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Dataset Information

ADME gene-driven prognostic model for bladder cancer: a breakthrough in predicting survival and personalized treatment.


ABSTRACT:

Background

Genes that participate in the absorption, distribution, metabolism, excretion (ADME) processes occupy a central role in pharmacokinetics. Meanwhile, variability in clinical outcomes and responses to treatment is notable in bladder cancer (BLCA).

Methods

Our study utilized expansive datasets from TCGA and the GEO to explore prognostic factors in bladder cancer. Utilizing both univariate Cox regression and the lasso regression techniques, we identified ADME genes critical for patient outcomes. Utilizing genes identified in our study, a model for assessing risk was constructed. The evaluation of this model's predictive precision was conducted using Kaplan-Meier survival curves and assessments based on ROC curves. Furthermore, we devised a predictive nomogram, offerin

SUBMITTER: Dai H 

PROVIDER: S-EPMC11921678 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature