Advances in models predicting efficacy of immune checkpoint inhibitors

Abstract

The use of immune checkpoint inhibitor (ICI) has revolutionized the treatment among patients with various types of tumors. However, only some patients can benefit from ICI. The identification of predictive markers of response to treatment in patients is required, such as programmed death ligand-1 (PD-L1) and tumor mutation burden (TMB). Besides, there have been numerous studies using sequence and radiomics data based on large populations to explore the factors related to the efficacy, and to establish the prediction model. This kind of model has a rigorous establishment and validation process, can include more tumor immune related variables, and is helpful to improve the prediction ability of the efficacy of ICI. This paper reviewed the establishment of immunotherapy prediction models and provided new thoughts pertaining to screening the potential beneficiaries from immunotherapy.

Keywords

• |immunotherapy|efficacy|prognosis|prediction model