Author(s)

Mingyu Sun ¹

Affiliation(s)

¹ University of Toronto, Mississauga, Ontario, Canada

Corresponding Author

Mingyu Sun

ABSTRACT

This study employed survival analysis methods to evaluate the effects of different tumor immunotherapy combinations on patient survival time and risk of death. By analyzing clinical data from 200 patients with advanced tumors, the Kaplan-Meier survival curve, Cox proportional hazards model, and LASSO regression method were used to identify biomarkers significantly associated with survival. Results indicated that immunotherapy combined with targeted therapy most effectively prolonged survival and reduced mortality risk, significantly outperforming other combinations. Cluster analysis was also used to explore treatment response heterogeneity among tumor samples, revealing differential immunotherapy efficacy among different subtypes, with some responding more favorably to combined treatments. LASSO regression feature screening successfully reduced overfitting risk while retaining key features significantly impacting survival. In summary, this study demonstrated significant advantages of immunotherapy combination use in tumor treatment, providing a theoretical basis for optimizing treatment strategies.

KEYWORDS

Tumor Immunotherapy; Combined Treatment Regimen; Survival Analysis; Lasso Regression; Cox Proportional Hazard Model

CITE THIS PAPER

Mingyu Sun, A Comparative Evaluation of Survival Analysis Methods for Tumor Immunotherapy Combination Regimens. Social Medicine and Health Management (2024) Vol. 5: 95-104. DOI: http://dx.doi.org/10.23977/socmhm.2024.050213.

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