Subpopulation Treatment Effect Pattern Plot (STEPP) analysis for continuous, binary, and count outcomes.

ABSTRACT:

Background

For the past few decades, randomized clinical trials have provided evidence for effective treatments by comparing several competing therapies. Their successes have led to numerous new therapies to combat many diseases. However, since their conclusions are based on the entire cohort in the trial, the treatment recommendation is for everyone, and may not be the best option for an individual. Medical research is now focusing more on providing personalized care for patients, which requires investigating how patient characteristics, including novel biomarkers, modify the effect of current treatment modalities. This is known as heterogeneity of treatment effects. A better understanding of the interaction between treatment and patient-specific prognostic factors will enable pra

SUBMITTER: Yip WK 

PROVIDER: S-EPMC4942365 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature