Insights for Quantifying the Long-Term Benefit of Immunotherapy Using Quantile Regression

Bassirou Mboup (1, 2) , Christophe Le Tourneau (2) , Aurélien Latouche (1, 3)

1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
2 INSERM - Institut National de la Santé et de la Recherche Médicale
3 Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe

PURPOSE Immunotherapy has been approved to treat many tumor types. However, one characteristic of this therapeutic class is that survival benefit is due to late immune response, which leads to a delayed treatment effect. Quantifying the benefit, if any, of such treatment, will thus require other metrics than the usual hazard ratio and different approaches have been proposed to quantify the long-term response of immunotherapy. METHOD In this paper, we suggest to use quantile regression for survival data to quantify the long-term benefit of immunotherapy. Our motivation is that this approach is not trial-specific and provides clinically understandable results without specifying arbitrary time points or the necessity to reach median survival, as is the case with other methods. We use reconstructed data from published Kaplan-Meier curves to illustrate our method. RESULTS On average, patients from the immunotherapy group have 60% chance to survive 5.46 months (95% CI, 2.57 to 9.02) more than patients in the chemotherapy group.

Domaines: Cancer; Immunothérapie; Applications [stat.AP]

Bassirou Mboup, Christophe Le Tourneau, Aurélien Latouche. Insights for Quantifying the Long-Term Benefit of Immunotherapy Using Quantile Regression. JCO precision oncology, 2021, 5, pp.173-176. ⟨10.1200/PO.20.00164⟩. ⟨hal-03822479⟩