Rapamycin-coated expanded polytetrafluoroethylene bypass grafts exhibit decreased anastomotic neointimal hyperplasia in a porcine model

ObjectiveWe tested the hypothesis that rapamycin coated onto, and eluted from, expanded polytetrafluoroethylene (ePTFE) grafts would diminish neointimal hyperplasia in a porcine model.MethodsRapamycin (also called sirolimus) was coated onto the luminal surface of 6-mm-internal-diameter thin-walled ePTFE grafts by using an adhesive polymer that allows timed release of the drug. An adhesive polymer that allows timed release of rapamycin from ePTFE was developed with commercially available chemicals and applied on 6-mm ePTFE grafts. Graft integrity was characterized by scanning electron microscopy, and rapamycin levels were quantified by using high-performance liquid chromatography. Twenty-two mongrel pigs were randomized into three groups: untreated ePTFE (n = 6), adhesive-only coated ePTFE (n = 6), or adhesive- and rapamycin-coated ePTFE (n = 10). End-to-side unilateral aortoiliac bypasses were performed by using 6-mm-internal-diameter ePTFE grafts and standardized anastomotic lengths. Unilateral end-to-side aortoiliac ePTFE grafts (6-mm internal diameter) were inserted by using polypropylene sutures, 6-0 proximally and 7-0 distally; all anastomoses were 12 mm long. All animals received aspirin (325 mg orally) daily. All animals were given oral aspirin (325 mg) daily beginning on the day before surgery. At 28 days, the animals were killed, and the grafts were explanted in continuity with the adjacent aortic cuff and the outflow iliac artery. Variables compared between groups included graft patency, distal anastomotic length and cross-sectional narrowing, and intimal thickness at the arterial-graft junction indexed to the adjacent graft thickness. Microscopic analysis was performed with hematoxylin and eosin and Masson trichrome stains on paraffin sections. A pathologist blinded to experimental groups graded sections for collagen deposition, neointima formation, inflammatory cellular infiltrates, medial necrosis, and aneurysmal degeneration.ResultsAll animals survived until they were killed without clinical evidence of limb ischemia or graft infection. Preplanned t tests in the context of one-way analysis of variance showed no difference in outcome measures between the untreated ePTFE and adhesive-only coated ePTFE groups; therefore, they were combined in further comparisons with the adhesive- and rapamycin-coated ePTFE group. The Rapamycine eluting expanded polytetrafluoroethylene group had longer anastomoses (85.6% vs 60.6% of the initial anastomotic length maintained; P < .0001) and less cross-sectional narrowing in the outflow graft (16.2% vs 28.5%; P = .0007) when compared with the other two groups by using two-tailed Student t tests. There was no evidence of medial necrosis or aneurysmal degeneration. All patent grafts had complete endothelialization on hematoxylin and eosin sections. Rapamycin was detectable and quantifiable in the arterial wall at 28 days after implantation.ConclusionsRapamycin can be coated onto and eluted from ePTFE by using a nonionic polymer and a simple coating technique. At 4 weeks after implantation, the rapamycin-eluting ePTFE grafts demonstrate gross, pathologic, and morphometric features of diminished neointimal hyperplasia when compared with non–drug-eluting ePTFE. Four weeks after implantation in a porcine model, rapamycin-eluting ePTFE grafts demonstrated gross, pathologic, and morphometric features of diminished neointimal hyperplasia when compared with untreated and adhesive-only coated ePTFE grafts.Clinical RelevanceRapamycin-eluting ePTFE grafts decrease neointimal hyperplasia in a porcine model. Further studies are needed to evaluate whether patency will be improved. Rapamycin-eluting ePTFE grafts may allow the use of prosthetic grafts in situations in which autologous vein is unavailable and in which neointimal hyperplasia is pronounced, such as in small-diameter (<6-mm) vessels typical of infrapopliteal interventions

A Telephone-Adapted Mindfulness-Based Stress Reduction Program: Preliminary Effects among Healthcare Employees

Healthcare employees often experience high stress and may benefit from accessible psychosocial interventions. In this pilot study, we explored preliminary feasibility, acceptability, and psychological effects of a telephone-based adaption of mindfulness-based stress reduction (MBSR) for healthcare employees. Eleven participants (M age = 49.9; 27.3% ethnic/racial minority) were enrolled in an eight-session group-based MBSR program adapted for telephone delivery. Feasibility was assessed using rates of program attrition and session completion; acceptability was explored qualitatively via participants\u27 responses to an open-ended item about their program experience. Participants also completed pre-and post-program assessments on psychosocial outcomes (distress (overall distress, depression, anxiety, somatization), mindfulness, and self-compassion). We characterized mean change scores, 95% confidence intervals, and effect sizes to explore preliminary program effects. With regard to preliminary feasibility, one participant dropped out prior to the intervention; of the remaining 10 participants, 90% completed at least half (≥4) of the sessions; 70% completed at least three-quarters (≥6 sessions). Feedback reflected positive experiences and included suggestions for program delivery. Participants reported reductions in distress post-program (M difference range = -5.0 to -9.4), showing medium to large effect sizes (d range = 0.68 to 1.11). Mindfulness scores increased from pre- to post-intervention (M difference range = 1.0 to 10.4), with small-to-medium effects (d range = 0.18 to 0.55). Almost all aspects of self-compassion remained stable over time, with the exception of common humanity, which increased post-program (M difference = 2.9, CI 95% 0.5 to 5.4, d = 0.91). Preliminary findings from our small pilot trial suggest that telephone-based adaptations of MBSR may be a useful mode of delivery for healthcare employees; however, larger studies are needed to provide further evidence of feasibility, acceptability, and program effects

The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer

INTRODUCTION: Neighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment. MATERIALS AND METHODS: The study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-values RESULTS: In combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with \u3e3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%). DISCUSSION: Utilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed

Genetic Risk Factors for Hepatopulmonary Syndrome in Patients With Advanced Liver Disease

Hepatopulmonary syndrome (HPS) affects 10%–30% of patients with cirrhosis and portal hypertension and significantly increases mortality. Studies in experimental models indicate that pulmonary angiogenesis contributes to the development of HPS, but pathogenesis in humans is poorly understood. We investigated genetic risk factors for HPS in patients with advanced liver disease

Statistical methods for cost-effectiveness analysis using observational data

Observational studies are a useful resource for evaluating the cost and cost-effectiveness of medical treatments, but the results are subject to bias from measured and unmeasured confounding. Investigators must adjust for measured confounders using an appropriate model, and it is also advisable to assess the sensitivity of the results to potential unmeasured confounders. In this dissertation, we develop a sensitivity analysis procedure for the treatment effect on cost. We show that, in some cases, closed-form relationships exist between the observed treatment effect and the treatment effect after adjustment for hypothetical confounders. We derive a general adjustment formula for log-linear cost models. We evaluate our method using simulations, and demonstrate the sensitivity analysis procedure by comparing two bladder cancer treatments using a cohort derived from SEER-Medicare. Next we discuss the challenges of correctly modeling cost-effectiveness, including skewed outcomes, censoring, and correlations between costs and effects. We describe several methods for estimating the Net Monetary Benefit (NMB): linear regression, generalized linear models, parametric and semi-parametric survival methods, and non-parametric estimates with propensity score stratification. Using simulations, we compare the performance of the models for analysis of skewed and censored cost and survival data. We find that correctly specified non-linear parametric models provide the best estimates. Linear regression is insufficient for censored data, and semi-parametric and non-parametric approaches have improved bias and coverage over incorrectly specified parametric models. We illustrate the sensitivity of estimated NMB to model choice with a comparison of two prostate cancer treatments. Finally, we propose a sensitivity analysis procedure for the NMB using a Gamma GLM for cost and a Weibull model for survival. We derive closed-form relationships between the expected values of cost and survival obtained from observed data, and the expected values which account for an unmeasured confounder. Our general formulas allow for any unmeasured confounder which can be characterized using a moment-generating function, and also allow for separate unmeasured confounders to influence cost and survival. We evaluate our formulas using simulations, and return to the bladder cancer example to demonstrate a sensitivity analysis for NMB

Statistical methods for cost-effectiveness analysis using observational data

Observational studies are a useful resource for evaluating the cost and cost-effectiveness of medical treatments, but the results are subject to bias from measured and unmeasured confounding. Investigators must adjust for measured confounders using an appropriate model, and it is also advisable to assess the sensitivity of the results to potential unmeasured confounders. In this dissertation, we develop a sensitivity analysis procedure for the treatment effect on cost. We show that, in some cases, closed-form relationships exist between the observed treatment effect and the treatment effect after adjustment for hypothetical confounders. We derive a general adjustment formula for log-linear cost models. We evaluate our method using simulations, and demonstrate the sensitivity analysis procedure by comparing two bladder cancer treatments using a cohort derived from SEER-Medicare. Next we discuss the challenges of correctly modeling cost-effectiveness, including skewed outcomes, censoring, and correlations between costs and effects. We describe several methods for estimating the Net Monetary Benefit (NMB): linear regression, generalized linear models, parametric and semi-parametric survival methods, and non-parametric estimates with propensity score stratification. Using simulations, we compare the performance of the models for analysis of skewed and censored cost and survival data. We find that correctly specified non-linear parametric models provide the best estimates. Linear regression is insufficient for censored data, and semi-parametric and non-parametric approaches have improved bias and coverage over incorrectly specified parametric models. We illustrate the sensitivity of estimated NMB to model choice with a comparison of two prostate cancer treatments. Finally, we propose a sensitivity analysis procedure for the NMB using a Gamma GLM for cost and a Weibull model for survival. We derive closed-form relationships between the expected values of cost and survival obtained from observed data, and the expected values which account for an unmeasured confounder. Our general formulas allow for any unmeasured confounder which can be characterized using a moment-generating function, and also allow for separate unmeasured confounders to influence cost and survival. We evaluate our formulas using simulations, and return to the bladder cancer example to demonstrate a sensitivity analysis for NMB