Digoxin use after diagnosis of prostate cancer and survival: a population-based cohort study

PURPOSE:
Preclinical studies have shown that digoxin exerts anticancer effects on different cancer cell lines including prostate cancer. A recent observational study has shown that digoxin use was associated with a 25% reduction in prostate cancer risk. The aim of this study was to investigate whether digoxin use after diagnosis of prostate cancer was associated with decreased prostate cancer-specific mortality.
METHODS:
A cohort of 13 134 patients with prostate cancer newly diagnosed from 1998 to 2009 was identified from English cancer registries and linked to the UK Clinical Practice Research Datalink (to provide digoxin and other prescription records) and to the Office of National Statistics mortality data (to identify 2010 prostate cancer-specific deaths). Using time-dependent Cox regression models, unadjusted and adjusted hazard ratios (HR) and 95% confidence intervals (CIs) were calculated for the association between post-diagnostic exposure to digoxin and prostate cancer-specific mortality.
RESULTS:
Overall, 701 (5%) patients with prostate cancer used digoxin after diagnosis. Digoxin use was associated with an increase in prostate cancer-specific mortality before adjustment (HR = 1.59; 95% CI 1.32-1.91), but after adjustment for confounders, the association was attenuated (adjusted HR = 1.13; 95% CI 0.93-1.37) and there was no evidence of a dose response.
CONCLUSIONS:
In this large population-based prostate cancer cohort, there was no evidence of a reduction in prostate cancer-specific mortality with digoxin use after diagnosis.

Epirubicin, oxaliplatin, and capecitabine with or without panitumumab for patients with previously untreated advanced oesophagogastric cancer (REAL3): a randomised, open-label phase 3 trial.

BACKGROUND: EGFR overexpression occurs in 27-55% of oesophagogastric adenocarcinomas, and correlates with poor prognosis. We aimed to assess addition of the anti-EGFR antibody panitumumab to epirubicin, oxaliplatin, and capecitabine (EOC) in patients with advanced oesophagogastric adenocarcinoma. METHODS: In this randomised, open-label phase 3 trial (REAL3), we enrolled patients with untreated, metastatic, or locally advanced oesophagogastric adenocarcinoma at 63 centres (tertiary referral centres, teaching hospitals, and district general hospitals) in the UK. Eligible patients were randomly allocated (1:1) to receive up to eight 21-day cycles of open-label EOC (epirubicin 50 mg/m(2) and oxaliplatin 130 mg/m(2) on day 1 and capecitabine 1250 mg/m(2) per day on days 1-21) or modified-dose EOC plus panitumumab (mEOC+P; epirubicin 50 mg/m(2) and oxaliplatin 100 mg/m(2) on day 1, capecitabine 1000 mg/m(2) per day on days 1-21, and panitumumab 9 mg/kg on day 1). Randomisation was blocked and stratified for centre region, extent of disease, and performance status. The primary endpoint was overall survival in the intention-to-treat population. We assessed safety in all patients who received at least one dose of study drug. After a preplanned independent data monitoring committee review in October, 2011, trial recruitment was halted and panitumumab withdrawn. Data for patients on treatment were censored at this timepoint. This study is registered with ClinicalTrials.gov, number NCT00824785. FINDINGS: Between June 2, 2008, and Oct 17, 2011, we enrolled 553 eligible patients. Median overall survival in 275 patients allocated EOC was 11.3 months (95% CI 9.6-13.0) compared with 8.8 months (7.7-9.8) in 278 patients allocated mEOC+P (hazard ratio [HR] 1.37, 95% CI 1.07-1.76; p=0.013). mEOC+P was associated with increased incidence of grade 3-4 diarrhoea (48 [17%] of 276 patients allocated mEOC+P vs 29 [11%] of 266 patients allocated EOC), rash (29 [11%] vs two [1%]), mucositis (14 [5%] vs none), and hypomagnesaemia (13 [5%] vs none) but reduced incidence of haematological toxicity (grade ≥ 3 neutropenia 35 [13%] vs 74 [28%]). INTERPRETATION: Addition of panitumumab to EOC chemotherapy does not increase overall survival and cannot be recommended for use in an unselected population with advanced oesophagogastric adenocarcinoma. FUNDING: Amgen, UK National Institute for Health Research Biomedical Research Centre.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

Modeling the distribution of crossovers and interference with mice DNA data

Chiasma and crossover are two related biological processes of great importance in the understanding genetic variation. The study of these processes is straightforward in organisms where all products of meiosis are recovered and can be observed. This is not the case in mammals. Our understanding of these processes depends on our ability to model them. In this study I describe the biological processes that underline chiasma and crossover as well as the two main inference problems associated with these processes: i) in mammals we only recover one of the four products of meiosis and, ii) in general, we do not observe where the crossovers actually happen, but we find an interval containing type-2 censored information. NPML estimate was proposed and used in this work and used to compare chromosome length and chromosome expansion through the crosses.

Assessment of an oral Mycobacterium bovis BCG vaccine and an inactivated M. bovis preparation for wild boar in terms of adverse reactions, vaccine strain survival, and uptake by nontarget species

Wildlife vaccination is increasingly being considered as an option for tuberculosis control. We combined data from laboratory trials and an ongoing field trial to assess the risk of an oral Mycobacterium bovis BCG vaccine and a prototype heat-inactivated Mycobacterium bovis preparation for Eurasian wild boar (Sus scrofa). We studied adverse reactions, BCG survival, BCG excretion, and bait uptake by nontarget species. No adverse reactions were observed after administration of BCG (n = 27) or inactivated M. bovis (n = 21). BCG was not found at necropsy (175 to 300 days postvaccination [n = 27]). No BCG excretion was detected in fecal samples (n = 162) or in urine or nasal, oral, or fecal swab samples at 258 days postvaccination (n = 29). In the field, we found no evidence of loss of BCG viability in baits collected after 36 h (temperature range, 11°C to 41°C). Camera trapping showed that wild boar (39%) and birds (56%) were the most frequent visitors to bait stations (selective feeders). Wild boar activity patterns were nocturnal, while diurnal activities were recorded for all bird species. We found large proportions of chewed capsules (29%) (likely ingestion of the vaccine) and lost baits (39%) (presumably consumed), and the proportion of chewed capsules showed a positive correlation with the presence of wild boar. Both results suggest proper bait consumption (68%). These results indicate that BCG vaccination in wild boar is safe and that, while bait consumption by other species is possible, this can be minimized by using selective cages and strict timing of bait deployment.

Oral cancer incidence and survival rates in the Republic of Ireland, 1994-2009

Background: Oral cancer is a significant public health problem world-wide and exerts high economic, social, psychological, and physical burdens on patients, their families, and on their primary care providers. We set out to describe the changing trends in incidence and survival rates of oral cancer in Ireland between 1994 and 2009. Methods: National data on incident oral cancers [ICD 10 codes C01-C06] were obtained from the National Cancer Registry Ireland from 1994 to 2009. We estimated annual percentage change (APC) in oral cancer incidence during 1994–2009 using joinpoint regression software (version 4.2.0.2). The lifetime risk of oral cancer to age 79 was estimated using Irish incidence and population data from 2007 to 2009. Survival rates were also examined using Kaplan-Meier curves and Cox proportional hazard models to explore the influence of several demographic/lifestyle covariates with follow-up to end 2012. Results: Data were obtained on 2,147 oral cancer incident cases. Men accounted for two-thirds of oral cancer cases (n = 1,430). Annual rates in men decreased significantly during 1994–2001 (APC = -4.8 %, 95 % CI: −8.7 to −0.7) and then increased moderately (APC = 2.3 %, 95 % CI: −0.9 to 5.6). In contrast, annual incidence increased significantly in women throughout the study period (APC = 3.2 %, 95 % CI: 1.9 to 4.6). There was an elevated risk of death among oral cancer patients who were: older than 60 years of age; smokers; unemployed or retired; those living in the most deprived areas; and those whose tumour was sited in the base of the tongue. Being married and diagnosed in more recent years were associated with reduced risk of death. Conclusion: Oral cancer increased significantly in both sexes between 1999 and 2009 in Ireland. Our analyses demonstrate the influence of measured factors such as smoking, time of diagnosis and age on observed trends. Unmeasured factors such as alcohol use, HPV and dietary factors may also be contributing to increased trends. Several of these are modifiable risk factors which are crucial for informing public health policies, and thus more research is needed.

Comparison of 1-year outcome in patients with severe aorta stenosis treated conservatively or by aortic valve replacement or by percutaneous transcatheter aortic valve implantation (data from a multicenter Spanish registry)

The factors that influence decision making in severe aortic stenosis (AS) are unknown. Our aim was to assess, in patients with severe AS, the determinants of management and prognosis in a multicenter registry that enrolled all consecutive adults with severe AS during a 1-month period. One-year follow-up was obtained in all patients and included vital status and aortic valve intervention (aortic valve replacement [AVR] and transcatheter aortic valve implantation [TAVI]). A total of 726 patients were included, mean age was 77.3 ± 10.6 years, and 377 were women (51.8%). The most common management was conservative therapy in 468 (64.5%) followed by AVR in 199 (27.4%) and TAVI in 59 (8.1%). The strongest association with aortic valve intervention was patient management in a tertiary hospital with cardiac surgery (odds ratio 2.7, 95% confidence interval 1.8 to 4.1, p <0.001). The 2 main reasons to choose conservative management were the absence of significant symptoms (136% to 29.1%) and the presence of co-morbidity (128% to 27.4%). During 1-year follow-up, 132 patients died (18.2%). The main causes of death were heart failure (60% to 45.5%) and noncardiac diseases (46% to 34.9%). One-year survival for patients treated conservatively, with TAVI, and with AVR was 76.3%, 94.9%, and 92.5%, respectively, p <0.001. One-year survival of patients treated conservatively in the absence of significant symptoms was 97.1%. In conclusion, most patients with severe AS are treated conservatively. The outcome in asymptomatic patients managed conservatively was acceptable. Management in tertiary hospitals is associated with valve intervention. One-year survival was similar with both interventional strategies.

Using multivariate sequential patterns to improve survival prediction in intensive care burn unit

Resuscitation and stabilization are key issues in Intensive Care Burn Units and early survival predictions help to decide the best clinical action during these phases. Current survival scores of burns focus on clinical variables such as age or the body surface area. However, the evolution of other parameters (e.g. diuresis or fluid balance) during the first days is also valuable knowledge. In this work we suggest a methodology and we propose a Temporal Data Mining algorithm to estimate the survival condition from the patient’s evolution. Experiments conducted on 480 patients show the improvement of survival prediction.

Influence of Baculovirus anticarsia on the growth rate and survival of some nontarget aquatic organisms.

Recently, microbial pest control agents (MPCAs) have been worldwide used to reduce chemical pesticide use and to diminish the high risk of those compounds in the environment. Among various MPCAs, the nuclear polyhedrosis virus Baculovirus anticarsia is widely used in Brazil in the biological control of the velvet bean caterpillar. Although literature data do not show adverse effects of baculoviruses to nontarget organisms, it is necessary to evaluate their toxicity or patogenicity in order to study th environmental risk of those products and to register the formulations in the Brazilian Environmental Regularory Agency - IBAMA. In the presente work, the influence of a Baculovirus anticarsia formulation was evaluted to measure the consequences in the growth rateof the green algae Selenastrum capricornutum, the duckweed Lemna valdiviana and the microcrustacean Daphnia similis. The survival of the fish Hyphessobrycon scholzei exposed during 28 days was also evaluated. No significative adverse effects (P > 0.05) were observed in the test organisms which were exposed to 1-1000 times the maximum calculated pesticide concentration following a direct application to 15 cm layer of water.

Growth and survival of Sclerolobium paniculatum vogel and the relationship between rainfall and the increment in diameter at different planting spacings.

Sclerolobium paniculatum Vogel is a species that has good potential for reclamation of degraded soils. The aim of the investigation was to evaluate the growth and survival of the species and the influence of rainfall on growth in diameter as a function of different spacings (4 m x 2 m, 4 m x 3 m, and 4 m x 4 m). The results indicate that the temporal analysis (period from November 2007 to August 2013) detected significant differences (p ? 0.05) in height between the 4 m x 2 m and 4 m x 4 m spacings, while no significant difference in diameter was found between the 4 m x 2 m and 4 m x 3 m spacings. However, the statistical differences did not persist when the data was analyzed at seven and half years old. Regarding survival, a significant difference was observed only between the 4 m x 4 m spacing and the others, with superiority to the former. A strong correlation was found between rainfall and the increment in diameter of individuals in the broader spacings (R = 0.80 in the 4 m x 3 m spacing and R = 0.77 in the 4 m x 4 m spacing), while in the denser spacing the correlation was moderate (R = 0.56 in the 4 m x 2 m spacing). Since the spacings adopted did not influence tree growth by the end of the period, the choice will depend on other factors such as survival and costs of implementation and forestry management. Plantations in regions with larger rainfall amplitude may benefit the productivity of the species.