Novel sequential methods in dose-finding designs : extensions of the continual reassessment method

Dose-finding trials are a form of clinical data collection process in which the primary objective is to estimate an optimum dose of an investigational new drug when given to a patient. This thesis develops and explores three novel dose-finding design methodologies. All design methodologies presented in this thesis are pragmatic. They use statistical models, incorporate clinicians' prior knowledge efficiently, and prematurely stop a trial for safety or futility reasons. Designing actual dose-finding trials using these methodologies will minimize practical difficulties, improve efficiency of dose estimation, be flexible to stop early and reduce possible patient discomfort or harm.

Haemodialysis work environment contributors to job satisfaction and stress: A sequential mixed methods study

Background: Haemodialysis nurses form long term relationships with patients in a technologically complex work environment. Previous studies have highlighted that haemodialysis nurses face stressors related to the nature of their work and also their work environments leading to reported high levels of burnout. Using Kanters (1997) Structural Empowerment Theory as a guiding framework, the aim of this study was to explore the factors contributing to satisfaction with the work environment, job satisfaction, job stress and burnout in haemodialysis nurses. Methods: Using a sequential mixed-methods design, the first phase involved an on-line survey comprising demographic and work characteristics, Brisbane Practice Environment Measure (B-PEM), Index of Work Satisfaction(IWS), Nursing Stress Scale (NSS) and the Maslach Burnout Inventory (MBI). The second phase involved conducting eight semi-structured interviews with data thematically analyzed. Results: From the 417 nurses surveyed the majority were female (90.9 %), aged over 41 years of age (74.3 %), and 47.4 % had worked in haemodialysis for more than 10 years. Overall the work environment was perceived positively and there was a moderate level of job satisfaction. However levels of stress and emotional exhaustion (burnout) were high. Two themes, ability to care and feeling successful as a nurse, provided clarity to the level of job satisfaction found in phase 1. While two further themes, patients as quasi-family and intense working teams, explained why working as a haemodialysis nurse was both satisfying and stressful. Conclusions: Nurse managers can use these results to identify issues being experienced by haemodialysis nurses working in the unit they are supervising.

Prospective, non-randomized phase 2 clinical trial of carboplatin plus paclitaxel with sequential radical pelvic radiotherapy for uterine papillary serous carcinoma

Objective Uterine Papillary Serous Carcinoma (UPSC) is uncommon and accounts for less than 5% of all uterine cancers. Therefore the majority of evidence about the benefits of adjuvant treatment comes from retrospective case series. We conducted a prospective multi-centre non-randomized phase 2 clinical trial using four cycles of adjuvant paclitaxel plus carboplatin chemotherapy followed by pelvic radiotherapy, in order to evaluate the tolerability and safety of this approach. Methods This trial enrolled patients with newly diagnosed, previously untreated patients with stage 1b-4 (FIGO-1988) UPSC with a papillary serous component of at least 30%. Paclitaxel (175 mg/m2) and carboplatin (AUC 6) were administered on day 1 of each 3-week cycle for 4 cycles. Chemotherapy was followed by external beam radiotherapy to the whole pelvis (50.4 Gy over 5.5 weeks). Completion and toxicity of treatment (Common Toxicity Criteria, CTC) and quality of life measures were the primary outcome indicators. Results Twenty-nine of 31 patients completed treatment as planned. Dose reduction was needed in 9 patients (29%), treatment delay in 7 (23%), and treatment cessation in 2 patients (6.5%). Hematologic toxicity, grade 3 or 4 occurred in 19% (6/31) of patients. Patients' self-reported quality of life remained stable throughout treatment. Thirteen of the 29 patients with stages 1–3 disease (44.8%) recurred (average follow up 28.1 months, range 8–60 months). Conclusion This multimodal treatment is feasible, safe and tolerated reasonably well and would be suitable for use in multi-institutional prospective randomized clinical trials incorporating novel therapies in patients with UPSC.

Sequential nonlinear manifold learning

The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.

Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products.

Investigation of methods for increasing the energy efficiency on unmanned aerial vehicles (UAVS)

In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.

Using patterns co-occurrence matrix for cleaning closed sequential patterns for text mining

With the overwhelming increase in the amount of texts on the web, it is almost impossible for people to keep abreast of up-to-date information. Text mining is a process by which interesting information is derived from text through the discovery of patterns and trends. Text mining algorithms are used to guarantee the quality of extracted knowledge. However, the extracted patterns using text or data mining algorithms or methods leads to noisy patterns and inconsistency. Thus, different challenges arise, such as the question of how to understand these patterns, whether the model that has been used is suitable, and if all the patterns that have been extracted are relevant. Furthermore, the research raises the question of how to give a correct weight to the extracted knowledge. To address these issues, this paper presents a text post-processing method, which uses a pattern co-occurrence matrix to find the relation between extracted patterns in order to reduce noisy patterns. The main objective of this paper is not only reducing the number of closed sequential patterns, but also improving the performance of pattern mining as well. The experimental results on Reuters Corpus Volume 1 data collection and TREC filtering topics show that the proposed method is promising.

Nurse-administered procedural sedation and analgesia in the cardiac catheterisation laboratory : a mixed methods study

The cardiac catheterisation laboratory (CCL) is a specialised medical radiology facility where both chronic-stable and life-threatening cardiovascular illness is evaluated and treated. Although there are many potential sources of discomfort and distress associated with procedures performed in the CCL, a general anaesthetic is not usually required. For this reason, an anaesthetist is not routinely assigned to the CCL. Instead, to manage pain, discomfort and anxiety during the procedure, nurses administer a combination of sedative and analgesic medications according to direction from the cardiologist performing the procedure. This practice is referred to as nurse-administered procedural sedation and analgesia (PSA). While anecdotal evidence suggested that nurse-administered PSA was commonly used in the CCL, it was clear from the limited information available that current nurse-led PSA administration and monitoring practices varied and that there was contention around some aspects of practice including the type of medications that were suitable to be used and the depth of sedation that could be safely induced without an anaesthetist present. The overall aim of the program of research presented in this thesis was to establish an evidence base for nurse-led sedation practices in the CCL context. A sequential mixed methods design was used over three phases. The objective of the first phase was to appraise the existing evidence for nurse-administered PSA in the CCL. Two studies were conducted. The first study was an integrative review of empirical research studies and clinical practice guidelines focused on nurse-administered PSA in the CCL as well as in other similar procedural settings. This was the first review to systematically appraise the available evidence supporting the use of nurse-administered PSA in the CCL. A major finding was that, overall, nurse-administered PSA in the CCL was generally deemed to be safe. However, it was concluded from the analysis of the studies and the guidelines that were included in the review, that the management of sedation in the CCL was impacted by a variety of contextual factors including local hospital policy, workforce constraints and cardiologists’ preferences for the type of sedation used. The second study in the first phase was conducted to identify a sedation scale that could be used to monitor level of sedation during nurse-administered PSA in the CCL. It involved a structured literature review and psychometric analysis of scale properties. However, only one scale was found that was developed specifically for the CCL, which had not undergone psychometric testing. Several weaknesses were identified in its item structure. Other sedation scales that were identified were developed for the ICU. Although these scales have demonstrated validity and reliability in the ICU, weaknesses in their item structure precluded their use in the CCL. As findings indicated that no existing sedation scale should be applied to practice in the CCL, recommendations for the development and psychometric testing of a new sedation scale were developed. The objective of the second phase of the program of research was to explore current practice. Three studies were conducted in this phase using both quantitative and qualitative research methods. The first was a qualitative explorative study of nurses’ perceptions of the issues and challenges associated with nurse-administered PSA in the CCL. Major themes emerged from analysis of the qualitative data regarding the lack of access to anaesthetists, the limitations of sedative medications, the barriers to effective patient monitoring and the impact that the increasing complexity of procedures has on patients' sedation requirements. The second study in Phase Two was a cross-sectional survey of nurse-administered PSA practice in Australian and New Zealand CCLs. This was the first study to quantify the frequency that nurse-administered PSA was used in the CCL setting and to characterise associated nursing practices. It was found that nearly all CCLs utilise nurse-administered PSA (94%). Of note, by characterising nurse-administered PSA in Australian and New Zealand CCLs, several strategies to improve practice, such as setting up protocols for patient monitoring and establishing comprehensive PSA education for CCL nurses, were identified. The third study in Phase Two was a matched case-control study of risk factors for impaired respiratory function during nurse-administered PSA in the CCL setting. Patients with acute illness were found to be nearly twice as likely to experience impaired respiratory function during nurse-administered PSA (OR=1.78; 95%CI=1.19-2.67; p=0.005). These significant findings can now be used to inform prospective studies investigating the effectiveness of interventions for impaired respiratory function during nurse-administered PSA in the CCL. The objective of the third and final phase of the program of research was to develop recommendations for practice. To achieve this objective, a synthesis of findings from the previous phases of the program of research informed a modified Delphi study, which was conducted to develop a set of clinical practice guidelines for nurse-administered PSA in the CCL. The clinical practice guidelines that were developed set current best practice standards for pre-procedural patient assessment and risk screening practices as well as the intra and post-procedural patient monitoring practices that nurses who administer PSA in the CCL should undertake in order to deliver safe, evidence-based and consistent care to the many patients who undergo procedures in this setting. In summary, the mixed methods approach that was used clearly enabled the research objectives to be comprehensively addressed in an informed sequential manner, and, as a consequence, this thesis has generated a substantial amount of new knowledge to inform and support nurse-led sedation practice in the CCL context. However, a limitation of the research to note is that the comprehensive appraisal of the evidence conducted, combined with the guideline development process, highlighted that there were numerous deficiencies in the evidence base. As such, rather than being based on high-level evidence, many of the recommendations for practice were produced by consensus. For this reason, further research is required in order to ascertain which specific practices result in the most optimal patient and health service outcomes. Therefore, along with necessary guideline implementation and evaluation projects, post-doctoral research is planned to follow up on the research gaps identified, which are planned to form part of a continuing program of research in this field.

Feeding attitudes, practices and traditional dietary beliefs of Chinese mothers with young children in Australia : a mixed methods study

Background and Objectives Obesity and some dietary related diseases are emerging health problems among Chinese immigrants and their children in developed countries. These health problems are closely linked to eating habits, which are established in the early years of life. Young children’s eating habits are likely to persist into later childhood and youth. Family environment and parental feeding practices have a strong effect on young children’s eating habits. Little information is available on the early feeding practices of Chinese mothers in Australia. The aim of this study was to understand the dietary beliefs, feeding attitudes and practices of Chinese mothers with young children who were recent immigrants to Australia. Methods Using a sequential explanatory design, this mixed methods study consisted of two distinct phases. Phase 1 (quantitative): 254 Chinese immigrant mothers of children aged 12 to 59 months completed a cross-sectional survey. The psychometric properties and factor structure of a Chinese version of the Child Feeding Questionnaire (CFQ, by Birch et al. 2001) were assessed and used to measure specific maternal feeding attitudes and controlling feeding practices. Other questions were developed from the literature and used to explore maternal traditional dietary beliefs and feeding practices related to their beliefs, perceptions of picky eating in children and a range of socioeconomic and acculturation factors. Phase 2 (qualitative): 21 mothers took part in a follow-up telephone interview to assist in explaining and interpreting some significant findings obtained in the first phase. Results Chinese mothers held strong traditional dietary beliefs and fed their children according to these beliefs. However, children’s consumption of non-core foods was high. Both traditional Chinese and Australian style foods were consumed by their children. Confirmatory factor analysis revealed that the original 7-factor model of the CFQ provided an acceptable fit to the data with minor modification. However, an alternative model with eight constructs in which two items related to using food rewards were separated from the original restriction construct, not only provided an acceptable fit to the data, but also improved the conceptual clarity of the constructs. The latter model included 24 items loading onto the following eight constructs: restriction, pressure to eat, monitoring, use of food rewards, perceived responsibility, perception of own weight, perception of child’s weight, and concern about child becoming overweight. The internal consistency of the constructs was acceptable or desirable (Cronbach’s α = .60 - .93). Mothers reported low levels of concern about their child overeating or becoming overweight, but high levels of controlling feeding practices: restriction, monitoring, pressure to eat and use of food rewards. More than one quarter of mothers misinterpreted their child’s weight status (based on mothers’ self-reported data). In addition, mothers’ controlling feeding practices independently predicted half of the variance and explained 16% of the variance in child weight status: pressuring the child to eat was negatively associated with child weight status (β = -0.30, p < .01) and using food rewards was positively associated with child weight status (β = 0.20, p < .05) after adjusting for maternal and child covariates. Monitoring and restriction were not associated with child weight status. Mothers’ perceptions of their child’s weight were positively associated with child weight status (β = 0.33, p < .01). Moreover, mothers reported that they mostly decided what (65%) and how much (80%) food their child ate. Mothers who decided what food their child ate were more likely to monitor (β = -0.17, p < .05) and restrict (β = -0.17, p < .05) their child’s food consumption. Mothers who let their child decide how much food their child ate were less likely to pressure their child to eat (β = -0.38, p < .01) and use food rewards (β = -0.24, p < .01). Mothers’ perceptions of picky eating behaviour were positively associated with their use of pressure (β = 0.21, p < .01) and negatively associated with monitoring (β = -0.16, p < .05) and perceptions of their child’s weight status (β = -0.13, p < .05). Qualitative data showed that pressuring to eat, monitoring and restriction of the child’s food consumption were common practices among these mothers. However, mothers stated that their motivation for monitoring and restricting was to ensure the child’s general health. Mothers’ understandings of picky eating behaviour in their children were consistent with the literature and they reported multiple feeding strategies to deal with it. Conclusion Chinese immigrant mothers demonstrated strong traditional dietary beliefs, a low level of concern for child weight, misperceptions of child weight status, and a high overall level of control in child feeding in this study. The Chinese version of the CFQ, which consists of eight constructs and distinguishes between the constructs using food rewards and restriction, is an appropriate instrument to assess feeding attitudes and controlling feeding practices among Chinese immigrant mothers of young children in Australia. Mothers’ feeding attitudes and practices were associated with children’s weight status and mothers’ perceptions of picky eating behaviour in children after adjusting for a range of socio-demographic maternal and child characteristics. Monitoring and restriction of children’s food consumption according to food selection may be positive feeding practices, whereas pressuring to eat and using food rewards appeared to be negative feeding practices in this study. In addition, the results suggest that these young children have high exposure to energy-dense, nutrient-poor food. There is a need to develop and implement nutrition interventions to improve maternal feeding practices and the dietary quality among children of Chinese immigrant mothers in Australia.

Macromolecular engineering via RAFT chemistry : from sequential to modular design

Sequential Design Molecular Weight Range Functional Monomers: Possibilities, Limits, and Challenges Block Copolymers: Combinations, Block Lengths, and Purities Modular Design End-Group Chemistry Ligation Protocols Conclusions

Sequential monitoring of hospital adverse events when control charts fail : the example of fall injuries in hospitals

Objective To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation. Design Retrospective audit. Setting The Northern Hospital, Melbourne, Australia. Participants 171,059 patients admitted between January 2001 and December 2006. Measurements The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit. Results The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation. Conclusion Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Organisational culture, leadership behaviour and job satisfaction among primary health care professionals in Saudi Arabia : a mixed-methods study

The purpose of this study was to improve individual and organisational performance in primary health care (PHC) by identifying the relationship between organisational culture, leadership behaviour and job satisfaction. The study used a sequential explanatory mixed methods design, to investigate the relationships between organisational culture, leadership behaviour, and job satisfaction among 550 PHCC professionals in Saudi Arabia. From surveying the PHC professionals, the results highlighted the importance of human caring qualities, including praise and recognition, consideration, and support, with respect to their perceptions of job satisfaction, leadership behaviour, and organisational culture. As a consequence a management framework was proposed to address these issues.

Second-order quantile methods for experts and combinatorial games

We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.