In patients with a particular disease or health condition, prognostic factors are characteristics (such as age, biomarkers) that are associated with different risks of a future clinical outcome. Research is needed to identify prognostic factors, but current evidence suggests that primary research is of low quality and poorly/selectively reported, which limits subsequent systematic reviews and meta-analysis. This thesis aims to improve prognostic factor research, through the application, development and evaluation of statistical methods to quantify the effect of potential prognostic factors. Firstly, I conduct a new prognostic factor study in pregnant women. The findings suggest that the albumin/creatinine ratio (ACR) is an independent prognostic factor for neonatal and, in particular, maternal composite adverse outcomes; thus ACR may enhance individualised risk prediction and clinical decision-making. Then, a literature review is performed to flag challenges in conducting meta-analysis of prognostic factor studies in the same clinical area. Many issues are identified, especially between-study heterogeneity and potential bias in the thresholds (cut-off points) used to dichotomise continuous factors, and the set of adjustment factors. Subsequent chapters aim to tackle these issues by proposing novel multivariate meta-analysis methods to ‘borrow strength’ across correlated thresholds and/or adjustment factors. These are applied to a variety of examples, and evaluated through simulation, which show how the approach can reduce bias and improve precision of meta-analysis results, compared to traditional univariate methods. In particular, the percentage reduction in the variance is of a similar magnitude to the percentage of data missing at random.

Hospitals and other health institutions around the world have begun to tie staff promotion and careers to publication; accordingly, an increasing number of medical journal articles are being written by non-native English speakers and novice writers. This work aims to analyse medical journal articles as a genre, and follows Swales’ (1990) framework for doing so, by interviewing a sample of the discourse community and finding the Rhetorical Moves that make up the genre, with additional investigation of stance, via selected reporting verbs, and cohesion, through selected discourse markers. I compiled one of the larger corpora of medical research articles (250), as well as one of the most recent (2001-2011). Previous studies reviewed 50 articles at most, drawn from earlier periods of time. As part of the examination of the genre, this study includes discussions with a sample of the discourse community, the users of the genre, with interviews from ten doctors and five editors from around the world who have a wide range of experience in writing, publishing and editing articles. In addition, I identified 17 Rhetorical Moves, with four considered optional, with the idea to identify a sequence that writers and educators can use to see how the medical article may be written. I also examined 13 reporting verbs to determine if it is possible to identify authorial stance regarding the information being reported, and were coded as being factive (the authors agreed with the information), non-factive (the authors conveyed no judgement on the information) and counter-factive (the authors disagreed with the information being reported). Finally, the study looked at how cohesion is maintained through examples of the five types of discourse markers. This study presents the most comprehensive examination of the genre to date, which, through the utilization of corpus analysis techniques, allows a more in-depth analysis than previous studies.

Background: The universal principles of biomedical ethics provide overall guidance which are applicable to all settings. However, the range of ethical issues present in different communities differs subject to variations in ethno-cultural contexts. Rapid Ethical Assessment (REA) is an approach developed to improve context-tailored application of the informed consent process in low-income settings. The tool employs ethnographic and action research techniques to explore and address context specific ethical issues. However, information is lacking on its feasibility and applicability for wide-scale use. This study aimed to explore the need for REA and establish its usefulness for research in Ethiopia and similar settings. The study also aimed to assess feasibility of REA so as to provide further guidance on strategies for its future application. Methods: Pilot REA studies were conducted in three different research projects, 'parent studies', in Ethiopia between 2012 and 2013. The studies employed a range of study designs with multi-disciplinary approach and were conducted in multi-ethnic and multi-cultural settings in Ethiopia. The study disciplines employed ranged from ethics, social science and anthropology to public health. The study designs employed ranged from qualitative, ethnographic and mixed methods to quantitative interventional studies. Results: Qualitative and quantitative studies of research stakeholders indicated presence of gaps in the research consent process in Ethiopia. The need for the REA approach in understanding and addressing these gaps was highlighted. Based on the pilot studies, REA was found to be useful to identify important context-specific ethical issues and contextualizing consent processes for community-based medical research. The ethical issues ranged from general issues such as the cultural setting of the study, perception about research, health and health care practices to perceptions about the research subject matters, and communication dynamics and norms and their hierarchies. REA was associated with improved levels of information comprehension and quality of the informed consent process. REA also appeared to be a feasible intervention in terms of cost, time and skill. REA skills were easily transferrable to local experts and the approach was flexible and adaptable to circumstances, settings and needs. Conclusion: Given clear strategic guidelines, REA is a highly useful approach to identify important ethical issues in research conducted in the Ethiopian context. It is feasible that the approach could be applied at wider scale in such settings. The approach is recommended for further dissemination coupled with continued documentation and validation.

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Objectives: Missing data represent a source of bias in randomized clinical trials (RCTs). This thesis focuses on pragmatic RCTs with missing continuous outcome data and evaluates the use and appropriateness of current methods of analysis. Methods: This thesis consists of three parts. First, a systematic review examined practices relating to missing data in published RCTs. Second, a simulation study compared the performance of various methods for handling missing data in a number of plausible trial scenarios. Finally, an empirical evaluation of two pragmatic RCTs investigated the use of a reminder process to inform whether missingness is likely to be non-ignorable. Results: The majority of 91 trials in the systematic review adopted a form of single imputation, such as last observation carried forward (LOCF) for dealing with missing data. Mixed-effects model for repeated measures (MMRM) and/or multiple imputation (MI) were limited to eight trials. Sensitivity analyses were infrequently and inappropriately used, and insufficiently reported. In the simulation study, LOCF yielded biased estimates of treatment effect in most scenarios, irrespective of missing data mechanisms. All methods, except LOCF, yielded unbiased estimates for scenarios of equal dropout rate and same direction of dropout in both treatment groups. MMRM and MI were more robust to bias than complete-case and LOCF-based analyses. In the empirical study, the evaluation using reminder responses indicated the possibility of biased MMRM estimation in one trial and unbiased MMRM estimation in the other. Conclusion: CCA and LOCF-based analysis should be disregarded in favour of methods such as MMRM and MI-based analysis. The proposed reminder approach can be used to assess the robustness of the missing at random (MAR) assumption by checking expected consistency in MAR-based estimates. If the results deviate, then analyses incorporating a range of plausible missing not at random assumptions are advisable, at least as sensitivity tests for the evaluation of treatment effect.

This thesis discusses comprehensively the issue of exploitation from a normative perspective specifically relating to clinical trials within developing countries using a normative definition. Exploitation is defined from an unfairness perspective as the unfair use of an individual (group of individual) by another. In order to ease the flow of the arguments within this thesis, unfairness will be assessed from two different perspectives: a procedural perspective and an outcome perspective. The procedural perspective discusses whether the procedures followed when obtaining informed consent from the potential participants fulfilled the requirements of informed consent or failed to do so. Though the use of this approach it is concluded that informed consent is not a necessary condition for the avoidance of exploitation. Similarly, it is concluded that even if morally transformative, valid consent is given by potential participants, exploitation may still be lurking in the shadows of the interaction between the trial participants and the researchers/sponsors. The outcome perspective of unfairness focuses on the effect of the interaction on the parties involved within it and whether they benefit from their interaction with each other, are not affected by it, or are actually harmed as a result of the interaction. As an extension of this argument, the thesis will also consider the post-trial perspective of the interaction. The thesis concludes that post-trial access (reasonable availability) has a very narrow view of benefit and does not ensure that there is a fair share of the benefits between the parties involved. Instead of this narrow approach, a wider, post-trial benefit approach is adopted in order to prevent exploitation. Further discussion within the thesis will include, the requirements of an ethical review, the makeup of the review boards, and priority decision making in keeping with the current research ethics discussion in the literature.

Physiological systems are well recognised to be nonlinear, stochastic and complex. In situations when only one time series of a single variable is available, exacting useful information from the dynamic data is crucial to facilitate personalised clinical decisions and deepen the understanding of the underlying mechanisms. This thesis is focused on establishing and validating data-driven models that incorporate nonlinearity and stochasticity into the model developing framework, to describe a single measurement time series in the field of biomedical engineering. The tasks of model selection and parameter estimation are performed by applying the variational Bayesian method, which has shown great potential as a deterministic alternative to Markov Chain Monte Carlo sampling methods. The free energy, a maximised lower bound of the model evidence, is considered as the main model selection criterion, which penalises the complexity of the model. Several other model selection criteria, alongside the free energy criterion, have been utilised according to the specific requirements of each application. The methodology has been employed to two biomedical applications. For the first application, a nonlinear stochastic second order model has been developed to describe the blood glucose response to food intake for people with and without Diabetes Mellitus (DM). It was found that the glucose dynamics for the people with DM show a higher degree of nonlinearity and a different range of parameter values compared with people without DM. The developed model shows clinical potential of classifying individuals into these two groups, monitoring the effectiveness of the diabetes management, and identifying people with pre-diabetes conditions. For the second application, a linear third order model has been established for the first time to describe post-transplant antibody dynamics after high-risk kidney transplantation. The model was found to have different ranges of parameter values between people with and without acute antibody-mediated rejection (AMR) episodes. The findings may facilitate the formation of an accurate pre-transplant risk profile which predicts AMR and allows the clinician to intervene at a much earlier stage, and therefore improve the outcomes of high-risk kidney transplantation.

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.

MLL2 is a H3K4 specific HMT which vital for normal embryonic development in the mouse. Little is known on how MLL2 is recruited to its target genes and activates transcription. To gain insight into the molecular mechanism underlying MLL2 function, we focused on a known MLL2 target gene: Magoh2. This gene is controlled by a CpG island promoter and is ubiquitously expressed. Our results demonstrate that in the absence of MLL2, the Magoh2 promoter is methylated and Magoh2 is transcriptionally silenced. The Magoh2 promoter adopts the active conformation only in the presence of MLL2. Pol II is lost from the Magoh2 promoter in the absence of MLL2, resulting in Magoh2 down-regulation. We observed loss of H3K4me\(_3\)and H3K9ac and relocation of a nucleosome over the promoter, coinciding with the onset of DNA methylation. Use of ORB and a-amanitin demonstrated that neither transcription nor the presence of Pol II are required for the maintenance of H3K4me\(_3\). Magoh2 silencing can be overcome by re-introducing full-length MLL2. We investigated the role of MLL2 in haemopoiesis and demonstrated that MLL2 is vital for macrophage differentiation from embryoid bodies. MLL2 may be required for correct upregulation of Flk1 and generation of haem angioblast cells. When M//2 was deleted in haemangioblasts, the haemopoietic transcriptional program was perturbed suggesting that MLL2 may also play a role at this later developmental stage.

This research study presents a Hypothesised Model, developed on the basis of the Unified Theory of Acceptance and Use of Technology (UTAUT). Its aim is to evaluate innovative Health Information Technology (HIT) at the early stages of projects. It is contended that this practice would support system developers at the design and implementation phases, and reduce the risk of underutilisation or rejection. The performance of the model was tested in three studies within the Clinical Trial Management Systems framework. The Hypothesised Model approaches Behavioural Intention from a socio-technical point of view, taking into consideration the complexity and need of HIT to achieve joint optimisation. Moreover, it simplifies and extends UTAUT so that it may fit soundly within the healthcare context. Hence, it excludes the moderators and adds three core constructs, including: System-Specific Features, Technology Anxiety, and Adaptation Timeline. However, the model is easily adjustable to fit specific situations, especially given that this research study posits the non-existence of a single model that suits all situations. This approach appears to have improved the final outcome and outperformed the use of generic models within the healthcare context. The total explained variance reported from the three studies is: (76%), (86%), and (87%) respectively.