Clinical decision support algorithm based on machine learning to assess the clinical response to anti –programmed death-1 therapy in patients with non–small-cell lung cancer

Anti –programmed death (PD)-1 therapy confers sustainable clinical benefits for patients with non–small-cell lung cancer (NSCLC), but only some patients respond to the treatment. Various clinical characteristics, including the PD-ligand 1 (PD-L1) level, are related to the anti–PD-1 response; howeve r, none of these can independently serve as predictive biomarkers. Herein, we established a machine learning (ML)–based clinical decision support algorithm to predict the anti–PD-1 response by comprehensively combining the clinical information.

Source: European Journal of Cancer - June 25, 2021 Category: Cancer & Oncology Authors: Beung-Chul Ahn, Jea-Woo So, Chun-Bong Synn, Tae Hyung Kim, Jae Hwan Kim, Yeongseon Byeon, Young Seob Kim, Seong Gu Heo, San-Duk Yang, Mi Ran Yun, Sangbin Lim, Su-Jin Choi, Wongeun Lee, Dong Kwon Kim, Eun Ji Lee, Seul Lee, Doo-Jae Lee, Chang Gon Kim, Sun M Tags: Original Research Source Type: research