Search

Background: Men tend to have more upper body mass and fat than women, a physical characteristic that may predispose them to severe motor vehicle crash (MVC) injuries, particularly in certain body regions. This study examined MVC-related regional body injury and its association with the presence of driver obesity using both real-world data and computer crash simulation. Methods and Findings: Real-world data were from the 2001 to 2005 National Automotive Sampling System Crashworthiness Data System. A total of 10,941 drivers who were aged 18 years or older involved in frontal collision crashes were eligible for the study. Sex-specific logistic regression models were developed to analyze the associations between MVC injury and the presence of driver obesity. In order to confirm the findings from real-world data, computer models of obese subjects were constructed and crash simulations were performed. According to real-world data, obese men had a substantially higher risk of injury, especially serious injury, to the upper body regions including head, face, thorax, and spine than normal weight men (all p<0.05). A U-shaped relation was found between body mass index (BMI) and serious injury in the abdominal region for both men and women (p,0.05 for both BMI and BMI2). In the high-BMI range, men were more likely to be seriously injured than were women for all body regions except the extremities and abdominal region (all p<0.05 for interaction between BMI and sex). The findings from the computer simulation were generally consistent with the real-world results in the present study. Conclusions: Obese men endured a much higher risk of injury to upper body regions during MVCs. This higher risk may be attributed to differences in body shape, fat distribution, and center of gravity between obese and normal-weight subjects, and between men and women. [ABSTRACT FROM AUTHOR]

Background: Type 1 diabetes (T1D) is a T-cell mediated autoimmune disease targeting the insulin-producing pancreatic b cells. Naturally occurring FOXP3+CD4+CD25high regulatory T cells (Tregs) play an important role in dominant tolerance, suppressing autoreactive CD4+ effector T cell activity. Previously, in both recent-onset T1D patients and β cell antibodypositive at-risk individuals, we observed increased apoptosis and decreased function of polyclonal Tregs in the periphery. Our objective here was to elucidate the genes and signaling pathways triggering apoptosis in Tregs from T1D subjects. Principal Findings: Gene expression profiles of unstimulated Tregs from recent-onset T1D (n = 12) and healthy control subjects (n = 15) were generated. Statistical analysis was performed using a Bayesian approach that is highly efficient in determining differentially expressed genes with low number of replicate samples in each of the two phenotypic groups. Microarray analysis showed that several cytokine/chemokine receptor genes, HLA genes, GIMAP family genes and cell adhesion genes were downregulated in Tregs from T1D subjects, relative to control subjects. Several downstream target genes of the AKT and p53 pathways were also upregulated in T1D subjects, relative to controls. Further, expression signatures and increased apoptosis in Tregs from T1D subjects partially mirrored the response of healthy Tregs under conditions of IL-2 deprivation. CD4+ effector T-cells from T1D subjects showed a marked reduction in IL-2 secretion. This could indicate that prior to and during the onset of disease, Tregs in T1D may be caught up in a relatively deficient cytokine milieu. Conclusions: In summary, expression signatures in Tregs from T1D subjects reflect a cellular response that leads to increased sensitivity to apoptosis, partially due to cytokine deprivation. Further characterization of these signaling cascades should enable the detection of genes that can be targeted for restoring Treg function in subjects predisposed to T1D. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Racial and socioeconomic disparities have been identified in osteoporosis screening.Objective: To determine whether racial and socioeconomic disparities in osteoporosis screening diminish after hip fracture.Design: Retrospective cohort study of female Medicare patients.Setting: Entire states of Illinois, New York, and Florida.Participants: Female Medicare recipients aged 65-89 years old with hip fractures between January 2001 and June 2003.Measurements: Differences in bone density testing by race/ethnicity and zip-code level socioeconomic characteristics during the 2-year period preceding and the 6-month period following a hip fracture.Results: Among all 35,681 women with hip fractures, 20.7% underwent bone mineral density testing in the 2 years prior to fracture and another 6.2% underwent testing in the 6 months after fracture. In a logistic regression model adjusted for age, state, and comorbidity, women of black race were about half as likely (RR 0.52 [0.43, 0.62]) and Hispanic women about 2/3 as likely (RR 0.66 [0.54, 0.80]) as white women to undergo testing before their fracture. They remained less likely (RR 0.66 [0.50, 0.88] and 0.58 [0.39, 0.87], respectively) to undergo testing after fracture. In contrast, women residing in zip codes in the lowest tertile of income and education were less likely than those in higher-income and educational tertiles to undergo testing before fracture, but were no less likely to undergo testing in the 6 months after fracture.Conclusions: Racial, but not socioeconomic, differences in osteoporosis evaluation continued to occur even after Medicare patients had demonstrated their propensity to fracture. Future interventions may need to target racial/ethnic and socioeconomic disparities differently. [ABSTRACT FROM AUTHOR]

Objectives. We examined the association between number of breast cancer operations performed in a hospital (hospital volume) and all-cause and breast cancer-specific mortality using a national database and statistical methods appropriate for clustering and reducing confounding. Methods. In a retrospective cohort study, we linked Surveillance, Epidemiology, and End Results tumor registry data with Medicare claims data. The cohort included 11225 Medicare patients who had undergone surgery for early-stage breast cancer from 1994 to 1996 in 457 different hospitals. Primary outcomes were all-cause and breast cancer-specific survival rates at a mean follow-up time of 62.5 months. Results. In comparison with treatment in a low-volume hospital, treatment in a high-volume hospital was associated with hazard ratios of 0.83 (95% confidence interval [CI] = 0.75, 0.92) for all-cause mortality and 0.80 (CI = 0.66, 0.97) for breast cancer-specific mortality. Conclusions. An association between the volume of breast cancer operations performed in a hospital and 5-year survival rates was observed for both all-cause and breast cancer-specific mortality. Further work investigating the aspects of hospital volume that contribute to increased survival is warranted. [ABSTRACT FROM AUTHOR]

The article presents a case study on the inequalities in colon cancer screening in the U.S. medicare population. The study shows that the lowest relative risk of screening colonoscopy in women was in the oldest age group and the highest income tertile as compared to men. It was found out that there remain disparities between sex and racial or ethnic groups in screening practices, despite Medicare coverage for colorectal cancer screening expansion.

A new simulation method, auxiliary random functions is introduced. When used within a Gibbs sampler, this method enables a unified treatment of exact, right-censored, left-censored, left-truncated and interval censored data, with and without covariates in survival models. The models and methods are exemplified via illustrative analysis. [ABSTRACT FROM AUTHOR]

Objectives. We examined the role of body mass index (BMI) and other factors in driver deaths within 30 days after motor vehicle crashes. Methods. We collected data for 22 107 drivers aged 16 years and older who were involved in motor vehicle crashes from the Crashworthiness Data System of the National Automotive Sampling System (1997-2001). We used logistic regression and adjusted for confounding factors to analyze associations between BMI and driver fatality and the associations between BMI and gender, age, seatbelt use, type of collision, airbag deployment, and change in velocity during a crash. Results. The fatality rate was 0.87% (95% confidence interval [CI]=0.50, 1.24) among men and 0.43% (95% CI=0.31, 0.56) among women involved as drivers in motor vehicle crashes. Risk for death increased significantly at both ends of the BMI continuum among men but not among women (P<.05). The association between BMI and male fatality increased significantly with a change in velocity and was modified by the type of collision, but it did not differ by age, seatbelt use, or airbag deployment. Conclusions. The increased risk for death due to motor vehicle crashes among obese men may have important implications for traffic safety and motor vehicle design. (Am J Public Health. 2006;96:734-739. [ABSTRACT FROM AUTHOR]

Here we extend predictive method for model selection of Laud and Ibrahim to the generalized linear model. This prescription avoids the need to directly specify prior probabilities of models and prior densities for the parameters. Instead, a prior prediction for the response induces the required priors. We propose normal and conjugate priors for generalized linear models, each using a single prior prediction for the mean response to induce suitable priors for each variable-subset model. In this way, an informative prior is used to select a subset of variables. In addition to producing a ranking of models by size of the predictive criterion, the standard deviation of the criterion is used as a calibration number to produce a set of equally good models. A straightforward Markov chain Monte Carlo algorithm is used to accomplish the necessary computations. We illustrate this method with real and simulated datasets and compare results with the Bayes factors and the Akaike information and Bayes information model selection criteria. The simulation results confirm the efficacy of the method. because the correct model is known. An illustrative application demonstrates selection of important predictors of success in identifying the sentinel lymph node during surgical treatment ot breast cancer. A forward selection procedure is described to avoid a full search over the 218 possible models in this case. [ABSTRACT FROM AUTHOR]

In recent years, Bayesian nonparametric inference, both theoretical and computational, has witnessed considerable advances. However, these advances have not received a full critical and comparative analysis of their scope, impact and limitations in statistical modelling; many aspects of the theory and methods remain a mystery to practitioners and many open questions remain. In this paper, we discuss and illustrate the rich modelling and analytic possibilities that are available to the statistician within the Bayesian nonparametric and/or semiparametric framework. [ABSTRACT FROM AUTHOR]

Presents a paper on the computation of several number theoretic functions using the application of probability. Blocks of numbers; Sum of ratio of blocks to bits.

SUMMARY We examine the problem of specifying prior probabilities for all possible subset models in the context of variable selection in normal linear models. A solution is proposed that uses a prior prediction for the observable, an associated weight, and prior opinion regarding error precision as the only required input. Numerical examples are given to illustrate the method. [ABSTRACT FROM AUTHOR]

Introduces the use of a predictive Bayesian criterion in the context of model selection problem based on the predictive density of a replicate experiment (PDRE). Provision of a calibration of the criterion; Relationships of the proposed criterion to other prevalent criteria; Illustration of the proposed methodology.

Copyright of Canadian Journal of Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Interventions aimed at upstream factors contributing to late‐stage diagnoses could reduce disparities and improve breast cancer outcomes. This study examines the association between measures of housing stability and contemporary mortgage lending bias on breast cancer stage at diagnosis among older women in the United States. Methods: We studied 67,588 women aged 66–90 from the SEER‐Medicare linked database (2010–2015). The primary outcome was breast cancer stage at diagnosis. Multinomial regression models adjusted for individual and neighborhood socio‐economic factors were performed using a three‐category outcome (stage 0, early stage, and late stage). Key census tract‐level independent variables were residence in the same house as the previous year, owner‐occupied homes, and an index of contemporary mortgage lending bias. Results: In models adjusted for individual factors, higher levels of mortgage lending bias were associated with later stage diagnosis (RR = 1.10, 95% CI 1.02–1.20; RR = 1.31, 95% CI 1.16–1.49; RR = 1.41, 95% CI 1.24–1.60 for least to high, respectively). In models adjusted for individual and neighborhood socio‐economic factors, moderate and high levels of mortgage lending bias were associated with later stage diagnosis (RR = 1.16, 95% CI 1.02–1.33 for moderate and RR = 1.18, 95% CI 1.02–1.37 for high). Owner occupancy and tenure were not associated with later stage diagnosis in adjusted models. Conclusions: Contemporary mortgage lending bias demonstrated a significant gradient relationship with later stage at diagnosis of breast cancer. Policy interventions aimed at reducing place‐based mortgage disinvestment and its impacts on local resources and opportunities should be considered as part of an overall strategy to decrease late‐stage breast cancer diagnosis and improve prognosis. [ABSTRACT FROM AUTHOR]

Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that could provide erroneous predictions when the effects of covariates are complex. Modern advances in computational hardware have led to an increasing interest in flexible Bayesian nonparametric methods for time‐to‐event data such as Bayesian additive regression trees (BART). We propose a novel approach that we call nonparametric failure time (NFT) BART in order to increase the flexibility beyond accelerated failure time (AFT) and proportional hazard models. NFT BART has three key features: (1) a BART prior for the mean function of the event time logarithm; (2) a heteroskedastic BART prior to deduce a covariate‐dependent variance function; and (3) a flexible nonparametric error distribution using Dirichlet process mixtures (DPM). Our proposed approach widens the scope of hazard shapes including nonproportional hazards, can be scaled up to large sample sizes, naturally provides estimates of uncertainty via the posterior and can be seamlessly employed for variable selection. We provide convenient, user‐friendly, computer software that is freely available as a reference implementation. Simulations demonstrate that NFT BART maintains excellent performance for survival prediction especially when AFT assumptions are violated by heteroskedasticity. We illustrate the proposed approach on a study examining predictors for mortality risk in patients undergoing hematopoietic stem cell transplant (HSCT) for blood‐borne cancer, where heteroskedasticity and nonproportional hazards are likely present. [ABSTRACT FROM AUTHOR]

Previous analysis of 13 overlapping subcongenic strains led to the identification of a 1.37 Mbp region on chromosome 13 (positions 80.92 to 82.29 Mbp in the Rn5 genome assembly) that influenced the mean arterial blood pressure of the Dahl salt-sensitive (SS) rat on a high-salt diet by more than 20 mmHg. The goal of the present study was to identify biological pathways that could mediate the blood pressure effect of this genomic region. RNA-seq analysis was performed for the renal outer medulla tissue in five selected subcongenic strains, the SS, and a congenic strain from which the subcongenic strains were derived. Rats were fed a 0.4% salt diet or switched to a high-salt diet for 7 days. Affymetrix GeneChip data for SS and three additional congenic or consomic strains were obtained from a previous study. The RNA-seq and microarray data were merged using a cross-platform normalization method to generate a transcriptome dataset containing 90 observations for each gene. A Bayesian model analysis was performed for 243 biological pathways to assess their likelihood to discriminate blood pressure levels across experimental groups. Seven pathways showed posterior probabilities greater than 0.4. These pathways involved neuroactive ligand-receptor interaction, phenylalanine, tyrosine and tryptophan biosynthesis, and protein degradation. A Bayesian approach was used to estimate undirected graphical models among the three known genes located in the 1.37 Mbp region (Astn1, Fam5b, and Rfwd2) and genes in each of the 7 pathways identified above and 11 additional pathways known to be involved in blood pressure regulation. The analysis identified several previously unknown relationships between the three candidate genes and genes in pathways that could regulate blood pressure. The study demonstrated a new, unbiased approach for identifying biological pathways mediating the effect of a candidate genomic region on hypertension. [ABSTRACT FROM AUTHOR]

Studies of transcriptome profiles have provided new insights into mechanisms underlying the development of hypertension. Cell type heterogeneity in tissue samples, however, has been a significant hindrance in these studies. We performed a transcriptome analysis in medullary thick ascending limbs (mTALs) of the loop of Henle isolated from Dahl salt-sensitive (SS) rats and salt-insensitive consomic SS.13BN rats on either 0.4% or 7 days of 8% NaCl diet (n=4). The mTAL is a nephron segment importantly implicated in the development of hypertension in SS rats. Pathway analysis was performed based on genes differentially expressed between the two rat strains or by a Bayesian model analysis. The Bayesian model analysis was independent of a priori determination of differential expression and selected pathways by incorporating biological knowledge and expression profiles. Both analytical approaches identified pathways involving cell proliferation, cell cycle regulation, and cytokine signaling. The proliferative state of mTAL cells was analyzed by immunofluorescent staining of Ki-67 and p-H3. Of approximately 4,000 mTAL cells counted in each individual rat, 2.3% to 4.4% were in a proliferative state (positive for Ki-67 staining) when the rats were on the 0.4% salt diet (not significantly different between SS and SS.13BN rats). Exposure to the 8% salt diet for 7 days substantially increased the number of proliferative mTAL cells in both strains. In SS rats on the 8% salt diet, 15.0% of mTAL cells analyzed were in a proliferative state, which was significantly higher than the 10.1% in SS.13BN rats (n=7-9, P<0.05). The total number of cells per mTAL section analyzed was not different between the two strains. The number of cells that were in the G2/M phases (positive for p-H3 staining) tended to be higher in SS rats on the 8% salt diet, but the numbers were small in all treatment groups. The study revealed alterations in regulatory pathways in SS rats in a single cell type, leading to the unexpected finding of a greater increase in the number of proliferative mTAL cells in SS rats on a high-salt diet. [ABSTRACT FROM AUTHOR]

The ability to reliably predict outcomes after trauma in older adults (age ≥ 65 y) is critical for clinical decision making. Using novel machine-learning techniques, we sought to design a nonlinear, competing risks paradigm for prediction of older adult discharge disposition following injury. The National Trauma Databank (NTDB) was used to identify patients 65+ y between 2007 and 2014. Training was performed on an enriched cohort of diverse patients. Factors included age, comorbidities, length of stay, and physiologic parameters to predict in-hospital mortality and discharge disposition (home versus skilled nursing/long-term care facility). Length of stay and discharge status were analyzed via competing risks survival analysis with Bayesian additive regression trees and a multinomial mixed model. The resulting sample size was 47,037 patients. Admission GCS and age were important in predicting mortality and discharge disposition. As GCS decreased, patients were more likely to die (risk ratio increased by average of 1.4 per 2-point drop in GCS, P < 0.001). As GCS decreased, patients were also more likely to be discharged to a skilled nursing or long-term care facility (risk ratio decreased by 0.08 per 2-point decrease in GCS, P < 0.001). The area under curve for prediction of discharge home was improved in the competing risks model 0.73 versus 0.43 in the traditional multinomial mixed model. Predicting older adult discharge disposition after trauma is improved using machine learning over traditional regression analysis. We confirmed that a nonlinear, competing risks paradigm enhances prediction on any given hospital day post injury. [ABSTRACT FROM AUTHOR]

Background: Patient contextual data (PCD) are often missing from electronic health records, limiting the opportunity to incorporate preferences and life circumstances into care. Engaging patients through tools that collect and summarize such data may improve communication and patient activation. However, differential tool adoption by race might widen health care disparities. Objective: Determine if a digital tool designed to collect and present PCD improves communication and patient activation; secondarily, evaluate if use impacts outcomes by race. Design, Setting, and Participants: A pragmatic, two-armed, non-blinded, randomized controlled trial conducted during 2019 in a primary care setting. Intervention: The PCD tool (PatientWisdom) invited patients to identify preferences, values, goals, and barriers to care. Patients were randomized to a standard pre-visit email or facilitated enrollment with dedicated outreach to encourage use of the tool. Main Outcomes and Measures: Outcomes of interest were post-visit patient communication and patient activation measured by the Communication Assessment Tool (CAT) and Patient Activation Measure (PAM), respectively. Outcomes were evaluated using treatment-on-the-treated (TOT) and intention-to-treat (ITT) principles. Key Results: A total of 301 patients were enrolled. Facilitated enrollment resulted in a five-fold increase in uptake of the PCD tool. TOT analysis indicated that the PCD tool was associated with notable increases in specific CAT items rated as excellent: "treated me with respect" (+ 13 percentage points; p = 0.04), "showed interest in my ideas" (+ 14 percentage points; p = 0.03), "showed care and concern" (+ 16 percentage points; p = 0.02), and "spent about the right amount of time with me" (+ 11 percentage points; p = 0.05). There were no significant pre/post-visit differences in PAM scores between arms (− 4.41 percentage points; p = 0.58). ITT results were similar. We saw no evidence of the treatment effect varying by race in ITT or TOT analyses. Conclusions and Relevance: The inclusion of PCD enhanced essential aspects of patient-provider communication but did not affect patient activation. Outcomes did not differ by race. Trial Registration: Clincaltrials.gov identifier: NCT03766841 [ABSTRACT FROM AUTHOR]

PURPOSE: Donor selection practices for matched unrelated donor (MUD) hematopoietic cell transplantation (HCT) vary, and the impact of optimizing donor selection in a patient-specific way using modern machine learning (ML) models has not been studied. METHODS: We trained a Bayesian ML model in 10,318 patients who underwent MUD HCT from 1999 to 2014 to provide patient- and donor-specific predictions of clinically severe (grade 3 or 4) acute graft-versus-host disease or death by day 180. The model was validated in 3,501 patients from 2015 to 2016 with archived records of potential donors at search. Donor selection optimizing predicted outcomes was implemented over either an unlimited donor pool or the donors in the search archives. Posterior mean differences in outcomes from optimal donor selection versus actual practice were summarized per patient and across the population with 95% intervals. RESULTS: Event rates were 33% (training) and 37% (validation). Among donor features, only age affected outcomes, with the effect consistent regardless of patient features. The median (interquartile range) difference in age between the youngest donor at search and the selected donor was 6 (1-10) years, whereas the number of donors per patient younger than the selected donor was 6 (1-36). Fourteen percent of the validation data set had an approximate 5% absolute reduction in event rates from selecting the youngest donor at search versus the actual donor used, leading to an absolute population reduction of 1% (95% interval, 0 to 3). CONCLUSION: We confirmed the singular importance of selecting the youngest available MUD, irrespective of patient features, identified potential for improved HCT outcomes by selecting a younger MUD, and demonstrated use of novel ML models transferable to optimize other complex treatment decisions in a patient-specific way. [ABSTRACT FROM AUTHOR]

In Caucasian and Asian populations, evidence suggests that 24-h blood pressures (BP) are more predictive of long-term cardiovascular events than clinic BP. However, few long-term studies have evaluated the predictive value of 24-h BP phenotypes (24-h, daytime, nighttime) among African Americans (AA). The purpose of this study is to evaluate the added value of 24-h BP phenotypes compared to clinic BP in predicting the subsequent fatal and non-fatal cardiovascular/renal disease events in AA subjects. AA subjects (n = 270) were initially studied between 1994 and 2006 and standardized clinic BP measurements were obtained during screening procedures for a 3-day inpatient clinical study during which 24-h BP measurements were obtained. To assess the subsequent incidence of cardiovascular and renal disease events, follow-up information was obtained and confirmed by review of paper and electronic medical records between 2015 and 2017. During a mean follow-up of 14 ± 4 years, 50 subjects had one or more fatal or non-fatal cardiovascular/renal disease events. After adjustment for covariates, clinic systolic and diastolic BP were strongly associated with cardiovascular/renal disease events and all-cause mortality (p < 0.0001). Twenty-four-hour BP phenotypes conferred a small incremental advantage over clinic BP in predicting cardiovascular/renal events, which was limited to making a difference of one predicted event in 250–1,000 predictions depending on the 24-h BP phenotype. Nocturnal BP was no more predictive than the other 24-h BP phenotypes. In AA, 24-h BP monitoring provides limited added value as a predictor of cardiovascular/renal disease events. Larger studies are needed in AA to confirm these findings. [ABSTRACT FROM AUTHOR]

Racial health disparities continue to be a serious problem in the United States and have been linked to contextual factors, including racial segregation. In some cases, including breast cancer survival, racial disparities appear to be worsening. Using the Home Mortgage Disclosure Act (HMDA) database, we extend current spatial analysis methodology to derive new, spatially continuous indices of (1) racial bias in mortgage lending and (2) redlining. We then examine spatial patterns of these indices and the association between these new measures and breast cancer survival among Black/African American women in the Milwaukee, Wisconsin metropolitan area. These new measures can be used to examine relationships between mortgage discrimination and patterns of disease throughout the United States. [ABSTRACT FROM AUTHOR]

Background: Aromatase inhibitors (AIs) substantially reduce breast cancer mortality in clinical trials, but high rates of nonadherence to these long-term oral therapies have reduced their impact outside of trials. We examined the association of generic AI availability with AI adherence among a large national breast cancer cohort. Methods: Using a quasi-experimental prepost design, we examined the effect of generic AI introductions (7/2010 and 4/2011) on adherence among a national cohort of women with incident breast cancer in 2006 and 2007 who were enrolled in the Medicare D pharmaceutical coverage program. Medicare D claims were used to calculate AI adherence, defined as a medication possession ratio of 80% or more of eligible days, over 36 months. Multivariable logistic regression models estimated with generalized estimating equations were applied to longitudinal adherence data to control for possible confounders, including receipt of a Medicare D low-income subsidy, and to account for repeated measures. All statistical tests were two-sided. Results: Sixteen thousand four hundred sixty-two Medicare D enrollees were eligible. Adherence declined throughout the study. However, among women without a subsidy, the median quarterly out-of-pocket cost of anastrozole fell from $183 in the fourth quarter of 2009 to $15 in 2011, and declines in adherence were attenuated with generic AI introductions. Regression-adjusted adherence probabilities were estimated to be 5.4% higher after generic anastrozole was introduced in 2010 and 11% higher after generic letrozole/exemestane was introduced in 2011. Subsidy recipients had higher adherence rates throughout the study. Conclusions: The introduction of generic medications attenuated the decline in adherence to AIs over three years of treatment among breast cancer survivors not receiving low-income subsidies for Medicare D coverage. [ABSTRACT FROM AUTHOR]

Objectives. We examined whether community translation of an effective evidence-based fall prevention program via standard monetary support can produce a community-wide reduction in fall injuries in older adults and evaluated whether an enhanced version with added technical support and capacity building amplified the fall reduction effect. Methods. We completed a randomized controlled community trial among adults aged 65 and older in (1) 10 control communities receiving no special resources or guidance on fall prevention, (2) 5 standard support communities receiving modest funding to implement Stepping On, and (3) 5 enhanced support communities receiving funding and technical support. The primary outcome was hospital inpatient and emergency department discharges for falls, examined with Poisson regression. Results. Compared with control communities, standard and enhanced support communities showed significantly higher community-wide reductions (9% and 8%, respectively) in fall injuries from baseline (2007-2008) to follow-up (2010-2011). No significant difference was found between enhanced and standard support communities. Conclusions. Population-based fall prevention interventions can be effective when implemented in community settings. More research is needed to identify the barriers and facilitators that influence the successful adoption and implementation of fall prevention interventions into broad community practice. [ABSTRACT FROM AUTHOR]

Background and Aims Persons receiving haemodialysis ( HD) are at increased risk of cognitive impairment ( CI). Since blood pressure ( BP) fluctuations during HD may affect cerebral perfusion - and subsequently cognitive function - we examined the relationship between dialytic BP fluctuation and cognitive outcomes. Methods We included HD patients without diagnosed dementia who were 50 years or older. Using established methods, we classified participants' in CI categories (none to mild and moderate to severe) based on results of a neurocognitive battery. We collected demographic and laboratory data from dialysis unit records, as well as all BP measurements from 12 dialysis sessions. We tested the association between CI and BP fluctuation, adjusting for demographic and laboratory variables. Results Our study enrolled 39 patients; 25 had moderate to severe CI. The normal to mild CI group and the moderate to severe patients had similar degrees of BP fluctuation (average minimum systolic BP ( SBP): 107.6 ± 18.7 vs 110.2 ± 18.6 mmHg, maximum drop in SBP: 32.6 ± 10.2 vs 35.4 ± 15.0 mmHg; proportion of sessions with SBP < 90 mmHg: 0.2 ± 0.3 vs 0.2 ± 0.3; average change in SBP, pre to post HD: 10.2 ± 12.4 vs 11.8 ± 16.4 mmHg, all P > 0.55). There was no association between BP variables and performance on individual cognitive tests. Multivariable analysis showed that older age and non-Caucasian race were associated with a reduction in cognitive scores. Conclusions There was no cross-sectional association between dialytic BP changes and cognitive performance. [ABSTRACT FROM AUTHOR]

R2896 --> 626.2 --> Epigenetics may reflect the interactions between DNA and environment and lifestyle and DNA methylation marks have been implicated in the development and progression of hypertension. In an African American (AA) cohort of hypertensives and normotensives (n = 281), we have recently discovered up to 72 methylation regions (MRs) in whole blood DNA that were significantly associated with 24‐h BP phenotypes (False Discovery Rate (FDR) < 0.05) via reduced representation bisulfite sequencing (RRBS). One‐time clinic BP measurements were not associated with MRs. Upon adjustments for covariates age, sex, and body mass index, 13 MRs remained associated with 24‐h BP phenotypes (FDR < 0.05), each explaining 6.5% ‐ 9.4% of BP variance. Analysis of the chr19 MR in an independent cohort (n=117) using Bisulfite ULtrapLEx Targeted Sequencing (BULLET‐Seq), a new method that we developed, validated its association with 24‐h avg BP phenotypes (FDR < 0.05). In the current study, we functionally annotated the MRs that we identified as uniquely associated with 24‐h BP phenotypes and examined CpG sites previously reported to be associated with BP. Two MRs were near chr1 linkage disequilibrium (LD) regions within genes, PRDM16 and CASZ1, containing BP‐associated sentinel single nucleotide polymorphisms (SNPs). Although no MRs were found to directly overlap with reported BP‐relevant expression or methylation quantitative trait loci (eQTLs or meQTLs), many overlapped with enhancer regions, CTCF‐binding sites, or genes related to hypertension and stroke. To demonstrate consistency with prior studies, we found associations between reported clinic BP‐associated methylation array chip CpGs and the 24‐h BP phenotypes in our study. Of the 16 BP‐associated CpGs from two reports that were detected in both the methylation chip and our RRBS data, several CpGs were significantly associated with 24‐h and clinic BP phenotypes in our cohort (p < 0.05) but not after adjustment for both covariates and FDR. A chr7 CpG (cg06340364) showed significant negative associations with all studied BP phenotypes except nighttime and clinic DBPs (p < 0.05, unadjusted). These investigations highlight the value of regional DNA methylation and the ability to capture the overall effect of environmental and genetic factors that influence BPs over a 24‐h period which have functional epigenomic relevance. [ABSTRACT FROM AUTHOR]

Abstract: Postmortem preservation conditions may be one of factors contributing to wide material property variations in brain tissues in literature. The objective of present study was to determine the effects of preservation temperatures on high strain-rate material properties of brain tissues using the split Hopkinson pressure bar (SHPB). Porcine brains were harvested immediately after sacrifice, sliced into 2mm thickness, preserved in ice cold (group A, 10 samples) and 37°C (group B, 9 samples) saline solution and warmed to 37°C just prior to the test. A SHPB with tube aluminum transmission bar and semi-conductor strain gauges were used to enhance transmitted wave signals. Data were gathered using a digital acquisition system and processed to obtain stress–strain curves. All tests were conducted within 4h postmortem. The mean strain-rate was 2487±72s−1. A repeated measures model with specimen-level random effects was used to analyze log transformed stress–strain responses through the entire loading range. The mean stress–strain curves with ±95% confidence bands demonstrated typical power relationships with the power value of 2.4519 (standard error, 0.0436) for group A and 2.2657 (standard error, 0.0443) for group B, indicating that responses for the two groups are significantly different. Stresses and tangent moduli rose with increasing strain levels in both groups. These findings indicate that storage temperatures affected brain tissue material properties and preserving tissues at 37°C produced a stiffer response at high strain-rates. Therefore, it is necessary to incorporate material properties obtained from appropriately preserved tissues to accurately predict the responses of brain using stress analyses models, such as finite element simulations. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study was to test the hypothesis that the human lumbosacral joint behaves differently from L1–L5 joints and provides primary moment–rotation responses under pure moment flexion and extension and left and right lateral bending on a level-by-level basis. In addition, range of motion (ROM) and stiffness data were extracted from the moment–rotation responses. Ten T12–S1 column specimens with ages ranging from 27 to 68 years (mean: 50.6±13.2) were tested at a load level of 4.0Nm. Nonlinear flexion and extension and left and right lateral bending moment–rotation responses at each spinal level are reported in the form of a logarithmic function. The mean ROM was the greatest at the L5–S1 level under flexion (7.37±3.69°) and extension (4.62±2.56°) and at the L3–L4 level under lateral bending (4.04±1.11°). The mean ROM was the least at the L1–L2 level under flexion (2.42±0.90°), L2–L3 level under extension (1.58±0.63°), and L1–L2 level under lateral bending (2.50±0.75°). The present study proved the hypothesis that L5–S1 motions are significantly greater than L1–L5 motions under flexion and extension loadings, but the hypothesis was found to be untrue under the lateral bending mode. These experimental data are useful in the improved validation of FE models, which will increase the confidence of stress analysis and other modeling applications. [Copyright &y& Elsevier]

Abstract: The objective of this study was to determine the bone mineral density (BMD) of cervical vertebrae and correlate with the lumbar spine. Fifty-seven young adult healthy male volunteers, ranging from 18 to 41 years of age, underwent quantitative computed tomography (QCT) scanning of C2-T1 and L2–L4 vertebrae. To account for correlations, repeated measures techniques were used to compare data as a function of spinal level and region. Linear regression methods were used (±95% CI) to compare data as a function of spinal level and region. The mean age and body height were 25.0 ± 5.8 years and 181.0 ± 7.6 cm. BMD decreased from the rostral to caudal direction along the spinal column. Grouped data indicated that the neck is the densest followed by the first thoracic vertebra and low back with mean BMD of 256.0 ± 48.1, 194.3 ± 44.2, and 172.2 ± 28.4 mg/cm3, respectively; differences were statistically significant. While BMD did not vary significantly between the three lumbar bodies, neck vertebrae demonstrated significant trends. The matrix of correlation coefficients between BMD and spinal level indicated that the relationship is strong in the lumbar (r = 0.92–0.96) and cervical (r = 0.73–0.92) spines. Data from the present study show that the trabecular bony architecture of the neck is significantly different from the low back. These quantitative BMD data from a controlled young adult healthy human male volunteer population may be valuable in establishing normative data specifically for the neck. From a trabecular bone density perspective, these results indicate that lumbar vertebrae cannot act as the best surrogates for neck vertebrae. Significant variations in densities among neck vertebrae, unlike the low back counterpart, may underscore the need to treat these bones as different structures. [Copyright &y& Elsevier]

We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell transplantation (HCT) recipients using a novel machine learning approach, the Nonparametric Failure Time Bayesian Additive Regression Trees (NFT BART). NFT BART models were trained on data from 10,016 patients who underwent a first HLA-A, B, C and DRB1 matched unrelated donor HCT between 2016 and 2019 reported to the CIBMTR, then validated on an independent cohort of 1,802 patients. The NFT BART models were adjusted based on recipient, disease and transplant variables. We defined a clinically meaningful impact on overall survival (OS) or event-free survival (EFS) (survival without relapse, graft failure, or moderate to severe chronic GVHD) as >1% difference in predicted outcome at 3 years. Characteristics with <1% impact (within a zone of indifference) were not considered to be clinically relevant. Donor CMV, parity, HLA-DQB1 and HLA-DPB1 T cell epitope matching fell within the zone of indifference. The only significant donor factor that associated with OS was age, where compared to 18-year-old donors, donors ≥31 years old were associated with lower OS. Both donor age (≤ 32 years old) and use of a male donor, regardless of recipient sex, improved EFS. We therefore recommend selecting the earliest available donor within the 18-30 age range for HCT to optimize OS. If several donors in the 18-30-year-old age range are available, a male donor may be chosen to optimize EFS., (Copyright © 2024 American Society of Hematology.)

Purpose: Reimbursement strategies to regionalize care can be effective for improving patient outcomes but may adversely affect access to care. We sought to determine the effect on travel distance for surgical treatment of a 2009 New York State (NYS) policy restricting Medicaid reimbursement for breast cancer surgery at low-volume hospitals., Patients and Methods: From a linked data set merging the NYS tumor registry with hospital discharge data, we identified women younger than 65 years with stage I-III first breast tumors from pre- and post-policy periods. We classified patients by urbanicity of their residence into four geographic areas (New York City, other large urban core, suburban/large town, and small town/rural). A multivariable difference-in-difference-in-differences model was used to estimate the policy effect on the distance traveled by Medicaid and non-Medicaid insured patients before and after the policy, by area of residence., Results: Among the 46,029 study sample, 13.5% were covered by Medicaid. Regardless of insurance, women treated more recently traveled longer distances to their surgical facility than those in the prepolicy period. Regardless of time period, Medicaid beneficiaries drove fewer miles to treatment than women with other insurance. Although all women traveled greater distances postpolicy, the increase was not significantly different by insurance status (Medicaid or not), except for those living in suburban areas in which Medicaid patients traveled further postpolicy (+7.7 miles compared with +3.4 miles for non-Medicaid; P = .007)., Conclusion: After a policy regionalizing surgical care, only suburban Medicaid patients experienced a statistically significant (albeit small) increase in travel distance compared with non-Medicaid patients. In the state of NY, regionalization of breast cancer care yielded improved outcomes with minimal decrease in access.

Despite the widespread adoption of early warning systems (EWSs), it is uncertain if their implementation improves patient outcomes. The authors report a pre-post quasi-experimental evaluation of a commercially available EWS on patient outcomes at a 700-bed academic medical center. The EWS risk scores were visible in the electronic medical record by bedside clinicians. The EWS risk scores were also monitored remotely 24/7 by critical care trained nurses who actively contacted bedside nurses when a patient's risk levels increased. The primary outcome was inpatient mortality. Secondary outcomes were rapid response team calls and activation of cardiopulmonary arrest (code-4) response teams. The study team conducted a regression discontinuity analysis adjusting for age, gender, insurance, severity of illness, risk of mortality, and hospital occupancy at admission. The analysis included 53,229 hospitalizations. Adjusted analysis showed no significant change in inpatient mortality, rapid response team call, or code-4 activations after implementing the EWS. This study confirms the continued uncertainty in the effectiveness of EWSs and the need for further rigorous examinations of EWSs., (Copyright © 2023 the American College of Medical Quality.)

Background: Residential segregation is an important factor that negatively impacts cancer disparities, yet studies yield mixed results and complicate clear recommendations for policy change and public health intervention. In this study, we examined the relationship between local and Metropolitan Statistical Area (MSA) measures of Black isolation (segregation) and survival among older non-Hispanic (NH) Black women with breast cancer (BC) in the United States. We hypothesized that the influence of local isolation on mortality varies based on MSA isolation-specifically, that high local isolation may be protective in the context of highly segregated MSAs, as ethnic density may offer opportunities for social support and buffer racialized groups from the harmful influences of racism., Methods: Local and MSA measures of isolation were linked by Census Tract (CT) with a SEER-Medicare cohort of 5,231 NH Black women aged 66-90 years with an initial diagnosis of stage I-IV BC in 2007-2013 with follow-up through 2018. Proportional and cause-specific hazards models and estimated marginal means were used to examine the relationship between local and MSA isolation and all-cause and BC-specific mortality, accounting for covariates (age, comorbidities, tumor stage, and hormone receptor status)., Findings: Of 2,599 NH Black women who died, 40.0% died from BC. Women experienced increased risk for all-cause mortality when living in either high local (HR = 1.20; CI = 1.08-1.33; p < 0.001) or high MSA isolation (HR = 1.40; CI = 1.17-1.67; p < 0.001). A similar trend existed for BC-specific mortality. Pairwise comparisons for all-cause mortality models showed that high local isolation was hazardous in less isolated MSAs but was not significant in more isolated MSAs., Interpretation: Both local and MSA isolation are independently associated with poorer overall and BC-specific survival for older NH Black women. However, the impact of local isolation on survival appears to depend on the metropolitan area's level of segregation. Specifically, in highly segregated MSAs, living in an area with high local isolation is not significantly associated with poorer survival. While the reasons for this are not ascertained in this study, it is possible that the protective qualities of ethnic density (e.g., social support and buffering from experiences of racism) may have a greater role in more segregated MSAs, serving as a counterpart to the hazardous qualities of local isolation. More research is needed to fully understand these complex relationships., Funding: National Cancer Institute., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Purpose: Poor women with breast cancer have worse survival than others, and are more likely to undergo surgery in low-volume facilities. We leveraged a natural experiment to study the effectiveness of a policy intervention undertaken by New York (NY) state in 2009 that precluded payment for breast cancer surgery for NY Medicaid beneficiaries treated in facilities performing fewer than 30 breast cancer surgeries annually., Methods: We identified 37,822 women with stage I-III breast cancer during 2004-2008 or 2010-2013 and linked them to NY hospital discharge data. A multivariable difference-in-differences approach compared mortality of Medicaid insured patients with that of commercially or otherwise insured patients unaffected by the policy., Results: Women treated during the postpolicy years had slightly lower 5-year overall mortality than those treated prepolicy; the survival gain was significantly larger for Medicaid patients ( P = .018). Women enrolled in Medicaid had a greater reduction than others in breast cancer-specific mortality ( P = .005), but no greater reduction in other causes of death ( P = .50). Adjusted breast cancer mortality among women covered by Medicaid declined from 6.6% to 4.5% postpolicy, while breast cancer mortality among other women fell from 3.9% to 3.8%. A similar effect was not observed among New Jersey Medicaid patients with breast cancer treated during the same years., Conclusion: A statewide centralization policy discouraging initial care for breast cancer in low-volume facilities was associated with better survival for the Medicaid population targeted. Given these impressive results and those from prior research, other policymakers should consider adopting comparable policies to improve breast cancer outcomes.[Media: see text].

Purpose: Over 50% of breast cancer patients prescribed a 5-year course of daily oral adjuvant endocrine therapy (ET) are nonadherent. We investigated the role of costs and cancer medication delivery mode and other medication delivery factors on adherence., Methods: We conducted a retrospective cohort study of commercially insured and Medicare advantage patients with newly diagnosed breast cancer in 2007-2015 who initiated ET. We examined the association between 12-month ET adherence (proportion of days covered by fills ≥ 0.80) and ET copayments, 90-day prescription refill use, mail order pharmacy use, number of pharmacies, and synchronization of medications. We used regression models to estimate nonadherence risk ratios adjusted for demographics (age, income, race, urbanicity), comorbidities, total medications, primary cancer treatments, and generic AI availability. Sensitivity analyses were conducted using alternative specifications for independent variables., Results: Mail order users had higher adherence in both commercial and Medicare-insured cohorts. Commercially insured patients who used mail order were more likely to be adherent if they had low copayments (< $5) and 90-day prescription refills. For commercially insured patients who used local pharmacies, use of one pharmacy and better synchronized refills were also associated with adherence. Among Medicare patients who used mail order pharmacies, only low copayments were associated with adherence, while among Medicare patients using local pharmacies both low copayments and 90-day prescriptions were associated with ET adherence., Conclusion: Out-of-pocket costs, medication delivery mode, and other pharmacy-related medication delivery factors are associated with adherence to breast cancer ET. Future work should investigate whether interventions aimed at streamlining medication delivery could improve adherence for breast cancer patients., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Estimation of long-term quality of life in patients sustaining Traumatic brain injuries is a difficult but important task during the early hospitalization. There are very limited tools to assess these outcomes, therefore we aimed to develop a predictive model for quality-of-life that could be used in hospitalized adults with TBIs., Methods: The TRACK-TBI dataset was used to identify adult patients with TBI from 2014 to 2018. Multiple variables were assessed to predict favorable versus unfavorable scores on the Quality of Life after Brain Injury-Overall Scale (QOLIBRI-OS)., Results: We included 1549 subjects. 57% had a favorable outcome, and were more likely to have private insurance, higher GCS scores, and fewer comorbidities. A model (TBI-PRO) for 3, 6, and 12-month QOLIBRI score was created. The AUROCs for predicting 3, 6 and 12-month favorable QOLIBRI scores were 0.81, 0.79, and 0.76, respectively., Conclusion: The TBI-PRO model adequately estimates long-term outcomes in patients with TBI., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Importance: Health care systems have implemented remote patient monitoring (RPM) programs to manage patients with COVID-19 at home, but the associations between participation and outcomes or resource utilization are unclear., Objective: To assess whether an RPM program for COVID-19 is associated with lower or higher likelihood of hospitalization and whether patients who are admitted present earlier or later for hospital care., Design, Setting, and Participants: This retrospective, observational, cohort study of RPM was performed at Froedtert & Medical College of Wisconsin Health Network, an academic health system in southeastern Wisconsin. Participants included patients with internal primary care physicians and a positive SARS-CoV-2 test in the ambulatory setting between March 30, 2020, and December 15, 2020. Data analysis was performed from February 15, 2021, to February 2, 2022., Exposures: Activation of RPM program., Main Outcomes and Measures: Hospitalizations within 2 to 14 days of a positive test. Inverse propensity score weighting was used to account for differences between groups. Sensitivity analyses were performed looking at usage of the RPM among patients who activated the program., Results: A total of 10 660 COVID-19-positive ambulatory patients were eligible, and 9378 (88.0%) had email or mobile numbers on file and were invited into the RPM program; the mean (SD) age was 46.9 (16.3) years and 5448 patients (58.1%) were women. Patients who activated monitoring (5364 patients [57.2%]) had a mean (SD) of 35.3 (33.0) check-ins and a mean (SD) of 1.27 (2.79) (median [IQR], 0 [0-1]) free-text comments. A total of 878 patients (16.4%) experienced at least 1 alert; 128 of 5364 activated patients (2.4%) and 158 of 4014 inactivated patients (3.9%) were hospitalized (χ21 = 18.65; P < .001). In weighted regression analysis, activation of RPM was associated with a lower odds of hospitalization (odds ratio, 0.68; 95% CI, 0.54-0.86; P = .001) adjusted for demographics, comorbidities, and time period. Monitored patients had a longer mean (SD) time between test and hospitalization (6.67 [3.21] days vs 5.24 [3.03] days), a shorter length of stay (4.44 [4.43] days vs 7.14 [8.63] days), and less intensive care use (15 patients [0.3%] vs 44 patients [1.1%])., Conclusions and Relevance: These findings suggest that activation of an RPM program is associated with lower hospitalization, intensive care use, and length of stay among patients with COVID-19.

Background: Epigenetic marks (eg, DNA methylation) may capture the effect of gene-environment interactions. DNA methylation is involved in blood pressure (BP) regulation and hypertension development; however, no studies have evaluated its relationship with 24-hour BP phenotypes (daytime, nighttime, and 24-hour average BPs)., Methods: We examined the association of whole blood DNA methylation with 24-hour BP phenotypes and clinic BPs in a discovery cohort of 281 Blacks participants using reduced representation bisulfite sequencing. We developed a deep and region-specific methylation sequencing method, Bisulfite ULtrapLEx Targeted Sequencing and utilized it to validate our findings in a separate validation cohort (n=117)., Results: Analysis of 38 215 DNA methylation regions (MRs), derived from 1 549 368 CpG sites across the genome, identified up to 72 regions that were significantly associated with 24-hour BP phenotypes. No MR was significantly associated with clinic BP. Two to 3 MRs were significantly associated with various 24-hour BP phenotypes after adjustment for age, sex, and body mass index. Together, these MRs explained up to 16.5% of the variance of 24-hour average BP, while age, sex, and BMI explained up to 11.0% of the variance. Analysis of one of the MRs in an independent cohort using Bisulfite ULtrapLEx Targeted Sequencing confirmed its association with 24-hour average BP phenotype., Conclusions: We identified several MRs that explain a substantial portion of variances in 24-hour BP phenotypes, which might be excellent markers of cumulative effect of factors influencing 24-hour BP levels. The Bisulfite ULtrapLEx Targeted Sequencing workflow has potential to be suitable for clinical testing and population screenings on a large scale.