Devices in heart failure: potential methods for device-based monitoring of congestive heart failure.

Congestive heart failure has long been one of the most serious medical conditions in the United States; in fact, in the United States alone, heart failure accounts for 6.5 million days of hospitalization each year. One important goal of heart-failure therapy is to inhibit the progression of congestive heart failure through pharmacologic and device-based therapies. Therefore, there have been efforts to develop device-based therapies aimed at improving cardiac reserve and optimizing pump function to meet metabolic requirements. The course of congestive heart failure is often worsened by other conditions, including new-onset arrhythmias, ischemia and infarction, valvulopathy, decompensation, end-organ damage, and therapeutic refractoriness, that have an impact on outcomes. The onset of such conditions is sometimes heralded by subtle pathophysiologic changes, and the timely identification of these changes may promote the use of preventive measures. Consequently, device-based methods could in the future have an important role in the timely identification of the subtle pathophysiologic changes associated with congestive heart failure.

The Role of Cell Sterilization in Population Based Studies of Radiogenic Second Cancers Following Radiation Therapy

Advances in radiotherapy have generated increased interest in comparative studies of treatment techniques and their effectiveness. In this respect, pediatric patients are of specific interest because of their sensitivity to radiation induced second cancers. However, due to the rarity of childhood cancers and the long latency of second cancers, large sample sizes are unavailable for the epidemiological study of contemporary radiotherapy treatments. Additionally, when specific treatments are considered, such as proton therapy, sample sizes are further reduced due to the rareness of such treatments. We propose a method to improve statistical power in micro clinical trials. Specifically, we use a more biologically relevant quantity, cancer equivalent dose (DCE), to estimate risk instead of mean absorbed dose (DMA). Our objective was to demonstrate that when DCE is used fewer subjects are needed for clinical trials. Thus, we compared the impact of DCE vs. DMA on sample size in a virtual clinical trial that estimated risk for second cancer (SC) in the thyroid following craniospinal irradiation (CSI) of pediatric patients using protons vs. photons. Dose reconstruction, risk models, and statistical analysis were used to evaluate SC risk from therapeutic and stray radiation from CSI for 18 patients. Absorbed dose was calculated in two ways: with (1) traditional DMA and (2) with DCE. DCE and DMA values were used to estimate relative risk of SC incidence (RRCE and RRMA, respectively) after proton vs. photon CSI. Ratios of RR for proton vs. photon CSI (RRRCE and RRRMA) were then used in comparative estimations of sample size to determine the minimal number of patients needed to maintain 80% statistical power when using DCE vs. DMA. For all patients, we found that protons substantially reduced the risk of developing a second thyroid cancer when compared to photon therapy. Mean RRR values were 0.052±0.014 and 0.087±0.021 for RRRMA and RRRCE, respectively. However, we did not find that use of DCE reduced the number of patents needed for acceptable statistical power (i.e, 80%). In fact, when considerations were made for RRR values that met equipoise requirements and the need for descriptive statistics, the minimum number of patients needed for a micro-clinical trial increased from 17 using DMA to 37 using DCE. Subsequent analyses revealed that for our sample, the most influential factor in determining variations in sample size was the experimental standard deviation of estimates for RRR across the patient sample. Additionally, because the relative uncertainty in dose from proton CSI was so much larger (on the order of 2000 times larger) than the other uncertainty terms, it dominated the uncertainty in RRR. Thus, we found that use of corrections for cell sterilization, in the form of DCE, may be an important and underappreciated consideration in the design of clinical trials and radio-epidemiological studies. In addition, the accurate application of cell sterilization to thyroid dose was sensitive to variations in absorbed dose, especially for proton CSI, which may stem from errors in patient positioning, range calculation, and other aspects of treatment planning and delivery.

Evaluation of a solid phase microextraction method for community-based monitoring of 1,3-butadiene and benzene in Houston, Texas

The Houston region is home to arguably the largest petrochemical and refining complex anywhere. The effluent of this complex includes many potentially hazardous compounds. Study of some of these compounds has led to recognition that a number of known and probable carcinogens are at elevated levels in ambient air. Two of these, benzene and 1,3-butadiene, have been found in concentrations which may pose health risk for residents of Houston.^ Recent popular journalism and publications by local research institutions has increased the interest of the public in Houston's air quality. Much of the literature has been critical of local regulatory agencies' oversight of industrial pollution. A number of citizens in the region have begun to volunteer with air quality advocacy groups in the testing of community air. Inexpensive methods exist for monitoring of ozone, particulate matter and airborne toxic ambient concentrations. This study is an evaluation of a technique that has been successfully applied to airborne toxics.^ This technique, solid phase microextraction (SPME), has been used to measure airborne volatile organic hydrocarbons at community-level concentrations. It is has yielded accurate and rapid concentration estimates at a relatively low cost per sample. Examples of its application to measurement of airborne benzene exist in the literature. None have been found for airborne 1,3-butadiene. These compounds were selected for an evaluation of SPME as a community-deployed technique, to replicate previous application to benzene, to expand application to 1,3-butadiene and due to the salience of these compounds in this community. ^ This study demonstrates that SPME is a useful technique for quantification of 1,3-butadiene at concentrations observed in Houston. Laboratory background levels precluded recommendation of the technique for benzene. One type of SPME fiber, 85 μm Carboxen/PDMS, was found to be a sensitive sampling device for 1,3-butadiene under temperature and humidity conditions common in Houston. This study indicates that these variables affect instrument response. This suggests the necessity of calibration within specific conditions of these variables. While deployment of this technique was less expensive than other methods of quantification of 1,3-butadiene, the complexity of calibration may exclude an SPME method from broad deployment by community groups.^

A community-based assessment of the spatiotemporal distribution of influenza in a U.S.-Mexico border county during the spring 2009 novel H1N1 swine-origin influenza A pandemic

This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

Impact of hormonal therapy on survival and racial disparities in a large community-based cohort of older men with local/regional prostate cancer

Prostate cancer (CaP) is the most diagnosed non-cutaneous malignancy and the second leading cause of cancer mortality among United States males. Major racial disparities in incidence, survival, as well as treatment persist. The mortality is three times higher among African Americans (AAs) compared with Caucasians. Androgen carcinogenesis has been persistently implicated but results are inconsistent; and hormone manipulation has been the main stay of treatment for metastatic disease, supportive of the androgen carcinogenesis. The survival disadvantage of AAs has been attributed to the differences in socioeconomic factors (SES), tumor stage, and treatment. We hypostasized that HT prolongs survival in CaP and that the racial disparities in survival is influenced by variation in HT and primary therapies as well as SES. To address these overall hypothesis, we first utilized a random-effect meta-analytic design to examine evidence from randomized trials on the efficacy of androgen deprivation therapy in localized and metastatic disease, and assessed, using Cox proportional hazards models, the effectiveness of HT in prolonging survival in a large community-based cohort of older males diagnosed with local/regional CaP. Further we examined the role of HT and primary therapies on the racial disparities in CaP survival. The results indicated that adjuvant HT compared with standard care alone is efficacious in improving overall survival, whereas HT has no significant benefit in the real world experience in increasing the overall survival of older males in the community treated for local/regional disease. Further, racial differences in survival persist and were explained to some extent by the differences in the primary therapies (radical prostatectomy, radiation and watchful waiting) and largely by SES. Therefore, given the increased used of hormonal therapy and the cost-effectiveness today, more RCTs are needed to assess whether or not survival prolongation translates to improved quality of life, and to answer the research question on whether or not the decreased use of radical prostatectomy by AAs is driven by the Clinicians bias or AAs's preference of conservative therapy and to encourage AAs to seek curative therapies, thus narrowing to some degree the persistent mortality disparities between AAs and Caucasians. ^

Adherence to adjuvant chemotherapy and post-treatment surveillance in a large community-based cohort of patients with colon cancer

The objective of this dissertation was to determine the initiation and completion rates of adjuvant chemotherapy, its toxicity and the compliance rates of post-treatment surveillance for elderly patients with colon cancer using the linked Surveillance, Epidemiology, and End Results – Medicare database.^ The first study assessed the initiation and completion rate of 5-fluorouracil-based adjuvant chemotherapy and its relationship with patient characteristics. Of the 12,265 patients diagnosed with stage III colon adenocarcinoma in 1991-2005, 64.4% received adjuvant chemotherapy within 3-months after tumor resection and 40% of them completed the treatment. Age, marital status, and comorbidity score were significant predictors for chemotherapy initiation and completion.^ The second study estimated the incidence rate of toxicity-related endpoints among stage III colon adenocarcinoma patients treated with chemotherapy in 1991-2005. Of the 12,099 patients, 63.9% underwent chemotherapy and had volume depletion disorder (3-month cumulative incidence rate [CIR]=9.1%), agranulocytosis (CIR=3.4%), diarrhea (CIR=2.4%), nausea and vomiting (CIR=2.3%). Cox regression analysis confirmed such association (HR=2.76; 95% CI=2.42-3.15). The risk of ischemic heart diseases was slightly associated with chemotherapy (HR=1.08), but significantly among patients aged <75 with no comorbidity (HR=1.70). ^ The third study determined the adherence rate of follow-up cares among patients diagnosed with stage I-III colon adenocarcinoma in 2000 - June 2002. We identified 7,348 patients with a median follow-up of 59 months. The adherence rate was 83.9% for office visits, 29.4% for CEA tests, and 74.3% for colonoscopy. Overall, 25.2% met the recommended post-treatment care. Younger age at diagnosis, white race, married, advanced stage, fewer comorbidities, and chemotherapy use were significantly associated with guideline adherence.^ In conclusions, not all colon cancer patients received chemotherapy. Receiving chemotherapy was associated with increased risk of developing gastrointestinal, hematological and cardiac toxicities. Patients were more likely to comply with the schedule for office visits and colonoscopy but failed in CEA tests. ^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^