Reporting and analysis of sex in vascular surgery research.

OBJECTIVE: To examine sex in human vascular surgery research by quantifying the inclusion and analysis of sex-based data in high-impact vascular surgery journals. METHODS: A bibliographic review of original articles published in the European Journal of Vascular and Endovascular Surgery, Journal of Vascular Surgery, JVS: Venous and Lymphatic Disorders, Journal of Endovascular Therapy, and Annals of Vascular Surgery from January 1, 2018, to December 31, 2020, and from January 1, 2023, to December 31, 2023, was conducted. Abstracted data included sex-based data analysis, inclusion of sex as a variable in multivariable analysis, inclusion of sex as an independent variable, and a discussion of sex-based results. RESULTS: Of the 3762 articles that included human, animal, or cell subjects, 249 (6.6%) did not state sex. Of those 249 articles, 183 included human subjects, 55 included animal subjects, and 11 used cell lines as the subjects. These were removed from analysis as well as the remaining 68 articles with animal subjects. In addition, 23 researched a sex-specific pathology and were removed from analysis. Of the remaining 3422 articles included in our study, 42.3% analyzed sex, 46.9% included sex in multivariable analysis, 4.8% included sex as an independent variable, and 26.6% included a discussion of sex. There were no significant differences in all four sex variables between 2018, 2019, and 2020. Between 2018-2020 and 2023, there were significant increases in all four sex variables. Multicenter studies had significantly higher rates of independent analysis of sex over single-center studies (7.4% vs 3.3%, P < .001). There was no significant difference in independent analysis of sex between U.S.-based and non-U.S.-based studies. Only 191 articles (5.6%) had 90% or greater matching of men and women in their study. CONCLUSIONS: Equitable inclusion and analysis of sex is rare in vascular surgery research. Less than 5% of articles included an independent analysis of data by sex, and few studies included males and females equally. Clinical research is the basis for evidence-based medicine; therefore, it is important to strive for equitable inclusion, analysis, and reporting of data to foster generalizability of clinical research to men and women.

Traveling Long Distances for Rectal Cancer Care: Institutional Outcomes and Patient Experiences.

INTRODUCTION: Mounting evidence supports traveling to high-volume centers for complex surgical procedures, such as a proctectomy, yet the burden of travel and outcomes of patients traveling long distances is not yet clear. Thus, we aimed to evaluate oncologic outcomes, quality of life, and travel burdens for patients treated for rectal cancer at a single tertiary-care institution. METHODS: A retrospective study of patients treated with proctectomy for locally advanced rectal cancer was performed comparing long and short travel distance (STD) cohorts. Primary outcome measures included overall mortality, disease recurrence, and quality of life. Secondary outcomes included out-of-pocket expenses. The cohorts were compared using Wilcoxon rank-sum and Chi-square tests for continuous and categorical variables, respectively. Kaplan-Meier plots were created to evaluate overall and disease-free survival. RESULTS: Among 102 patients, 51 (50%) were classified as long travel distance (LTD, mean 57.8 miles) and 51 (50%) were classified as STD (mean 12.8 miles). There was no statistical difference in 5-y mortality (4% LTD versus 4% STD, P = 1.000), disease recurrence (26% LTD versus 18% STD, P = 0.336), or quality of life (0.85 LTD versus 0.87 STD, P = 0.690). The LTD cohort did have significantly lower postresection compliance with surveillance (84% LTD versus 96% STD, P = 0.046). LTD cohort also had significantly more lodging ($77.1 LTD versus $0 STD, P = 0.025) and transportation expenses ($133.6 LTD versus $92.6 STD, P = 0.010). CONCLUSIONS: As the surgical management of rectal cancer becomes increasingly centralized, this study found patients who traveled long-distances received comparable care with outcomes similar to those who lived locally. Higher travel costs and lower compliance with surveillance were identified as barriers to care in the long-distance population, but a number of solutions can be implemented to address these issues.

Can We Actually Predict Long-Term Patient Satisfaction After Traumatic Brain Injury?

INTRODUCTION: The Traumatic Brain Injury - Patient Reported Outcome (TBI-PRO) model was previously derived to predict long-term patient satisfaction as assessed by the Quality of Life After Brain Injury (QOLIBRI) score. The aim of this study is to externally and prospectively validate the TBI-PRO model to predict long-term patient-reported outcomes and to derive a new model using a larger dataset of older adults with TBI. METHODS: Patients admitted to a Level I trauma center with TBI were prospectively followed for 1 y after injury. Outcomes predicted by the TBI-PRO model based on admission findings were compared to actual QOLIBRI scores reported by patients at 3,6, and 12 mo. When deriving a new model, Collaborative European NeuroTrauma Effectiveness Research in TBI and the Transforming Research and Clinical Knowledge in Traumatic Brain Injury databases were used to identify older adults (≥50 y) with TBI from 2014 to 2018. Bayesian additive regression trees were used to identify predictive admission covariates. The coefficient of determination was used to identify the fitness of the model. RESULTS: For prospective validation, a total of 140 patients were assessed at 3 mo, with follow-up from 69 patients at 6 mo and 13 patients at 12 mo postinjury. The area under receiver operating curve of the TBI-PRO model for predicting favorable outcomes at 3, 6, and 12 mo were 0.65, 0.57, and 0.62, respectively. When attempting to derive a novel predictive model, a total of 1521 patients (80%) was used in the derivation dataset while 384 (20%) were used in the validation dataset. A past medical history of heart conditions, initial hospital length of stay, admission systolic blood pressure, age, number of reactive pupils on admission, and the need for craniectomy were most predictive of long-term QOLIBRI-Overall Scale. The coefficient of determination for the validation model including only the most predictive variables were 0.28, 0.19, and 0.27 at 3, 6, and 12 mo, respectively. CONCLUSIONS: In the present study, the prospective validation of a previously derived TBI-PRO model failed to accurately predict a long-term patient reported outcome measures in TBI. Additionally, the derivation of a novel model in older adults using a larger database showed poor accuracy in predicting long-term health-related quality of life. This study demonstrates limitations to current targeted approaches in TBI care. This study provides a framework for future studies and more targeted datasets looking to assess long-term quality of life based upon early hospital variables and can serve as a starting point for future predictive analysis.

Nonparametric failure time: Time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures.

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.

The Variation of Withdrawal of Life Sustaining Therapy in Older Adults With Traumatic Brain Injury.

INTRODUCTION: The decision to withdraw life sustaining treatment (WDLST) in older adults with traumatic brain injury is subject to wide variability leading to nonbeneficial interventions and unnecessary use of hospital resources. We hypothesized that patient and hospital factors are associated with WDLST and WDLST timing. METHODS: All traumatic brain injury patients ≥65 with Glasgow coma scores (GCS) of 4-11 from 2018 to 2019 at level I and II centers were selected from the National Trauma Data Bank. Patients with head abbreviated injury scores 5-6 or death within 24 h were excluded. Bayesian additive regression tree analysis was performed to identify the cumulative incidence function (CIF) and the relative risks (RR) over time for withdrawal of care, discharge to hospice (DH), and death. Death alone (no WDLST or DH) served as the comparator group for all analyses. A subanalysis of the composite outcome WDLST/DH (defined as end-of-life-care), with death (no WDLST or DH) as a comparator cohort was performed. RESULTS: We included 2126 patients, of whom 1957 (57%) underwent WDLST, 402 (19%) died, and 469 (22%) were DH. 60% of patients were male, and the mean age was 80 y. The majority of patients were injured by fall (76%, n = 1644). Patients who were DH were more often female (51% DH versus 39% WDLST), had a past medical history of dementia (45% DH versus 18% WDLST), and had lower admission injury severity score (14 DH versus 18.6 WDLST) (P < 0.001). Compared to those who DH, those who underwent WDLST had a lower GCS (9.8 versus 8.4, P < 0.001). CIF of WDSLT and DH increased with age, stabilizing by day 3. At day 3, patients ≥90 y had an increased RR of DH compared to WDLST (RR 2.5 versus 1.4). As GCS increased, CIF and RR of WDLST decreased, while CIF and RR of DH increased (RR on day 3 for GCS 12: WDLST 0.42 versus DH 1.31).Patients at nonprofit institutions were more likely to undergo WDLST (RR 1.15) compared to DH (0.68). Compared to patients of White race, patients of Black race had a lower RR of WDLST at all timepoints. CONCLUSIONS: Patient and hospital factors influence the practice of end-of-life-care (WDLST, DH, and death), highlighting the need to better understand variability to target palliative care interventions and standardize care across populations and trauma centers.

Improved Prediction of Older Adult Discharge After Trauma Using a Novel Machine Learning Paradigm.

BACKGROUND: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Endothelial Rap1 (Ras-Association Proximate 1) Restricts Inflammatory Signaling to Protect From the Progression of Atherosclerosis.

OBJECTIVE: Small GTPase Rap1 (Ras-association proximate 1) is a novel, positive regulator of NO release and endothelial function with a potentially key role in mechanosensing of atheroprotective, laminar flow. Our objective was to delineate the role of Rap1 in the progression of atherosclerosis and its specific functions in the presence and absence of laminar flow, to better define its role in endothelial mechanisms contributing to plaque formation and atherogenesis. Approach and Results: In a mouse atherosclerosis model, endothelial Rap1B deletion exacerbates atherosclerotic plaque formation. In the thoracic aorta, where laminar shear stress-induced NO is otherwise atheroprotective, plaque area is increased in Athero-Rap1BiΔEC (atherogenic endothelial cell-specific, tamoxifen-inducible Rap1A+Rap1B knockout) mice. Endothelial Rap1 deficiency also leads to increased plaque size, leukocyte accumulation, and increased CAM (cell adhesion molecule) expression in atheroprone areas, whereas vascular permeability is unchanged. In endothelial cells, in the absence of protective laminar flow, Rap1 deficiency leads to an increased proinflammatory TNF-α (tumor necrosis factor alpha) signaling and increased NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) activation and elevated inflammatory receptor expression. Interestingly, this increased signaling to NF-κB activation is corrected by AKTVIII-an inhibitor of Akt (protein kinase B) translocation to the membrane. Together, these data implicate Rap1 in restricting Akt-dependent signaling, preventing excessive cytokine receptor signaling and proinflammatory NF-κB activation. CONCLUSIONS: Via 2 distinct mechanisms, endothelial Rap1 protects from the atherosclerosis progression in the presence and absence of laminar flow; Rap1-stimulated NO release predominates in laminar flow, and restriction of proinflammatory signaling predominates in the absence of laminar flow. Our studies provide novel insights into the mechanisms underlying endothelial homeostasis and reveal the importance of Rap1 signaling in cardiovascular disease.

Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.

OBJECTIVE: To create a new methodology that has a single simple rule to identify height outliers in the electronic health records (EHR) of children. METHODS: We constructed 2 independent cohorts of children 2 to 8 years old to train and validate a model predicting heights from age, gender, race and weight with monotonic Bayesian additive regression trees. The training cohort consisted of 1376 children where outliers were unknown. The testing cohort consisted of 318 patients that were manually reviewed retrospectively to identify height outliers. RESULTS: The amount of variation explained in height values by our model, R2 , was 82.2% and 75.3% in the training and testing cohorts, respectively. The discriminatory ability to assess height outliers in the testing cohort as assessed by the area under the receiver operating characteristic curve was excellent, 0.841. Based on a relatively aggressive cutoff of 0.075, the outlier sensitivity is 0.713, the specificity 0.793; the positive predictive value 0.615 and the negative predictive value is 0.856. CONCLUSIONS: We have developed a new reliable, largely automated, outlier detection method which is applicable to the identification of height outliers in the pediatric EHR. This methodology can be applied to assess the veracity of height measurements ensuring reliable indices of body proportionality such as body mass index.

Environmental health literacy for Anishinaabe (Great Lakes Native American) fish consumers: A randomized control trial.

BACKGROUND: Fish consumption comprises an important part of what the Anishinaabe (Great Lakes Native Americans) call "minobimaadiziiwin" which translates roughly to "living in a good way". Industrial activity leading to the accumulation of persistent contaminants in fish disrupts minobimaadiziiwin. Our team of academic and Anishinaabe scientists co-developed a fish consumption advisory for the Anishinaabe using software that can be accessed via mobile phones and/or the internet. OBJECTIVES: The software, Gigiigoo'inaan ("our fish") is designed to improve environmental health literacy using culturally congruent messaging and aesthetics. We tested the following hypotheses: 1) the Gigiigoo'inaan would encourage consumption of fish high in Polyunsaturated Omega-3 fatty acids (PFUA-3) whilst minimizing contaminant intake (methylmercury (MeHg) and Polychorinated Biphenyls (PCBs)); and 2) intervention participants will be more likely than controls to achieve a favorable n-3 PUFA/MeHg consumption ratios. METHODS: We conducted a randomized controlled trial with prospective self-reported fish consumption using automated email surveys. One-month pre and one month post, control and intervention outcome variables were calculated per participant as µg/kg/day of MeHg, µg/kg/day of PCB, g of fish, and mg/day of EPA+DHA. These were modeled using an analysis of covariance (ANCOVA) with a-priori covariates: age, sex, and tribal affiliation. RESULTS: Most participants in both trial arms reported eating relatively elevated amounts of fish yet remained within advisory guidelines for contaminants. EPA+DHA:MeHg ratios were also favorable in most participants. Advisory limits for contaminants were exceeded by relatively few participants in the study. DISCUSSION: Gigiigoo'inaan was previously reported to increase confidence, the current user feedback confirms this. Most participants ate fish but did not exceed the advisory limits, which demonstrates Environmental Health Literacy progress in the region despite a lack of observed behavior change during the trial. A small number of participants exceeded contaminant intake guidelines which matches the pilot work for this study.

Non-parametric recurrent events analysis with BART and an application to the hospital admissions of patients with diabetes.

Much of survival analysis is concerned with absorbing events, i.e., subjects can only experience a single event such as mortality. This article is focused on non-absorbing or recurrent events, i.e., subjects are capable of experiencing multiple events. Recurrent events have been studied by many; however, most rely on the restrictive assumptions of linearity and proportionality. We propose a new method for analyzing recurrent events with Bayesian Additive Regression Trees (BART) avoiding such restrictive assumptions. We explore this new method via a motivating example of hospital admissions for diabetes patients and simulated data sets.

Nonparametric machine learning for precision medicine with longitudinal clinical trials and Bayesian additive regression trees with mixed models.

Precision medicine is an active area of research that could offer an analytic paradigm shift for clinical trials and the subsequent treatment decisions based on them. Clinical trials are typically analyzed with the intent of discovering beneficial treatments if the same treatment is applied to the entire population under study. But, such a treatment strategy could be suboptimal if subsets of the population exhibit varying treatment effects. Identifying subsets of the population experiencing differential treatment effect and forming individualized treatment rules is a task well-suited to modern machine learning methods such as tree-based ensemble predictive models. Specifically, Bayesian additive regression trees (BART) has shown promise in this regard because of its exceptional performance in out-of-sample prediction. Due to the unique inferential needs of precision medicine for clinical trials, we have proposed the BART extensions explicated here. We incorporate random effects for longitudinal repeated measures and subject clustering within medical centers. The addition of a novel interaction detection prior to identify treatment heterogeneity among clinical trial patients and its association with patient characteristics. These extensions are unified under a framework that we call mixedBART. Simulation studies and applications of precision medicine based on real randomized clinical trials data examples are presented.

Influence of mid-life cognitive activity on cognitive function among men aged 68 years or older.

BACKGROUND: Cognitive activity in early and late life has been associated with increased cognitive function among older adults. There is less evidence on the effects of midlife cognitive activity. AIMS: We examined the association of midlife cognitive activity with cognitive function after age 65. METHODS: We studied 78 men 68 years old or older. We asked participants to assess their current and midlife cognitive activity using adaptations of a measure created by Wilson et al., which includes reading, writing letters, visiting museums and other leisure activities. Our outcomes were validated measures of cognitive and overall function. We compared midlife cognitive activity to our outcome measures in simple bivariable analyses, then adjusted for demographic characteristics using linear regression. RESULTS: Our study population of older (mean age 74.8 years) men was primarily white (87%) and well-educated; 65% had at least some post high school education. Although 67% were retired, household income was high (24% < $30 k and 44% > $50 k). More midlife cognitive activity was related to more current cognitive activity (p = < .0001, r2 = 0.55339). However, midlife activity was not associated with measures of cognitive or overall function, adjusted analyses gave similar results. DISCUSSION: We did not find an association between midlife cognitive activity and later life function. However, the Wilson measure of cognitive activity that we used excludes instrumental cognitive activities such as dealing with finances or healthcare, likely underestimating cognitive activity for many participants. CONCLUSION: Midlife cognitive activity was associated with late-life cognitive activity, suggesting efforts to increase late-life cognitive activity may need to start earlier in life. However, more robust measures of everyday cognitive activity might detect such an association.

Contribution of KV1.5 Channel to Hydrogen Peroxide-Induced Human Arteriolar Dilation and Its Modulation by Coronary Artery Disease.

RATIONALE: Hydrogen peroxide (H2O2) regulates vascular tone in the human microcirculation under physiological and pathophysiological conditions. It dilates arterioles by activating large-conductance Ca2+-activated K+ channels in subjects with coronary artery disease (CAD), but its mechanisms of action in subjects without CAD (non-CAD) when compared with those with CAD remain unknown. OBJECTIVE: We hypothesize that H2O2-elicited dilation involves different K+ channels in non-CAD versus CAD, resulting in an altered capacity for vasodilation during disease. METHODS AND RESULTS: H2O2 induced endothelium-independent vasodilation in non-CAD adipose arterioles, which was reduced by paxilline, a large-conductance Ca2+-activated K+ channel blocker, and by 4-aminopyridine, a voltage-gated K+ (KV) channel blocker. Assays of mRNA transcripts, protein expression, and subcellular localization revealed that KV1.5 is the major KV1 channel expressed in vascular smooth muscle cells and is abundantly localized on the plasma membrane. The selective KV1.5 blocker diphenylphosphine oxide-1 and the KV1.3/1.5 blocker 5-(4-phenylbutoxy)psoralen reduced H2O2-elicited dilation to a similar extent as 4-aminopyridine, but the selective KV1.3 blocker phenoxyalkoxypsoralen-1 was without effect. In arterioles from CAD subjects, H2O2-induced dilation was significantly reduced, and this dilation was inhibited by paxilline but not by 4-aminopyridine, diphenylphosphine oxide-1, or 5-(4-phenylbutoxy)psoralen. KV1.5 cell membrane localization and diphenylphosphine oxide-1-sensitive K+ currents were markedly reduced in isolated vascular smooth muscle cells from CAD arterioles, although mRNA or total cellular protein expression was largely unchanged. CONCLUSIONS: In human arterioles, H2O2-induced dilation is impaired in CAD, which is associated with a transition from a combined large-conductance Ca2+-activated K+- and KV (KV1.5)-mediated vasodilation toward a large-conductance Ca2+-activated K+-predominant mechanism of dilation. Loss of KV1.5 vasomotor function may play an important role in microvascular dysfunction in CAD or other vascular diseases.

Prevalence and Consequences of Axillary Lymph Node Dissection in the Era of Sentinel Lymph Node Biopsy for Breast Cancer.

BACKGROUND: Despite clear guidelines for its use and wide adoption, no population-based study has examined the extent to which patients with early stage breast cancer are benefiting from sentinel lymph node biopsy (SLNB) by being spared a potentially avoidable axillary lymph node dissection (ALND) and its associated morbidity. OBJECTIVE: Examine variation in type of axillary surgery performed by surgeon volume; investigate the extent and consequences of potentially avoidable ALND. RESEARCH DESIGN/SUBJECTS: Observational study of older women with pathologically node-negative stage I-II invasive breast cancer who underwent surgery in a SEER state in 2008-2009. MEASURES: Surgeon annual volume of breast cancer cases and type of axillary surgery were determined by Medicare claims. An estimated probability of excess lymphedema due to ALND was calculated. RESULTS: Among 7686 pathologically node-negative women, 49% underwent ALND (either initially or after SLNB) and 25% were operated on by low-volume surgeons. Even after adjusting for demographic and tumor characteristics, women treated by higher volume surgeons were less likely to undergo ALND [medium volume: odds ratio, 0.69 (95% confidence interval, 0.51-0.82); high volume: odds ratio, 0.59 (95% confidence interval, 0.45-0.76)]. Potentially avoidable ALND cases were estimated to represent 21% of all expected lymphedema cases. CONCLUSIONS: In this pathologically node-negative population-based breast cancer cohort, only half underwent solely SLNB. Patients treated by low-volume surgeons were more likely to undergo ALND. Resources and guidelines on the appropriate training and competency of surgeons to assure the optimal performance of SLNB should be considered to decrease rates of potentially avoidable ALND and lymphedema.

Effect of hospital volume on processes of breast cancer care: A National Cancer Data Base study.

BACKGROUND: The purpose of this study was to examine variations in delivery of several breast cancer processes of care that are correlated with lower mortality and disease recurrence, and to determine the extent to which hospital volume explains this variation. METHODS: Women who were diagnosed with stage I-III unilateral breast cancer between 2007 and 2011 were identified within the National Cancer Data Base. Multiple logistic regression models were developed to determine whether hospital volume was independently associated with each of 10 individual process of care measures addressing diagnosis and treatment, and 2 composite measures assessing appropriateness of systemic treatment (chemotherapy and hormonal therapy) and locoregional treatment (margin status and radiation therapy). RESULTS: Among 573,571 women treated at 1755 different hospitals, 38%, 51%, and 10% were treated at high-, medium-, and low-volume hospitals, respectively. On multivariate analysis controlling for patient sociodemographic characteristics, treatment year and geographic location, hospital volume was a significant predictor for cancer diagnosis by initial biopsy (medium volume: odds ratio [OR] = 1.15, 95% confidence interval [CI] = 1.05-1.25; high volume: OR = 1.30, 95% CI = 1.14-1.49), negative surgical margins (medium volume: OR = 1.15, 95% CI = 1.06-1.24; high volume: OR = 1.28, 95% CI = 1.13-1.44), and appropriate locoregional treatment (medium volume: OR = 1.12, 95% CI = 1.07-1.17; high volume: OR = 1.16, 95% CI = 1.09-1.24). CONCLUSIONS: Diagnosis of breast cancer before initial surgery, negative surgical margins and appropriate use of radiation therapy may partially explain the volume-survival relationship. Dissemination of these processes of care to a broader group of hospitals could potentially improve the overall quality of care and outcomes of breast cancer survivors. Cancer 2017;123:957-66. © 2016 American Cancer Society.

Aortic stiffening precedes onset of heart failure with preserved ejection fraction in patients with asymptomatic diastolic dysfunction.

BACKGROUND: Identifying which patients with diastolic dysfunction will progress to heart failure with preserved ejection fraction (HFpEF) remains challenging. The goal of this study is to determine whether increased vascular stiffness as identified on 2D transthoracic echocardiography (TTE) serves as a biomarker for the development of HFpEF in patients with diastolic dysfunction. METHODS: The study design is a matched retrospective case-control study. Subjects with diastolic dysfunction were divided into two groups based on whether they had a clinical diagnosis of HFpEF. The two groups were matched based on age, gender, race and body surface area, resulting in 77 matched pairs (n = 154). Data from the first TTE that documented diastolic dysfunction prior to the development of HFpEF was extracted along with baseline demographic and clinical data. Indices of vascular stiffness were measured and compared. A sub-group analysis was performed to compare diabetic subjects in Group 1 (n = 43) to those in Group 2 (n = 21). RESULTS: Group 1 had significantly decreased aortic distensibility as measured on the initial TTE when compared to Group 2 (1.9 ± 1.0 vs. 2.8 ± 1.8 cm2dyne-110-3, p = 0.01). In the diabetic subset, Group 1 had significantly less aortic strain (6.9 ± 3.3 vs. 9.7 ± 5.6%, p = 0.02) and aortic distensibility (1.8 ± 1.0 vs. 3.5 ± 2.6 cm2dyne-110-3, p = 0.02) compared to Group 2. Other indices of vascular stiffness did not differ significantly between groups. CONCLUSIONS: This study demonstrates that increased proximal aortic stiffness is associated with the development of HFpEF in patients with asymptomatic diastolic dysfunction. Larger prospective studies are needed to further investigate this relationship.

Outcomes of Allogeneic Hematopoietic Cell Transplantation in Children and Young Adults with Chronic Myeloid Leukemia: A CIBMTR Cohort Analysis.

Chronic myeloid leukemia (CML) in children and young adults is uncommon. Young patients have long life expectancies and low morbidity with hematopoietic cell transplantation (HCT). Prolonged tyrosine kinase inhibitor (TKI) use may cause significant morbidity. In addition, indication for HCT in patients in the first chronic phase is not established. We hence retrospectively evaluated outcomes in 449 CML patients with early disease receiving myeloablative HCT reported to the CIBMTR. We analyzed various factors affecting outcome, specifically the effect of age and pre-HCT TKI in pediatric patients (age < 18 years, n = 177) and young adults (age 18 to 29 years, n = 272) with the goal of identifying prognostic factors. Post-HCT probability rates of 5-year overall survival (OS) and leukemia-free survival (LFS) were 75% and 59%, respectively. Rates of OS and LFS were 76% and 57% in <18-year and 74% and 60% in 18- to 29-year group, respectively, by univariate analysis (P = .1 and = .6). Five-year rates of OS for HLA matched sibling donor (MSD) and bone marrow (BM) stem cell source were 83% and 80%, respectively. In multivariate analysis there was no effect of age (<18 versus 18 to 29) or pre-HCT TKI therapy on OS, LFS, transplant related mortality, or relapse. Favorable factors for OS were MSD (P < .001) and recent HCT (2003 to 2010; P = .04). LFS was superior with MSD (P < .001), BM as graft source (P = .001), and performance scores > 90 (P = .03) compared with unrelated or mismatched peripheral blood stem cells donors and recipients with lower performance scores. Older age was associated with increased incidence of chronic graft-versus-host disease (P = .0002). In the current era, HCT outcomes are similar in young patients and children with early CML, and best outcomes are achieved with BM grafts and MSD.

Nonparametric survival analysis using Bayesian Additive Regression Trees (BART).

Bayesian additive regression trees (BART) provide a framework for flexible nonparametric modeling of relationships of covariates to outcomes. Recently, BART models have been shown to provide excellent predictive performance, for both continuous and binary outcomes, and exceeding that of its competitors. Software is also readily available for such outcomes. In this article, we introduce modeling that extends the usefulness of BART in medical applications by addressing needs arising in survival analysis. Simulation studies of one-sample and two-sample scenarios, in comparison with long-standing traditional methods, establish face validity of the new approach. We then demonstrate the model's ability to accommodate data from complex regression models with a simulation study of a nonproportional hazards scenario with crossing survival functions and survival function estimation in a scenario where hazards are multiplicatively modified by a highly nonlinear function of the covariates. Using data from a recently published study of patients undergoing hematopoietic stem cell transplantation, we illustrate the use and some advantages of the proposed method in medical investigations. Copyright © 2016 John Wiley & Sons, Ltd.

In Vivo T Cell Depletion with Myeloablative Regimens on Outcomes after Cord Blood Transplantation for Acute Lymphoblastic Leukemia in Children.

The inclusion of antithymocyte globulin (ATG) in cord blood transplantation is controversial. We evaluated outcomes according to ATG inclusion in 297 children and adolescents with acute lymphoblastic leukemia (ALL) who received myeloablative total body irradiation-based conditioning and either single-unit (74%) or double-unit (26%) grafts. Ninety-two patients (31%) received ATG and 205 (69%) did not. ATG recipients were more likely to be cytomegalovirus seronegative. The incidences of day 100 grades II to IV acute graft-versus-host disease (GVHD; 30% versus 54%, P = .0002) and chronic GVHD (22% versus 43%, P = .0008) were lower with ATG compared with non-ATG regimens. However, day 100 grades III to IV acute GVHD was comparable (11% versus 17%, P = .15). The 3-year incidences of transplant-related mortality (16% versus 17%, P = .98), relapse (17% versus 27%, P = .12), and leukemia-free survival (66% versus 55%, P = .23) in ATG and non-ATG recipients were similar. There were no differences in viral reactivation between treatment groups (60% versus 58%, P = .83). Therefore, the data suggest that incorporation of ATG with myeloablative conditioning regimens may be useful in reducing the risk of acute and chronic GVHD without any deleterious effect on transplant-related mortality, relapse, or leukemia-free survival in children and adolescents with ALL.

Effects of Singing on Vascular Health in Older Adults with Coronary Artery Disease: A Randomized Trial.

Background: The impact of singing on cardiovascular health has not been extensively studied. The aim of this study is to investigate the effect of singing on cardiovascular biomarkers in an aging population with coronary artery disease. Methods: Participants had three study visits separated by 2-7 days, according to a randomized, single-blind, cross-over, controlled design: (1) a 30-minute period of coached singing from an in-person music therapist, (2) a 30-minute period of singing along to an instructional video and (3) a 30-minute rest (control). Primary outcomes included macrovascular endothelial function assessed by brachial artery flow-mediated dilation and microvascular function assessed by peripheral arterial tonometry (Framingham reactive hyperemia index; fRHI). Heart rate variability was a secondary outcome. Results: Sixty-five subjects (mean age 67.7± 0.8, 40% women) completed the study. Compared to control, there was an increase in fRHI for the singing video intervention (estimate 0.54, SE 0.25, p=0.005) but not for the coaching intervention (estimate 0.11, SE 0.18, p=0.570). There was no change in macrovascular function with either intervention. The low frequency/high frequency (LF/HF) ratio increased by 2.80 (SE 1.03, p=0.008), and the LnHF power decreased by -0.90 ms2 (SE 0.29, p=0.003) with the video (during to pre-change). When assessing post- to pre- change, the coaching intervention showed a significant change of -0.62 ms2 (SE 0.29, p=0.036) in LnHF power. Conclusions: Singing along to an instructional video for 30 minutes improved microvascular, but not macrovascular, endothelial function, in older patients with CAD. HRV changes with singing are similar to that of exercise. Clinical trial registration: ClinicalTrials.gov, identifier: NCT04121741.