Sample Size Determination in Clinical Trials
12-13 March
Location Reading, UK
Presenters Anne Whitehead, Patrick Kelly and Yinghui Zhou
Cost £580
At the planning stage of a clinical trial a key question is "How many patients
do we need?" For a superiority trial the main objective is to provide evidence
of superior efficacy for the new therapy relative to the control. This requires
a sample size that ensures sufficient statistical power to detect a clinically
relevant improvement. Equivalence or non-inferiority trials require sample sizes
that establish with sufficient confidence that the new therapy is respectively
equivalent to or no worse than the control.
This course provides a framework for sample size determination in superiority,
non-inferiority and equivalence trials. It considers a general parametric
approach applicable to binary, ordinal, time to event or normally distributed
patient responses. Comparisons are made with other commonly used approximate and
exact methods. Extension to more than two treatments, including a factorial
design, is considered. Practical aspects such as allowance for drop-outs,
protocol violations and mid-trial sample size reviews are addressed. The course
includes practical sessions involving the use of hand calculators and the
software package nQuery Advisor(r). Use of other packages is discussed.
Programme
A general parametric approach to sample size calculations
Binary, ordinal, time to event and normal data
A unified approach to superiority, equivalence and non-inferiority trials
Parallel group and cross-over designs
Designs with more than two treatments
Practical and ethical considerations
Software
Meta-analysis of Clinical Trials
14-15 March
Location Reading, UK
Presenters Anne Whitehead and Seokyung Hahn
Cost £580
Meta-analysis has an important role to play in evidence-based medicine.
Addressing a specific health care question, meta -analysis involves the use of
statistical methods to combine and summarise the evidence from randomised
controlled trials. This can provide more precise estimates of the treatment's
effect, and a more detailed investigation of subgroups, secondary variables and
safety than is possible from individual trials. In the development of a new drug
or medical intervention there is an advantage in designing the clinical trial
programme to recognise the need for meta-analysis.
This course presents a general framework for meta-analysis, applicable to
binary, ordinal, time to event or normally distributed patient responses. Fixed
and random effects models for combining study summary statistics or individual
patient data will be presented. Methods of dealing with heterogeneity as well
as Bayesian approaches are examined, together with preparation of a
meta-analysis protocol and reporting of results. In addition to lectures, there
will be practical sessions and group discussions based on published examples of
meta-analyses.
Programme
A general framework for meta-analysis
Binary, ordinal, time to event and normal data
Combining study summary statistics or individual patient data using fixed and
random effects models
Protocol development
Presentation and interpretation of results
Dealing with heterogeneity and selection bias
Cumulative meta-analysis
Bayesian methods
Further details from:
Barbara Dodds
MPS Research Unit
The University of Reading
PO Box 240, Earley Gate
Reading RG6 6FN, UK.
Tel: +44 118 931 6662
Fax: +44 118 975 3169
E-mail: [log in to unmask]
http://www.reading.ac.uk/mps
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