Identification of prognostic and predictive biomarkers in high-dimensional data with PPLasso.

ABSTRACT: In clinical trials, identification of prognostic and predictive biomarkers has became essential to precision medicine. Prognostic biomarkers can be useful for the prevention of the occurrence of the disease, and predictive biomarkers can be used to identify patients with potential benefit from the treatment. Previous researches were mainly focused on clinical characteristics, and the use of genomic data in such an area is hardly studied. A new method is required to simultaneously select prognostic and predictive biomarkers in high dimensional genomic data where biomarkers are highly correlated. We propose a novel approach called PPLasso, that integrates prognostic and predictive effects into one statistical model. PPLasso also takes into account the correlations between biomarkers that can

SUBMITTER: Zhu W 

PROVIDER: S-EPMC9869528 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature