Menstrual hygiene management among adolescent girls in West Africa: A systematic review.

A systematic literature review was conducted to examine all recent academic, peer-reviewed studies of menstrual hygiene management (MHM) across adolescent girls in Anglophone West Africa. The objective was to assess the status of the scholarship surrounding the knowledge, attitudes, and practices of MHM across English-speaking West African countries and identify gaps in the literature for further research. The authors searched the epidemiological literatures indexed in PubMed and cross-referenced bibliographies for studies published between 2010-2022. Of 59 abstracts and articles screened, 35 met the final inclusion criteria. Despite differences in study design, setting, and data sources, the study results concurred on an average age of menarche between 12-15 years old among adolescent girls. The knowledge of MHM came from multiple sources, most commonly mothers, female siblings, and teachers and higher knowledge was associated with age, source, wealth, religion, and education level. Less than half of the adolescent girls knew about menstruation before menarche. Many studies showed that girls were shocked by their first period and fearful of staining. Menstruation was associated with dysmenorrhea, fear/embarrassment, and missing school. The existing studies suggest that more implementation and evaluation of menstrual hygiene management materials, education, and facilities are needed to address the educational, physical, and social disparities that exist among girls in West African countries.

Une revue systématique de la littérature a été menée pour examiner toutes les études universitaires récentes évaluées par des pairs sur la gestion de l'hygiène menstruelle (MHM) chez les adolescentes d'Afrique de l'Ouest anglophone. L'objectif était d'évaluer l'état de la recherche sur les connaissances, les attitudes et les pratiques de la GHM dans les pays anglophones d'Afrique de l'Ouest et d'identifier les lacunes dans la littérature pour des recherches plus approfondies. Les auteurs ont recherché dans la littérature épidémiologique indexée dans PubMed et des bibliographies croisées pour les études publiées entre 2010 et 2022. Sur les 59 résumés et articles examinés, 35 répondaient aux critères d'inclusion finaux. Malgré les différences dans la conception, le cadre et les sources de données de l'étude, les résultats de l'étude concordaient sur un âge moyen des premières règles entre 12 et 15 ans chez les adolescentes. La connaissance de la GHM provenait de sources multiples, le plus souvent des mères, des frères et sœurs et des enseignants, et les connaissances supérieures étaient associées à l'âge, à la source, à la richesse, à la religion et au niveau d'éducation. Moins de la moitié des adolescentes connaissaient leurs règles avant les premières règles. De nombreuses études ont montré que les filles étaient choquées par leurs premières règles et craignaient les taches. Les menstruations étaient associées à la dysménorrhée, à la peur/à la gêne et à l'absence à l'école. Les études existantes suggèrent qu'une plus grande mise en œuvre et une plus grande évaluation du matériel, de l'éducation et des installations de gestion de l'hygiène menstruelle sont nécessaires pour remédier aux disparités éducatives, physiques et sociales qui existent parmi les filles dans les pays d'Afrique de l'Ouest.

Long-term exposure to air pollution and risk of stroke by ecoregions: The REGARDS study.

Several cohort studies have found associations between long-term exposure to air pollution and stroke risk. However, it is unclear whether the surrounding ecology may modify these associations. This study evaluates associations of air pollution with stroke risk by ecoregions, which are areas of similar type, quality, and quantity of environmental resources in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. We assessed the incidence of stroke in 26,792 participants (45+ yrs) from the REGARDS study, a prospective cohort recruited across the contiguous United States. One-yr and 3-yr means of PM2.5, PM10, O3, NO2, SO2, and CO were estimated at baseline using data from the Center for Air, Climate, & Energy Solution, and assigned to participants at the census block group level. Incident stroke was ascertained through September 30, 2020. Relations of air pollutants with the risk of incident stroke were estimated using Cox proportional hazards models, adjusting for relevant demographics, behavioral risk factors, and neighborhood urbanicity. Models were stratified by EPA designated ecoregions. A 5.4 µg/m3 (interquartile range) increase in 1-yr PM10 was associated with a hazard ratio (95 %CI) for incident stroke of 1.07 (1.003, 1.15) in the overall study population. We did not find evidence of positive associations for PM2.5, O3, NO2, SO2, and CO in the fully adjusted models. In our ecoregion-specific analysis, associations of PM2.5 with stroke were stronger in the Great Plains ecoregion (HR = 1.44) than other ecoregions, while associations for PM10 were strongest in the Eastern Temperate Forests region (HR = 1.15). The associations between long-term exposure to air pollution and risk of stroke varied by ecoregion. Our results suggests that the type, quality, and quantity of the surrounding ecology can modify the effects of air pollution on risk of stroke.

Quantifying the benefit-risk trade-off for individual patients in a clinical trial: principles and antithrombotic case study.

BACKGROUND: A treatment's overall favorable benefit-risk profile does not imply that every individual patient will benefit from the treatment. OBJECTIVES: To describe a statistical methodology for quantifying the benefit-risk trade-off in individual patients. METHODS: The method requires a large randomized controlled trial containing a primary efficacy outcome and a primary safety outcome, for instance, the Thrombin Receptor Antagonist in Secondary Prevention of Atherothrombotic Ischemic Events-Thrombolysis in Myocardial Infarction 50 placebo-controlled trial of vorapaxar in 17 779 patients following myocardial infarction. Multivariate regression models predict each individual patient's risk of ischemic events (benefit) and major bleeding events (harm) based on their profile. Hence, each patient's predicted benefit from vorapaxar (reduction in ischemic events) and predicted risk (increase in bleeding events) were estimated. The relative importance of ischemic and bleeding events based on links to all-cause mortality was quantified, although the limitations of such weightings are noted. RESULTS: Overall results demonstrated both clear benefit and harm from vorapaxar. Substantial interindividual variation in both benefit and risk facilitated distinguishing patients with a favorable benefit-risk trade-off from those who did not. Such findings were applied to recommend vorapaxar in as many as 98.3% of patients in which a favorable mortality-weighted benefit-risk trade-off was present, in 77.2% of patients with ischemic benefit 20% greater than bleeding risk, or in as few as 45.5% of patients if an annual decrease in ischemic risk of ≥0.5% was also required. CONCLUSION: While overall randomized controlled trials of treatment benefit vs risk are valuable, models determining each individual patient's estimated absolute benefit and risk provide more useful insight regarding patient-specific benefit-risk trade-offs to better enable personalized therapeutic decision-making.

Residence in urban or rural counties in relation to opioid overdose mortality among Kentucky hospitalizations before and during the COVID-19 pandemic.

BACKGROUND: At the beginning of the opioid overdose epidemic, overdose mortality rates were higher in urban than in rural areas. We examined the association between residence in an urban or rural county and subsequent opioid overdose mortality in Kentucky, a state highly impacted by the opioid epidemic, and whether this was modified by the COVID-19 pandemic. METHODS: We captured hospitalizations in Kentucky from 2016 to 2020, involving an opioid using ICD-10-CM codes T40.0-T40.4 and T40.6. Patient's county was classified as urban or rural based on the NCHS Urban-Rural Classification Scheme. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) of opioid overdose mortality, adjusted for demographics, hospitalization severity, and zip code SES. We assessed effect modification by the COVID-19 pandemic. RESULTS: Overall, patients living in urban counties had 46% higher odds of opioid overdose death than patients residing in rural counties (adjusted OR=1.46; 95% CI=1.22, 1.74). Before the pandemic, patients in urban counties had 63% increased odds of opioid overdose death (adjusted OR=1.63; 95% CI=1.34, 1.97); however, during the COVID-19 pandemic, patients in urban and rural counties became more similar in regard to opioid overdose mortality (adjusted OR=0.72; 95% CI=0.45, 1.16; p-value for interaction =0.02). CONCLUSION: Before the pandemic, living in urban counties was associated with higher opioid overdose mortality among Kentucky hospitalizations; however, during the COVID-19 pandemic, opioid overdose mortality in rural areas increased, approaching rates in urban areas. COVID-19 posed social, economic, and healthcare challenges that may be contributing to worsening mortality trends affecting both urban and rural patients.

Predicting Measles Outbreaks in the United States: Evaluation of Machine Learning Approaches.

BACKGROUND: Measles, a highly contagious viral infection, is resurging in the United States, driven by international importation and declining domestic vaccination coverage. Despite this resurgence, measles outbreaks are still rare events that are difficult to predict. Improved methods to predict outbreaks at the county level would facilitate the optimal allocation of public health resources. OBJECTIVE: We aimed to validate and compare extreme gradient boosting (XGBoost) and logistic regression, 2 supervised learning approaches, to predict the US counties most likely to experience measles cases. We also aimed to assess the performance of hybrid versions of these models that incorporated additional predictors generated by 2 clustering algorithms, hierarchical density-based spatial clustering of applications with noise (HDBSCAN) and unsupervised random forest (uRF). METHODS: We constructed a supervised machine learning model based on XGBoost and unsupervised models based on HDBSCAN and uRF. The unsupervised models were used to investigate clustering patterns among counties with measles outbreaks; these clustering data were also incorporated into hybrid XGBoost models as additional input variables. The machine learning models were then compared to logistic regression models with and without input from the unsupervised models. RESULTS: Both HDBSCAN and uRF identified clusters that included a high percentage of counties with measles outbreaks. XGBoost and XGBoost hybrid models outperformed logistic regression and logistic regression hybrid models, with the area under the receiver operating curve values of 0.920-0.926 versus 0.900-0.908, the area under the precision-recall curve values of 0.522-0.532 versus 0.485-0.513, and F2 scores of 0.595-0.601 versus 0.385-0.426. Logistic regression or logistic regression hybrid models had higher sensitivity than XGBoost or XGBoost hybrid models (0.837-0.857 vs 0.704-0.735) but a lower positive predictive value (0.122-0.141 vs 0.340-0.367) and specificity (0.793-0.821 vs 0.952-0.958). The hybrid versions of the logistic regression and XGBoost models had slightly higher areas under the precision-recall curve, specificity, and positive predictive values than the respective models that did not include any unsupervised features. CONCLUSIONS: XGBoost provided more accurate predictions of measles cases at the county level compared with logistic regression. The threshold of prediction in this model can be adjusted to align with each county's resources, priorities, and risk for measles. While clustering pattern data from unsupervised machine learning approaches improved some aspects of model performance in this imbalanced data set, the optimal approach for the integration of such approaches with supervised machine learning models requires further investigation.

Treatment-related side effects among Hispanic and non-Hispanic white long-term breast cancer survivors by tamoxifen use and duration.

PURPOSE: To determine the associations between ethnicity, age at diagnosis, obesity, multimorbidity, and odds of experiencing breast cancer (BC) treatment-related side effects among long-term Hispanic and non-Hispanic white (NHW) survivors from New Mexico and explore differences by tamoxifen use. METHODS: Lifestyle and clinical information including self-reported tamoxifen use and presence of treatment- related side effects were collected at follow-up interviews (12-15 years) for 194 BC survivors. Multivariable logistic regression models were used to examine associations between predictors and odds of experiencing side effects overall and by tamoxifen use. RESULTS: Women ranged in age at diagnosis (30-74, M = 49.3, SD = 9.37), most were NHW (65.4%) and had in-situ or localized BC (63.4%). Less than half reportedly used tamoxifen (44.3%), of which 59.3% reported using > 5 years. Overall, survivors who were overweight/obese at follow-up were 5.42 times more likely to experience treatment-related pain (95% CI 1.40-21.0) compared to normal weight survivors. Survivors with multimorbidity, compared to survivors without, were more likely to report treatment-related sexual health issues (aOR 6.90, 95% CI 1.43-33.2) and poorer mental health (aOR 4.51, 95% CI 1.06-19.1). The statistical interactions between ethnicity and overweight/obese with tamoxifen use were significant (p-interaction < 0.05) for treatment-related sexual health issues. CONCLUSION: Our results demonstrate that survivors with overweightness/obesity or multimorbidity may be more likely to experience BC treatment-related side effects. Tamoxifen use modifies associations between ethnicity, being overweight/obese, and sexual health issues following treatment. The likelihood of experiencing treatment-related side effects were more favorable for those on tamoxifen or those who had used tamoxifen for longer durations. These findings highlight the importance of fostering side effect awareness and applying appropriate interventions to assist with disease management throughout BC survivorship care.

Bayesian screening for feature selection.

Biomedical applications such as genome-wide association studies screen large databases with high-dimensional features to identify rare, weakly expressed, and important continuous-valued features for subsequent detailed analysis. We describe an exact, rapid Bayesian screening approach with attractive diagnostic properties using a Gaussian random mixture model focusing on the missed discovery rate (the probability of failing to identify potentially informative features) rather than the false discovery rate ordinarily used with multiple hypothesis testing. The method provides the likelihood that a feature merits further investigation, as well as distributions of the effect magnitudes and the proportion of features with the same expected responses under alternative conditions. Important features include the dependence of the critical values on clinical and regulatory priorities and direct assessment of the diagnostic properties.

Systemic inflammation and risk of all-cause mortality after invasive breast cancer diagnosis among Hispanic and non-Hispanic white women from New Mexico.

INTRODUCTION: Soluble tumor necrosis factor receptor-II (sTNF-R2), a pro-inflammatory biomarker, is associated with obesity and breast cancer (BC). The association between sTNF-R2 and risk of mortality after BC has not been studied, specifically among Hispanic women, an at-risk population due to their high prevalence of obesity and poor prognosis. We examined the association between sTNF-R2 and mortality among Hispanic and non-Hispanic white (NHW) BC survivors. METHODS: A total of 397 invasive BC survivors (96 Hispanic, 301 NHW) contributed baseline interview data and blood samples. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox proportional hazards regression models adjusting for clinical factors including body mass index. RESULTS: After a median follow-up time of 13 years, 133 deaths occurred. The association between high vs low levels of plasma sTNF-R2 and mortality was not statistically significant overall (HR, 1.32; 95% CI 0.89-1.98). However, when stratified the mortality risk among Hispanic women was nearly 3-fold (HR, 2.83; 95% CI 1.21-6.63), while risk among NHW women was attenuated (HR, 0.99; 95% CI 0.61-1.61) (p-interaction=0.10). CONCLUSION: Our results suggest Hispanic BC survivors with high sTNF-R2 levels may have increased risk of mortality and could inform targeted interventions to reduce inflammation and improve outcomes.

Physical activity, ethnicity, and quality of life among breast cancer survivors and population-based controls: the long-term quality of life follow-up study.

PURPOSE: To explore the relationship between physical activity (PA) and quality of life (QOL) among Hispanic and non-Hispanic white breast cancer (BC) cases and population-based controls from the New Mexico 'Long-Term Quality of Life Study'. METHODS: Self-reported PA (low, moderate, vigorous MET hours/week) at baseline and follow-up interviews (12-15 years) were available for 391 cases and controls and modeled using multiple linear regressions with SF-36 mean composite scores for physical and mental health. The change in PA from baseline to follow-up and interactions with ethnicity were also examined. Models were adjusted for age at diagnosis/baseline interview, education, comorbidities, body mass index, and change in PA. RESULTS: PA intensities at each timepoint did not differ by case/control status; however, the change in vigorous PA was lower among cases (p = 0.03). At follow-up, low intensity PA increased mental health QOL scores among cases; however, the interaction between low intensity PA and ethnicity was statistically significant among controls indicating decreased mental health among Hispanics (p = 0.02). Change in moderate PA was associated with increased physical and mental health among cases (physical: ß = 0.186, p = 0.008; mental: ß = 0.225, p = 0.001) and controls (physical: ß = 0.220, p < 0.0001; mental: ß = 0.193, p = 0.002), when controlling for confounders. CONCLUSION: Our results demonstrate that all levels of PA are important for mental health among BC cases, while activities of higher intensity are important for physical health among women overall. The statistical interaction observed between ethnicity and low intensity PA among controls for mental health warrants further research to provide a meaningful interpretation.

Self-reported symptoms of arm lymphedema and health-related quality of life among female breast cancer survivors.

We examined cross-sectional associations between arm lymphedema symptoms and health-related quality of life (HRQoL) in the Health, Eating, Activity and Lifestyle (HEAL) Study. 499 women diagnosed with localized or regional breast cancer at ages 35-64 years completed a survey, on average 40 months after diagnosis, querying presence of lymphedema, nine lymphedema-related symptoms, e.g., tension, burning pain, mobility loss, and warmth/redness, and HRQoL. Analysis of covariance models were used to assess HRQoL scores in relation to presence of lymphedema and lymphedema-related symptoms. Lymphedema was self-reported by 137 women, of whom 98 were experiencing lymphedema at the time of the assessment. The most common symptoms were heaviness (52%), numbness (47%), and tightness (45%). Perceived physical health was worse for women reporting past or current lymphedema than those reporting no lymphedema (P-value < 0.0001). No difference was observed for perceived mental health (P-value = 0.31). Perceived physical health, stress, and lymphedema-specific HRQoL scores worsened as number of symptoms increased (P-values ≤ 0.01). Women reporting tension in the arm had lower physical health (P-value = 0.01), and those experiencing burning pain, tension, heaviness, or warmth/redness in the arm had lower lymphedema-specific HRQoL (P-values < 0.05). Treatment targeting specific lymphedema-related symptoms in addition to size/volume reduction may improve some aspects of HRQoL among affected women.

Ethnic and biological differences in the association between physical activity and survival after breast cancer.

Physical activity is recommended for most cancer patients as a nonpharmacological therapy to improve prognosis. Few studies have investigated the association between physical activity and breast cancer prognosis by ethnicity, biological, and modifiable risk factors for mortality. We investigated the association between physical activity and long-term survival among breast cancer survivors. A total of 397 survivors (96 Hispanic and 301 non-Hispanic White (NHW)) from the New Mexico HEAL study contributed baseline and biological data approximately 6 months after diagnosis. Study outcomes included all-cause, breast cancer-specific, and non-breast cancer mortality. The exposure was self-reported physical activity within the past month. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox Proportional Hazards regression. A total of 133 deaths (53 breast cancer-specific deaths) were observed after a median follow-up time of 13 years. Engaging in >6.9 metabolic equivalent hours/week (MET-h/week) of moderate to vigorous physical activity (active) was inversely associated with all-cause mortality among all women (HR 0.66, 95% CI 0.43-0.99) and NHWs (HR 0.58, 95% CI 0.36-0.94). Active NHW women also had a reduced risk of non-breast cancer mortality (HR 0.56, 95% CI 0.31-0.99), compared to inactive women (0 MET-h/week). In subgroups, we observed the inverse associations with all-cause mortality among women >58 years old (p-interaction= 0.03) and with localized stage (p-interaction = 0.046). Our results confirm the protective association between physical activity and mortality after breast cancer diagnosis, and demonstrate that this association significantly differs by age and cancer stage. Larger studies are warranted to substantiate our findings.

A Lesson from Plants: High-Speed Soft Robotic Actuators.

Rapid energy-efficient movements are one of nature's greatest developments. Mechanisms like snap-buckling allow plants like the Venus flytrap to close the terminal lobes of their leaves at barely perceptible speed. Here, a soft balloon actuator is presented, which is inspired by such mechanical instabilities and creates safe, giant, and fast deformations. The basic design comprises two inflated elastomer membranes pneumatically coupled by a pressurized chamber of suitable volume. The high-speed actuation of a rubber balloon in a state close to the verge of mechanical instability is remotely triggered by a voltage-controlled dielectric elastomer membrane. This method spatially separates electrically active and passive parts, and thereby averts electrical breakdown resulting from the drastic thinning of an electroactive membrane during large expansion. Bistable operation with small and large volumes of the rubber balloon is demonstrated, achieving large volume changes of 1398% and a high-speed area change rate of 2600 cm2 s-1. The presented combination of fast response time with large deformation and safe handling are central aspects for a new generation of soft bio-inspired robots and can help pave the way for applications ranging from haptic displays to soft grippers and high-speed sorting machines.

Bayesian credible subgroup identification for treatment effectiveness in time-to-event data.

Due to differential treatment responses of patients to pharmacotherapy, drug development and practice in medicine are concerned with personalized medicine, which includes identifying subgroups of population that exhibit differential treatment effect. For time-to-event data, available methods only focus on detecting and testing treatment-by-covariate interactions and may not consider multiplicity. In this work, we introduce the Bayesian credible subgroups approach for time-to-event endpoints. It provides two bounding subgroups for the true benefiting subgroup: one which is likely to be contained by the benefiting subgroup and one which is likely to contain the benefiting subgroup. A personalized treatment effect is estimated by two common measures of survival time: the hazard ratio and restricted mean survival time. We apply the method to identify benefiting subgroups in a case study of prostate carcinoma patients and a simulated large clinical dataset.

Pyoderma Gangrenosum in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis.

BACKGROUND: Pyoderma gangrenosum (PG) is an uncommon but severe extra-intestinal manifestation (EIM) of inflammatory bowel disease (IBD). The incidence and risk factors for PG are disputed. AIMS: To assess the incidence of PG and identify factors associated with PG in IBD patients. METHODS: A search of electronic databases (Ovid and PubMed) was conducted between 1966 and 2019. Studies that calculated the incidence of PG in IBD patient cohorts were included. Patient demographics, IBD subtype, and EIM presence were recorded. A review of our institutional database of 1057 IBD patients was conducted. A multivariate regression model and meta-analysis were conducted to identify risk factors for PG. A random effects model was used to combine the data of included studies. RESULTS: Fourteen studies were included in addition to 1057 IBD patients and 26 PG cases from the Louisville cohort. In total, there were 379 cases of PG in the cumulative cohort of 61,695 IBD patients. The PG incidence in individual studies ranged from 0.4 to 2.6%. In the institutional cohort, ocular EIMs and a permanent stoma were significant risk factors for PG. In the meta-analysis, PG was associated with female gender (RR = 1.328, 95% CI 1.161-1.520), Crohn's disease (RR = 1.193, 95% CI 1.001-1.422), erythema nodosum (RR = 9.281, 95% CI 6.081-14.164), and ocular EIM (RR = 4.55, 95% CI 3.04-6.81). There was study heterogeneity when assessing IBD subtype, ocular, and joint EIMs. CONCLUSIONS: There are conflicting data on the incidence and risk factors for PG. This meta-analysis confirms an association between PG and female gender, Crohn's disease, erythema nodosum, and ocular EIM that have been described in smaller studies.

Fructosamine and diabetes as predictors of mortality among Hispanic and non-Hispanic white breast cancer survivors.

Epidemiologic studies have found that elevated insulin levels and chronic hyperglycemia among breast cancer (BC) survivors are associated with poor prognosis; few of these studies have included Hispanic women in whom diabetes is highly prevalent. We examined the associations between circulating fructosamine-a biomarker of hyperglycemia and blood glucose control, self-reported diabetes, and risk of BC-specific and all-cause mortality among Hispanic and non-Hispanic white (NHW) women diagnosed with invasive BC. A total of 399 BC survivors (96 Hispanic, 303 NHW) contributed baseline data and plasma samples. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using multivariable Cox proportional hazards regression models. After a median follow-up time of 13 years, a total of 134 deaths occurred, of which 56 deaths were from BC. Diabetes was associated with BC-specific (HR, 2.89; 95% CI 1.27-6.60) and all-cause (HR, 2.10; 95% CI 1.24-3.55) mortality. Associations were stronger among women with clinically high fructosamine levels (>285 µmol/L) (BC-specific: HR, 4.25; 95% CI 1.67-10.80; all-cause: HR, 2.32; 95% CI 1.30-4.14) compared to women with normal levels (≤285 µmol/L). In mediation analysis, fructosamine explained 47% of the association between diabetes and all-cause mortality and 41% of BC-specific mortality; the largest attenuation was among Hispanics for all-cause mortality (56%). Our results demonstrate that poor glycemic control explains a large extent of the relationship between diabetes and mortality among women with invasive BC, particularly among Hispanic women. The associations we observed for BC mortality should be confirmed in larger studies of ethnically diverse BC patients.

The Influence of Education and Apolipoprotein ε4 on Mortality in Community-Dwelling Elderly Men and Women.

We investigated the risk of death in relation to the apolipoprotein ε4 allele and evaluated how it interacts with education in 504 elderly adults (mean age 73 years, 65.3% women) who were enrolled in 1993 into the New Mexico Aging Process Study. During 9 years of follow-up, apolipoprotein ε2 appeared to be associated with a lower risk for all-cause mortality (hazard ratio (HR) = 0.73, 95% confidence interval (CI): 0.30-1.71) compared to apolipoprotein ε3 carriers in models adjusted for age, sociodemographic variables, medical conditions, adiposity, and lifestyle factors. The apolipoprotein ε4 allele conferred almost a threefold elevated risk of mortality (HR = 2.76, CI: 1.42-5.37). An interaction between education and apolipoprotein e4 (p=0.027) was observed with the HR of mortality among e4 carriers compared to noncarriers being 1.59 (0.64-3.96) for those with ≥college education; 6.66 (1.90-23.4) for those with some college or trade; and 14.1 (3.03-65.6) for participants with ≤high school education. No significant interaction was identified between apolipoprotein E genotype and cognitive function for mortality risk. These findings suggest that genetic (apolipoprotein ε4) and environmental (education) factors act interactively to influences survival in the elderly with higher education attenuating the adverse effect of apolipoprotein ε4 on mortality.

A Bayesian Framework for Estimating the Concordance Correlation Coefficient Using Skew-elliptical Distributions.

The concordance correlation coefficient (CCC) is a widely used scaled index in the study of agreement. In this article, we propose estimating the CCC by a unified Bayesian framework that can (1) accommodate symmetric or asymmetric and light- or heavy-tailed data; (2) select model from several candidates; and (3) address other issues frequently encountered in practice such as confounding covariates and missing data. The performance of the proposal was studied and demonstrated using simulated as well as real-life biomarker data from a clinical study of an insomnia drug. The implementation of the proposal is accessible through a package in the Comprehensive R Archive Network.

Associations between ALDH1A1 polymorphisms, alcohol consumption, and mortality among Hispanic and non-Hispanic white women diagnosed with breast cancer: the Breast Cancer Health Disparities Study.

PURPOSE: ALDH1A1, one of the main isotopes of aldehyde dehydrogenase-1 is involved in the differentiation and protection of normal hematopoietic stem cells and functions in alcohol sensitivity and dependence. We evaluated the associations between ALDH1A1 polymorphisms, alcohol consumption, and mortality among Hispanic and non-Hispanic white (NHW) breast cancer (BC) cases from the Breast Cancer Health Disparities Study. METHODS: Nine SNPs in ALDH1A1 were evaluated in 920 Hispanic and 1372 NHW women diagnosed with incident invasive BC. Adjusted Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Models were stratified by Native American (NA) ancestry and alcohol consumption. RESULTS: A total of 443 deaths occurred over a median follow-up time of 11 years. After adjusting all results for multiple comparisons, rs7027604 was significantly associated with all-cause mortality (HRAA = 1.40; 95% CI 1.13-1.73, P adj = 0.018). The rs1424482 CC genotype (HRCC = 1.69; 95% CI 1.20-2.37, P adj = 0.027) and the rs7027604 AA genotype (HRAA = 1.65; 95% CI 1.21-2.26, P adj = 0.018) were positively associated with non-BC mortality. Among long-term light drinkers, rs1888202 was associated with decreased all-cause mortality (HRCG/GG = 0.36; 95% CI 0.20-0.64), while associations were not significant among non-drinkers or moderate/heavy drinkers (P interation = 0.218). The increased risk of all-cause mortality associated with rs63319 was limited to women with low NA ancestry (HRAA = 1.53; 95% CI 1.19-1.97). CONCLUSIONS: Multiple SNPs in ALDH1A1 were associated with increased risk of mortality after BC. Future BC studies examining the relationship between ALDH1A1 and mortality should consider the modifying effects of alcohol consumption and NA ancestry.

The role of fMRI in drug development.

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility.