Investigating variability in patient response to treatment--a case study from a replicate cross-over study
Stephen Senn1, Katie Rolfe, Steven A Julious
1Department of Statistics, University of Glasgow, Glasgow, UK. s.senn@stats.gla.ac.uk
Statistical Methods in Medical Research
|August 27, 2010
Summary
Individual patient response variation is key to clinical trial outcomes. Formal investigation, using replicate cross-over studies, can isolate patient-by-treatment interactions to understand personalized medicine potential.
Area of Science:
- Clinical Trials
- Pharmacology
- Biostatistics
Background:
- Individual variation in treatment response is widely acknowledged but often not formally investigated.
- The potential for personalized medicine and tailor-made drugs is significant but underexplored in drug development.
- Current clinical trial designs may not adequately capture patient-by-treatment interactions.
Purpose of the Study:
- To highlight the lost opportunity in drug development regarding the formal investigation of individual treatment response.
- To demonstrate a method for isolating the patient-by-treatment interaction component of variation.
- To investigate the possibility of individual response to treatment in clinical settings.
Main Methods:
- Utilized a case study from a replicate cross-over study design.
- Employed statistical methods to isolate the component of variation corresponding to patient-by-treatment interaction.
- Focused on suitable replication to enable the investigation of individual response.
Main Results:
- Successfully showed how replicate cross-over studies can isolate patient-by-treatment interaction.
- Provided a framework for formally investigating individual response variation.
- Demonstrated the feasibility of identifying specific patient subgroups with differential treatment responses.
Conclusions:
- Replicate cross-over studies are valuable tools for investigating individual treatment responses.
- Formal investigation of patient-by-treatment interactions is crucial for advancing personalized medicine.
- There is a need to integrate methods for detecting individual response variation into drug development processes.
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