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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development of a prognostic nomogram for advanced non-small cell lung cancer using clinical characteristics
Haoyue Qin1, Zhe Huang1, Huan Yan1
1Department of Medical Oncology, Lung Cancer and Gastrointestinal Unit, Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410013, China.
Abstract:
This retrospective study demonstrated that patients with advanced non-small cell lung cancer who experienced any-grade or grade 1-2 immune-related adverse events (irAEs) with immune checkpoint inhibitor plus chemotherapy (ICI+Chemo) as first-line treatment regimen had significantly longer progression-free survival (PFS; p < 0.001) and overall survival (OS; p < 0.05) compared with patients without any irAE. Three variables were identified as predictors of favorable PFS and OS: absence of baseline brain metastasis (p < 0.05), receiving first-line ICI+Chemo (p < 0.01), and occurrence of any grade adverse events (p < 0.001). Using these three variables, two nomograms were generated to predict PFS and OS, which were validated using two independent cohorts treated with Chemo or ICI+Chemo (n = 161) or ICI monotherapy (n = 109). Patients with low scores in discovery and validation cohorts consistently had significantly longer PFS (p < 0.001) and OS (p < 0.05) than those with high scores. Our findings provide preliminary evidence of the clinical utility of a nomogram in prognosticating ICI-treated patients.
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