E9: STATISTICAL PRINCIPLES FOR CLINICAL TRIALS Flashcards
Confirmatory Trial
Objectives:
* Demonstrate/confirm efficacy
* Establish safety profile in larger, more representative patient populations
* Provide an adequate basis for assessing the benefit/risk relationship to support licensing
Study Examples:
* Randomized controlled clinical trials to establish efficacy in larger, more representative patient populations
* Dose-response studies
* Clinical safety studies
* Studies of mortality/morbidity outcomes
* Studies in special populations
Exploratory
Objectives:
* Explore use for the intended indication
* Estimate dose/dosing regimen for subsequent studies
* Explore dose-response/exposure-response relationship
* Provide basis for confirmatory study design (e.g., targeted population, clinical endpoints, patient reported outcome measures, factors affecting treatment effects)
Study Examples:
* Randomised controlled clinical trials of relatively short duration in well-defined narrow patient populations, using surrogate or pharmacological endpoints or clinical measures
* Dose finding studies
* Biomarker exploration studies
* Studies to validate patient reported outcomes
* Adaptive designs that may combine exploratory and confirmatory objectives
Human Pharmacology
Objectives:
* Assess tolerance and safety
* Define/describe clinical PK1 and PD2
* Explore drug metabolism and drug interactions
* Evaluate activity, assess immunogenicity
* Assess renal/hepatic tolerance
* Assess cardiac toxicity.
Study Examples:
* BA3/BE4 studies under fasted/fed conditions
* Dose-tolerance studies
* Single and multiple-rising dose PK and/or PD studies
* Drug-drug interaction studies
* QTc prolongation study
* Human factor studies for drug delivery devices
Bayesian Approaches
Approaches to data analysis that provide a posterior probability distribution for some parameter (e.g. treatment effect), derived from the observed data and a prior probability distribution for the parameter. The posterior distribution is then used as the basis for statistical inference.
Bias (Statistical & Operational)
The systematic tendency of any factors associated with the design, conduct, analysis
and evaluation of the results of a clinical trial to make the estimate of a treatment
effect deviate from its true value. Bias introduced through deviations in conduct is
referred to as ‘operational’ bias. The other sources of bias listed above are referred to
as ‘statistical’.
Blind Review
The checking and assessment of data during the period of time between trial
completion (the last observation on the last subject) and the breaking of the blind, for
the purpose of finalising the planned analysis.
Content Validity
The extent to which a variable (e.g. a rating scale) measures what it is supposed to
measure.
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