Biochemical markers and combination testing for the diagnosis of ovarian cancer in women with symptoms or signs suspicious of ovarian cancer

Ovarian cancer (OC) has the highest mortality of all gynaecological cancers. A significant contributing factor to the high mortality in OC is delayed diagnosis. Currently, there is no consensus regarding the best test for early diagnosis. A review of existing systematic reviews about symptoms, biochemical markers and US test used alone or in combination for the diagnosis of OC in symptomatic women demonstrated that existing reviews were variable in quality, applicability and limited by poor reporting. I attempted to address these deficiencies in two reviews on the accuracy of biomarkers alone and symptoms, biomarkers or US in combination for the diagnosis of OC in symptomatic women in generalist settings in pre and postmenopausal women separately. My thesis finds key methodological issues, e.g., literature is not applicable to generalist settings as studies included women typical of tertiary healthcare settings, some studies excluded borderline tumours which inflates estimates of sensitivity, important differences exist in test performance between pre and postmenopausal women. Main results are 1) reviews not applicable to primary care settings – more research is needed. 2) for biomarkers i) HE4 at the threshold of 60-80pMol/L and 130-150pMol/L is recommended in pre and postmenopausal women for low prevalence settings ii) ROMA or LR2 in premenopausal women to replace RMI in secondary/tertiary setting; continue with RMI for postmenopausal women as it shows comparable accuracy to ROMA and LR2

A Multi-Pronged Approach to Phishing Email Detection

Phishing emails are a nuisance and a growing threat for the world causing loss of time, effort and money. In this era of online communication and electronic data exchange, every individual connected to the Internet has to face the danger of phishing attacks. Typically, benign-looking emails are used as the attack vectors, which trick users into revealing sensitive information like login credentials, credit-card details, etc. Since every email contains important information in its header, this thesis describes ways of capturing this information for successful classification of phishing emails. Moreover, the phisher has total control over the email body and subject, but little control over the header after the email leaves the sender's domain, unless the phisher is sophisticated and spends a lot of time crafting the attack, which reduces the payoff or may even backfire or yield mixed results. This thesis is a consolidated account of various systems designed to combat phishing emails from different dimensions. The main area of focus is email header. Techniques like n-gram analysis, machine learning and network port scanning are used to extract useful features from the emails. This thesis shows that the classes of features used in these systems are very effective in distinguishing the phishing emails from the legitimate ones. Using different real datasets from varied domains, it highlights the robustness of the methods presented. Some methods, like the header-domain analysis, obtain high detection rates of 99.9% and low false positive rates of 0.1%. These approaches have the advantage and flexibility that they can be easily combined with other existing methods, in addition to being used in standalone mode.Computer Science, Department o

The combination effects of trivalent gold ions and gold nanoparticles with different antibiotics against resistant Pseudomonas aeruginosa

Despite much success in drug design and development, Pseudomonas aeruginosa is still considered as one of the most problematic bacteria due to its ability to develop mutational resistance against a variety of antibiotics. In search for new strategies to enhance antibacterial activity of antibiotics, in this work, the combination effect of gold materials including trivalent gold ions (Au ) and gold nanoparticles (Au NPs) with 14 different antibiotics was investigated against the clinical isolates of P. aeruginosa, Staphylococcus aureus and Escherichia coli. Disk diffusion assay was carried out, and test strains were treated with the sub-inhibitory contents of gold nanomaterial. Results showed that Au NPs did not increase the antibacterial effect of antibiotics at tested concentration (40 μg/disc). However, the susceptibility of resistant P. aeruginosa increased in the presence of Au and methicillin, erythromycin, vancomycin, penicillin G, clindamycin and nalidixic acid, up to 147 %. As an individual experiment, the same group of antibiotics was tested for their activity against clinical isolates of S. aureus, E. coli and a different resistant strain of P. aeruginosa in the presence of sub-inhibitory contents of Au , where Au increased the susceptibility of test strains to methicillin, erythromycin, vancomycin, penicillin G, clindamycin and nalidixic acid. Our finding suggested that using the combination of sub-inhibitory concentrations of Au and methicillin, erythromycin, nalidixic acid or vancomycin may be a promising new strategy for the treatment of highly resistant P. aeruginosa infections

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]