Quality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancer

Background Despite immune checkpoint inhibitors(ICIs) significantly improves clinical outcomes in patients with advanced non-small cell lung cancer (NSCLC), disease progression is inevitable. A diverse patient-reported Quality-of-life(QoL) scale attempts to predict outcomes for aNSCLC patients received atezolizumab using machine learning. Materials and Methods This study analysized the association between baseline QoL and clinical outcome in aNSCLC patients received atezolizumab in 4 randomized clinical trials: the IMpower150 study (discovery cohort), the BIRCH, OAK and POPLAR study (validation cohorts). We identified quality of life subtypes (QoLS) by consensus clustering in the discovery cohort and predicted them in external validated cohorts. Results We identified QoLS1 and QoLS2 via consensus clustering in the discovery cohort. Compared with QoLS2, patients in QoLS1 had a significantly longer median OS(13.14 vs. 21.42 months, hazard ratio [HR] 2.07 [1.64–2.62]; p < 0.0001) and PFS(5.7 vs. 8.3 months, HR 1.70 [1.42–2.04]; p < 0.0001), and higher clinical benefit rates( 68% vs 57% ,p = 0.0027) with 6, 12 and 24-month time-dependent AUC of 0.61, 0.6 and 0.53 for OS, respectively. We observed similar favorable trends for OS (p < 0.0001) for predicted QoLS1 in the external cohorts using the PAM algorithm. Additionally, QoLS1 served as a strong predictive biomarkers for atezolizumab (ICI)-treated aNSCLC patients in comparison with chemotherapy (non-ICI)-treated patients regarding OS in both the IMpower150 trial (QoLS1: HR _{ICI vs. non−ICI} = 1.30, p = 0.04; QoLS2: HR _{ICI vs. non−ICI} = 1.21, p = 0.2) and the OAK + POPLAR trials (QoLS1: HR _{ICI vs. non−ICI} = 1.27, p = 0.007; QoLS2: HR _{ICI vs. non−ICI} = 1.21, p = 0.07). Conclusions Our study demonstrated the potential of integrative machine learning in effectively analyzing QoL and predicting clinical outcomes in aNSCLC patients undergoing atezolizumab immunotherapy.