Week 1 Flashcards
Phase I:
- First stage in testing a new intervention in humans
- Usually 10-30 people
- Identify tolerable dose, provide information on drug metabolism, excretion, and toxicity
- Often not controlled
Phase II:
- Usually 30-100 people
- Preliminary information on efficacy, additional information on safety and side effects
Phase III:
- Usually 100+ people
- Assess efficacy and safety
- Controlled, usually randomized
Parallel Design
- Simultaneous treatment and control groups
- Each person is randomly assigned to one treatment group
- Randomization removes treatment selection bias and promotes comparability of treatment groups
- Statistical comparisons made between treatment groups
Crossover Design
- Randomization of order in which treatments are received
- Testing of both treatments in each patient
- Fewer patients needed
Randomization of order in which treatments are received
- AB or BA
* Randomization promotes balance between treatment groups in the timing of exposure
Testing of both treatments in each patient
- Each patient serves as his/her own control
* Variability reduced because less variability within patient than between patients
Crossover Design: Disadvantages
- Treatment can’t have permanent effects or cures
- Potential carry-over effects of first-period treatment to the second period
- Test for a period by treatment interactions not powerful
- Dropouts more significant
- Analysis may be more difficult
Potential carry-over effects of first-period treatment to the second period
- Washout needs to be long enough
- Unequal carry-over effects
- Treatment during washout
Crossover Design: Uses
Constant intensity of underlying disease
Short-term treatment effects
Metabolic, bioavailability, or tolerability studies
Constant intensity of underlying disease
Chronic diseases—asthma, hypertension, arthritis
Group Allocation Design
- Also known as “cluster randomization”
- Randomization unit is a group of individuals (community, school, clinic)
- Individual randomization and intervention is not feasible or is unacceptable
- If there is a correlation in the responses within a group, design loses some efficiency (more individuals required)
Individual randomization and intervention is not feasible or is unacceptable
- Tracking
- Contamination
Individual randomization and intervention is not feasible or is unacceptable
- Tracking
- Contamination
Factorial Design
- Two interventions tested simultaneously, either as . . .
1. Economical way to test two treatments simultaneously, or
2. Method to test for treatment interaction - For testing two treatments simultaneously, assumption is of no interaction
For testing two treatments simultaneously, assumption is of no interaction
- Treatments have independent mode of action
- More plausible if different outcome
Large, Simple Design (Features)
Features
- Very large number of patients (many study sites)
- Broad eligibility criteria
- Minimal data collection requirements
Large, Simple Design (Rational)
- Modest benefits require large sample sizes
- Treatment interactions unlikely, so baseline characteristics and interim response variables are not needed
- Less precision (more error, increased variance) is tolerated; countered with large numbers
Large, Simple Design: Requirements
- Easily administered intervention
- Easily ascertained outcome
- Short-term follow-up
- No complex baseline measurements
- Simple data are persuasive enough
Easily administered intervention
- Short-term adherence
- No treatment adjustment
- No ongoing monitoring for adverse events
Equivalence Design
Objective—show that intervention response falls sufficiently close to control group response
Non-Inferiority Design (Objectives)
- Determine whether treatment A (frequently a new treatment) is at least as good as treatment B (frequently an established treatment)
- Test, if hypothesis A is worse than B, than one can be rejected (one-sided)
Adaptive Design: Definition
- an adaptive design clinical study is defined as a study that
- includes a prospectively planned opportunity for modification of one or more specified aspects of the study design
*and hypotheses based on analysis of data (usually interim data) from subjects in the study.
*Analyses of the accumulating study data are performed at prospectively planned timepoints within the study, - can be performed in a fully blinded manner or in an
unblinded manner, - and can occur with or without formal statistical hypothesis testing.
Possible Adaptations in Adaptive Designs
- Randomization probabilities
- Sample size
- Visit schedule
- Hypotheses tested
Principles of Adaption
- Adaptation must be pre-specified
* IRB approval includes adaptation plan
Adaptation must be pre-specified
- Define adaptation triggers in protocol
- Define adaption
adaptation triggers in protocol
- After n-enrolled, re-evaluate sample size/power
calculations based on interim results - Enroll from two subpopulations until time t and then look at response rate in both populations
Define adaption
- Increase or decrease sample size to maintain power
- If response is p% larger in one population, continue
recruitment only in that population
adaptation plan
- Amendments not needed to change according to plan
- Amendment may be needed for other changes
Advantages of Adaptive plan
- Flexibility
- May be more efficient (shorter duration, fewer people)
- May be more likely to show effect if one exists
Limitations of Adaptive Plan
- Can be difficult to explain design and interpret results
- Rely on interim results to change trials
- May provide interim information on efficacy and safety to investigators and sponsor
- May be hard to implement
Why the Adaptive plan can be hard to implement
Need quick access to data
Extensive documentation
