Analysis of routinely collected repeated patient outcomes

Clinical practice should be based on the best available evidence. Ideally such evidence is obtained through rigorously conducted, purpose-designed clinical studies such as randomised controlled trials and prospective cohort studies. However gathering information in this way requires a massive effort, can be prohibitively expensive, is time consuming, and may not always be ethical or practicable. When answers are needed urgently and purpose-designed prospective studies are not feasible, retrospective healthcare data may offer the best evidence there is. But can we rely on analysis with such data to give us meaningful answers? The current thesis studies this question through analysis with repeated psychological symptom screening data that were routinely collected from over 20,000 outpatients who attended selected oncology clinics in Scotland. Linked to patients’ oncology records these data offer a unique opportunity to study the progress of distress symptoms on an unprecedented scale in this population. However, the limitations to such routinely collected observational healthcare data are many. We approach the analysis within a missing data context and develop a Bayesian model in WinBUGS to estimate the posterior predictive distribution for the incomplete longitudinal response and covariate data under both Missing At Random and Missing Not At Random mechanisms and use this model to generate multiply imputed datasets for further frequentist analysis. Additional to the routinely collected screening data we also present a purpose-designed, prospective cohort study of distress symptoms in the same cancer outpatient population. This study collected distress outcome scores from enrolled patients at regular intervals and with very little missing data. Consequently it contained many of the features that were lacking in the routinely collected screening data and provided a useful contrast, offering an insight into how the screening data might have been were it not for the limitations. We evaluate the extent to which it was possible to reproduce the clinical study results with the analysis of the observational screening data. Lastly, using the modelling strategy previously developed we analyse the abundant screening data to estimate the prevalence of depression in a cancer outpatient population and the associations with demographic and clinical characteristics, thereby addressing important clinical research questions that have not been adequately studied elsewhere. The thesis concludes that analysis with observational healthcare data can potentially be advanced considerably with the use of flexible and innovative modelling techniques now made practicable with modern computing power

Analysis of Client Anonymity in the Tor Network

The Tor Network has emerged as the most popular service providing sender anonymity on the Internet. It is a community-driven network with most of the infrastructure operated by volunteers. Peer-to-Peer (P2P) file sharing applications, such as BitTorrent, take up a large portion of the available resources in Tor, which reduce the quality of service for those browsing the web through Tor. In this thesis, experiences from operating a Tor exit relay with a reduced exit policy are recounted. Additionally, the lifecycle of the exit relay is presented and an analysis of the application distribution of exit traffic is done. This analysis uncovers that the reduced exit policy may reduce the BitTorrent traffic share as the total, byte-wise traffic share constituted by BitTorrent was 25.4%, which is lower than in similar analyses done earlier. Tor is a low latency service, thus it is possible that packet latency can leak information about either the source, the destination or both ends of the encrypted Tor traffic. There have been numerous proposals for side-channel attacks in the Tor Network, with one of the most interesting being the website fingerprinting attack. The website fingerprinting attack attempts to map encrypted client-side traffic with a web page by utilizing side-channel information from web page visits to train a machine learning classifier, which in turn is used to predict the web page corresponding to encrypted, client-side Tor traffic. This thesis aims to review existing website fingerprinting attacks as well as to propose a basic attack sorting under this category. The thesis argues that it is feasible that state of the art web site fingerprinting attacks can be applied in a real-world scenario under the assumption that certain Tor users visit censored web pages repeatedly. Website fingerprinting attacks proposed up until now attempt to identify individual web pages from an encrypted traffic stream. This thesis proposes a web site fingerprinting attack, an attack related to the general website fingerprinting attack, but instead of web pages, it attempts to identify web sites. The attack utilizes, among other things, the browsing pattern to attempt to map encrypted client-side traffic to a web site. The browsing pattern data is collected from a test group made up of volunteers who are asked to browse web sites as they feel natural. In one of the most successful experiments, the attack resulted in a True Positive Rate (TPR) of 91.7% and a corresponding False Positive Rate (FPR) of 0.95% from a total of 222 attempted web site predictions

Multi-elemental speciation analysis of barley genotypes diering in tolerance to cadmium toxicity using SEC-ICP-MS and ESI-TOF-MS

Plants respond to Cd exposure by synthesizing heavy-metal-binding oligopeptides, called phytochelatins (PCs). These peptides reduce the activity of Cd2+ ions in the plant tissues by forming Cd chelates. The main objective of the present work was to develop an analytical technique, which allowed identication of the most prominent Cd species in plant tissue by SEC-ICP-MS and ESI-TOF-MS. An integrated part of the method development was to test the hypothesis that dierential Cd tolerance between two barley genotypes was linked to dierences in Cd speciation. Only one fraction of Cd species, ranging from 7001800 Da, was detected in the shoots of both genotypes. In the roots, two additional fractions ranging from 29004600 and 670015 000 Da were found. The Cd-rich SEC fractions were heart-cut, de-salted and demetallized using reversed-phase chromatography (RPC), followed by ESI-MS-TOF to identify the ligands. Three dierent families of PCs, viz. (gGlu-Cys)n-Gly (PCn), (gGlu-Cys)n-Ser (iso-PCn) and Cys-(gGlu-Cys)n-Gly (des-gGlu-PCn), the last lacking the N-terminal amino acid, were identied. The PCs induced by Cd toxicity also bound several essential trace elements in plants, including Zn, Cu, and Ni, whereas no Mn species were detected. Zn, Cu and Ni-species were distributed between the 7001800 Da and 670015 000 Da fractions, whereas only Cd species were found in the 29004600 Da fraction dominated by PC3 ligands. Although the total tissue concentration of Cd was similar for the two species, the tolerant barley genotype synthesized signicantly more CdPC3 species with a high Cd specicity than the intolerant genotype, clearly indicating a correlation between Cd tolerance and the CdPC speciation

Nitro-fatty acids are formed in response to virus infection and are potent inhibitors of STING palmitoylation and signaling

The adaptor molecule stimulator of IFN genes (STING) is central to production of type I IFNs in response to infection with DNA viruses and to presence of host DNA in the cytosol. Excessive release of type I IFNs through STING-dependent mechanisms has emerged as a central driver of several interferonopathies, including systemic lupus erythematosus (SLE), Aicardi-Goutieres syndrome (AGS), and stimulator of IFN genes-associated vasculopathy with onset in infancy (SAVI). The involvement of STING in these diseases points to an unmet need for the development of agents that inhibit STING signaling. Here, we report that endogenously formed nitro-fatty acids can covalently modify STING by nitro-alkylation. These nitro-alkylations inhibit STING palmitoylation, STING signaling, and subsequently, the release of type I IFN in both human and murine cells. Furthermore, treatment with nitro-fatty acids was sufficient to inhibit production of type I IFN in fibroblasts derived from SAVI patients with a gain-of-function mutation in STING. In conclusion, we have identified nitro-fatty acids as endogenously formed inhibitors of STING signaling and propose for these lipids to be considered in the treatment of STING-dependent inflammatory diseases

GPS data som grundlag for en national rejsehastighedsdatabase

I 2008 afsluttede Vejdirektoratet et pilotprojekt omkring brugen af GPS data til trafikplanlægning. I pilotprojektet benyttedes GPS data indsamlet fra igangværende flådestyringssystemer for at undgå omkostningerne til dedikeret udstyr og datakommunikation. &nbsp

Predictors of lost to follow-up in a "test and treat" programme among adult women with high-risk sexual behavior in Kampala, Uganda.

BACKGROUND: Immediate uptake of antiretroviral therapy (ART) after an HIV-positive diagnosis (Test and Treat) is now being implemented in Uganda. Data are limited on lost to follow-up (LTFU) in high-risk cohorts that have initiated 'Test and Treat'. We describe LTFU in a cohort of women of high-risk sexual behaviour who initiated ART under "Test and Treat". METHODS: We performed a retrospective cohort study of participant records at the Good Health for Women Project (GHWP) clinic, a clinic in Kampala for women at high-risk of HIV-infection. We included HIV positive women ≥18 years who initiated ART at GHWP between August 2014 and March 2018. We defined LTFU as not taking an ART refill for ≥3 months from the last clinic appointment among those not registered as dead or transferred to another clinic. We used the Kaplan-Meier technique to estimate time to LTFU after ART initiation. Predictors of LTFU were assessed using a multivariable Cox proportional hazards model. RESULTS: The mean (±SD) age of the 293 study participants was 30.3 (± 6.5) years, with 274 (94%) reporting paid sex while 38 (13%) had never tested for HIV before enrolment into GHWP. LTFU within the first year of ART initiation was 16% and the incidence of LTFU was estimated at 12.7 per 100 person-years (95%CI 9.90-16.3). In multivariable analysis, participants who reported sex work as their main job at ART initiation (Adjusted Hazards Ratio [aHR] =1.95, 95%CI 1.10-3.45), having baseline WHO clinical stage III or IV (aHR = 2.75, 95% CI 1.30-5.79) were more likely to be LTFU. CONCLUSION: LTFU in this cohort is high. Follow up strategies are required to support women on Test and Treat to remain on treatment, especially those who engage in sex work and those who initiate ART at a later stage of disease

Incorporation of excluded volume correlations into Poisson-Boltzmann theory

We investigate the effect of excluded volume interactions on the electrolyte distribution around a charged macroion. First, we introduce a criterion for determining when hard-core effects should be taken into account beyond standard mean field Poisson-Boltzmann (PB) theory. Next, we demonstrate that several commonly proposed local density functional approaches for excluded volume interactions cannot be used for this purpose. Instead, we employ a non-local excess free energy by using a simple constant weight approach. We compare the ion distribution and osmotic pressure predicted by this theory with Monte Carlo simulations. They agree very well for weakly developed correlations and give the correct layering effect for stronger ones. In all investigated cases our simple weighted density theory yields more realistic results than the standard PB approach, whereas all local density theories do not improve on the PB density profiles but on the contrary, deviate even more from the simulation results.Comment: 23 pages, 7 figures, 1 tabl

A practical guide to pre-trial simulations for Bayesian adaptive trials using SAS and BUGS

It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. Before deciding on a particular design, it is generally advisable to carry out a simulation study to characterise the properties of candidate designs under a range of plausible assumptions. The implementation of such pre-trial simulation studies presents many challenges and requires considerable statistical programming effort and time. Despite the scale and complexity, there is little existing literature to guide the implementation of such projects using commonly available software. This Teacher's Corner article provides a practical step-by-step guide to implementing such simulation studies including how to specify and fit a Bayesian model in WinBUGS or OpenBUGS using SAS, and how results from the Bayesian analysis may be pulled back into SAS and used for adaptation of allocation probabilities before simulating subsequent stages of the trial. The interface between the two software platforms is described in detail along with useful tips and tricks. A key strength of our approach is that the entire exercise can be defined and controlled from within a single SAS program