Multi-omics prognostic marker discovery and survival modelling: a case study on multi-cancer survival analysis of women's specific tumours.

ABSTRACT: Survival analysis plays a critical role in predicting patient outcomes and guiding personalized cancer therapies. Although multi-omics data provide rich biological insights, their high dimensionality poses significant challenges for robust analysis and clinical implementation. While many studies rely on the traditional Cox proportional hazards model, few have explored alternative survival algorithms combined with rigorous feature selection to identify low-dimensional, clinically feasible prognostic signatures that retain strong predictive power comparable to models using the full feature set. To address these gaps, we developed PRISM (PRognostic marker Identification and Survival Modelling through Multi-omics Integration), a comprehensive framework aimed at improving survival prediction an

SUBMITTER: Nguyen R 

PROVIDER: S-EPMC12540658 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature