부산대학교 도서관

Backgrounds: Immune checkpoint inhibitors (ICIs) can significantly prolong the survival of patients with advanced non‐small‐cell lung cancer (NSCLC); however, few studies on the therapeutic effects of ICIs on bone metastases were performed. Methods: This retrospective study aimed to investigate the therapeutic effects of ICIs and determine predictors of favorable ICI response and prognosis in 55 advanced NSCLC patients with bone metastases who initiated ICI treatment between 2016 and 2019, with a mean follow‐up period of 23.2 months. Patients were classified into responders (complete or partial response) and non‐responders (stable or progressive disease) according to the MD Anderson Cancer Center (MDA) criteria, and the predictors of therapeutic response were identified using multivariate logistic regression analysis. Furthermore, overall survival from the time of ICI administration to the final follow‐up or death was evaluated, and prognostic predictors were identified using Cox proportional hazards regression analysis. Results: ICI response rate was 30.9% (complete in three cases, partial in 14). Median survival time was 9.3 months, with 1‐year and 2‐year survival rates of 40.6% and 19.3%, respectively. Responders survived significantly longer than non‐responders (p = 0.03). Based on the receiver operating characteristic curve, the predictive cutoff value of the pretreatment neutrophil‐to‐lymphocyte ratio (NLR) was 2.1. Multivariate analysis identified female sex (p = 0.03), use of ICIs as first‐line therapy (p < 0.01), and NLR <2.1 (p = 0.03) as significant predictors of therapeutic response, whereas concomitant use of a bone‐modifying agent (p < 0.01), Katagiri score ≤6 points (p < 0.01), and NLR <2.1 (p = 0.02) were identified as significant predictors of good prognosis. Conclusions: This study identified some novel predictors for favorable therapeutic response and prognosis in advanced NSCLC patients with bone metastases undergoing ICI treatment. Pretreatment NLR less than 2.1 can be considered the most important predictor. [ABSTRACT FROM AUTHOR]