published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Applied Statistics / Master / Master of Social Sciences

Objectives: 1) To evaluate the quality of randomized clinical trials (RCTs) in rare diseases using Juvenile Idiopathic Arthritis (JIA) as an example, 2) to evaluate the time to treatment response in patients with rheumatic diseases, 3) to evaluate the power of the Randomized Placebo-Phase Design (RPPD) under various response time distributions, and 4) to examine the use of Value of Information (VOI) methodology in the optimal design of clinical trials for rare disease using hemophilia prophylaxis with factor VIII as an example. Methods. The methods include a systematic review, a secondary analysis of data from an RCT and from a patient registry, a computer simulation study, and an evaluation of hypothetical RCT scenarios with VOI methodology. Results. The quality of RCTs in JIA based on selected quality indicators was poor with some positive changes over time. In the data sets used for the assessment of hazard distributions, the response times followed mostly generalized gamma or lognormal distributions. The impact of time-to-event distribution on the power of RCTs was assessed in computer simulations. Based on the simulation results, the highest sample sizes were observed for response times following the exponential distribution. In most scenarios, the parallel groups RCT design had higher power than the RPPD. The conclusion of the VOI analyses indicated that at threshold values lower than 400,000 the current evidence supported the use of on-demand therapy. Threshold values higher than 1,000,000 supported the use of tailored or alternate day prophylaxis. At threshold values between 400,000 - 1,000,000 the optimal decision varied from on-demand to prophylaxis therapies. Conclusions. New, more powerful and acceptable designs should be developed for rare diseases. When time-to-event outcomes are used, investigators should use various sources of information to evaluate response time distributions before the new trial is designed, and consider this information in sample size calculation and analysis. VOI methodology should be used in the planning stage of studies to determine the relevant costs and benefits of future research, and to determine the optimal trial parameters that maximize the cost-benefit trade-off.

No description available.

Objectives: 1) To evaluate the quality of randomized clinical trials (RCTs) in rare diseases using Juvenile Idiopathic Arthritis (JIA) as an example, 2) to evaluate the time to treatment response in patients with rheumatic diseases, 3) to evaluate the power of the Randomized Placebo-Phase Design (RPPD) under various response time distributions, and 4) to examine the use of Value of Information (VOI) methodology in the optimal design of clinical trials for rare disease using hemophilia prophylaxis with factor VIII as an example. Methods. The methods include a systematic review, a secondary analysis of data from an RCT and from a patient registry, a computer simulation study, and an evaluation of hypothetical RCT scenarios with VOI methodology. Results. The quality of RCTs in JIA based on selected quality indicators was poor with some positive changes over time. In the data sets used for the assessment of hazard distributions, the response times followed mostly generalized gamma or lognormal distributions. The impact of time-to-event distribution on the power of RCTs was assessed in computer simulations. Based on the simulation results, the highest sample sizes were observed for response times following the exponential distribution. In most scenarios, the parallel groups RCT design had higher power than the RPPD. The conclusion of the VOI analyses indicated that at threshold values lower than 400,000 the current evidence supported the use of on-demand therapy. Threshold values higher than 1,000,000 supported the use of tailored or alternate day prophylaxis. At threshold values between 400,000 - 1,000,000 the optimal decision varied from on-demand to prophylaxis therapies. Conclusions. New, more powerful and acceptable designs should be developed for rare diseases. When time-to-event outcomes are used, investigators should use various sources of information to evaluate response time distributions before the new trial is designed, and consider this information in sample size calculation and analysis. VOI methodology should be used in the planning stage of studies to determine the relevant costs and benefits of future research, and to determine the optimal trial parameters that maximize the cost-benefit trade-off.

This thesis discusses the current screening algorithm that is used to detect fetal Down's syndrome. The algorithm combines a model for predicting age related risks and a model for appropriately transformed serum concentrations to produce estimates of risks. A discriminant analysis is used to classify pregnancies as either unaffected or Down's syndrome. The serum concentrations vary with gestational age and the relationship between serum concentrations and gestational age is modelled using regression. These models are discussed and alternative models for these relationships are offered. Concentration values are generally expressed in terms of multiples of the medians for unaffected pregnancies, or MoM values, which involves grouping the concentrations into weekly bins. Transformations of the MoM values are used in the model for predicting risks. The transformed values are equivalent to the residuals of the fitted regression models. This thesis directly models the residuals rather than converting the data to MoM values. This approach avoids the need to group gestational dates into completed weeks. The performance of the algorithm is assessed in terms the detection rates and false positive rates. The performance rates are prone to considerable sampling error. Simulation methods are used to calculate standard errors for reported detection rates. The bias in the rates is also investigated using bootstrapping techniques. The algorithm often fails to recognize abnormalities other than Down's syndrome and frequently associates them with low risks. A solution to the problem is offered that assigns an index of atypicality to each pregnancy, to identify those pregnancies that are atypical of unaffected pregnancies, but are also unlike Down's syndrome pregnancies. Nonparametric techniques for estimating the class conditional densities of transformed serum values are used as an alternative to the conventional parametric techniques of estimation. High quality density estimates are illustrated and these are used to compute nonparametric likelihood ratios that can be used in the probability model to predict risks. The effect of errors in the methods of recording gestational dates on the parameter estimates that are used in the discriminant analysis is also considered.

The World Health Organization estimates that 4 billion people use herbal medicine for some aspect of primary health care. These herbal products are however mostly used without the necessary clinical trial done to prove their pharmacological activities and, therefore, their quality, efficacy and safety. It was the objective of this study to review the current international guidelines for the evaluation of herbal medicine / to gain a perspective on the number, type and quality of clinical trials that have been done on herbal medicine and to adopt a set of guidelines that could be used to conduct trial on a traditional herbal medicine used in South Africa. To verify these guidelines, a protocol for a clinical trial was drafted and submitted for approval to the regulatory and ethical authorities in South Africa.

Thesis (M. P. H.)--University of Hong Kong, 2006. / Also available in print.

Thesis (M. P. H.)--University of Hong Kong, 2006. / Also available in print.