, design, implementation, and preliminary outcomes associated with a pilot implementation of the curriculum. We conclude with implications for replicating efforts to enhance frontline providers' knowledge, skills, and self-efficacy in extending palliative care to communities that lack access to critical supports for their burdensome symptoms. [ABSTRACT FROM AUTHOR]

Introduction: Fasting prior to induction of anesthesia prevents vomiting and aspiration. Its duration varies according to the ingested food. However, many children are submitted to prolonged fasting risking hypoglycemia. Methods: Duration of fasting was interrogated in 143 children undergoing elective surgery. A blood sample was taken as a peropherial catheter was placed, prior to any fl uid infusion. Capillary blood glucose was measured. Data were analyzed using SPSS version 22. A value of p < 0.05 was considered significant. Results: 98 males (68.5%) and 45 female (31.5%). Patient age ranged from 1 month to 16 years old (mean: 5.56 ± 4.12). Weight ranged from 3.7 to 90 kg (mean: 22.74 ± 16.87). Duration of fasting was 6-21 hours (mean: 11.45 ± 2.45). Glucose levels of 55 to 135 mg/dL were reported. Conclusions: Even though no hypoglycemia levels were reported, it is recommended to respect the indication of pre-anesthetic fasting, as well as avoiding delays and prolonged waiting time before access to the operating room. [ABSTRACT FROM AUTHOR]