LOCC: a novel visualization and scoring of cutoffs for continuous variables with hepatocellular carcinoma prognosis as an example

In summary, we present LOCC as a novel visualization tool for the analysis of gene expression in cancer, particularly for understanding and selecting cutoffs. Our findings suggest that LOCC scores, which effectively rank genes based on their prognostic potential, represent a more suitable approach than ROC curves and Cox proportional hazard for prognostic modeling and understanding in cancer gene expression analysis. LOCC holds promise as an invaluable tool for advancing precision medicine and furthering biomarker research. Further research regarding multivariable integration and validation will help LOCC reach its full potential and establish its utility across diverse cancer types and clinical settings.