A predictive model for evaluating the efficacy of immunotherapy in non-small-cell lung cancer patients: A real-world study.

ABSTRACT: ObjectiveThe predictive accuracy of the efficacy of immunotherapy remains poor. Therefore, we aimed to develop a predictive model based on gene mutations to assess the immunotherapeutic efficacy in non-small-cell lung cancer.MethodsThree hundred and thirty-five non-small-cell lung cancer patients treated with immune checkpoint inhibitors were included in our study. The least absolute shrinkage and selection operator Cox regression model, multivariable analysis, and Kaplan-Meier test were used in this study.ResultsWe constructed a predictive model based on a 42-gene signature. Patients were classified into low-risk and high-risk groups based on risk scores generated from this model. Compared with patients in the high-risk group, those in the low-risk group showed better survival (median sur

SUBMITTER: Yu HH 

PROVIDER: S-EPMC12408997 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature