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Optimal and/or efficient three treatment crossover designs for five carryover models.
Jigneshkumar Gondaliya1, Jyoti Divecha2
1Gujarat Commerce College, Gujarat University, Ellisbridge, Ahmedabad, India.
Journal of Biopharmaceutical Statistics
|November 14, 2019
Summary
New crossover designs with two active treatments and a placebo offer improved estimation of treatment effects. These designs are more efficient than traditional methods, especially under complex carryover models, providing valuable options for clinical trials.
Area of Science:
- Clinical Trial Design
- Biostatistics
- Experimental Design
Background:
- Crossover designs are valuable in clinical trials for comparing treatments.
- Traditional two-treatment, two-period crossover designs have limitations in estimating treatment contrasts under carryover effects.
- Designs including a placebo alongside active treatments offer additional analytical benefits.
Purpose of the Study:
- To investigate and identify optimal and/or efficient crossover designs with two active treatments and a placebo.
- To address the limitations of classic crossover designs in estimating treatment contrasts under self and mixed carryover models.
- To provide a comprehensive list of new crossover designs suitable for various periods and subject numbers.
Main Methods:
- Utilized a computer search algorithm, the 5M balanced algorithm, to identify optimal crossover designs.
- Evaluated designs across two, three, and four periods for varying numbers of subjects.
- Focused on designs incorporating two active treatments and a placebo to assess treatment contrasts and carryover effects.
Main Results:
- Developed new two-period crossover designs that enable the estimation of treatment contrasts, unlike classic designs under self and mixed carryover models.
- Demonstrated that three- and four-period crossover designs with two active treatments and a placebo are more efficient in estimating treatment contrasts under self and mixed carryover models.
- Provided an exhaustive list of optimal/efficient designs for two (6-21 subjects), three (3-20 subjects), and four (3-14 subjects) periods.
- Identified 35 new designs optimal for at least one carryover model and 26 new designs optimal/efficient for all four plausible carryover models.
Conclusions:
- New crossover designs incorporating a placebo alongside two active treatments offer significant advantages in estimating treatment contrasts, particularly under complex carryover models.
- The identified optimal and efficient designs provide enhanced statistical power and reliability for clinical trial analysis.
- These findings contribute valuable, empirically-derived design options for researchers seeking robust comparative treatment evaluations.
Keywords:
Self and mixed carryover effectactive treatmentoptimal designplacebo treatmentwashout periodMore Related Videos
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