AN INNOVATIVE STATISTICAL METHOD PAVING THE WAY TO PERSONALIZED MEDICINE
The method of Generalized Pairwise Comparisons (GPC) fulfills a recent literature trend that attempts addressing a common concern for the analysis of randomized clinical trial data.
While multiple outcomes of interest are typically measured on patients, traditional statistical investigations only concentrate on a ‘’primary’’ outcome. All other outcomes are then either only considered as of secondary importance, or not considered at all in the analysis.
The core idea of GPC is to allow patients and clinicians to elicit among the outcomes of the trial, an order of importance that is most relevant to them. The outcomes can be of any type (categorical, continuous, or time-to-event), and can include efficacy, toxicity, quality of life, or cost-related information.
In conclusion, GPC bridges statistical soundness with clinical relevance by:
- Incorporating inputs of patients and clinicians into the analysis,
- Providing a methodologically sound statistical tool, appropriate for the interpretation and communication of the analysis results.
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