Publication-only abstracts (abstract number preceded by an "e"), published in conjunction with the 2019 ASCO Annual Meeting but not presented at the Meeting, can be found online only.
Nomogram based on multivariable regression model estimates the overall survival of patients with nivolumab who were previously treated for advanced non-small cell lung cancer.
Metastatic Non-Small Cell Lung Cancer
Lung Cancer—Non-Small Cell Metastatic
2019 ASCO Annual Meeting
J Clin Oncol 37, 2019 (suppl; abstr e20683)
Author(s): Motohiro Tamiya, Akihiro Tamiya, Hirofumi Go, Takako Inoue, Madoka Kimura, Kei Kunimasa, Kenji Nakahama, Yoshihiko Taniguchi, Takayuki Shiroyama, Shun-Ichi Isa, Kazumi Nishino, Toru Kumagai, Hidekazu Suzuki, Tomonori Hirashima, Shinji Atagi, Ayumi Shintani, Fumio Imamura; Department of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan; Department of Internal Medicine, National Hospital Organization Kinki-Chuo Chest Medical Center, Sakai, Japan; Department of Medical Statistics, Osaka City University Graduate School of Medicine, Osaka, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan; Department of Thoracic Malignancy, Osaka Habikino Medical Center, Habikino, Japan
Background: Nivolumab (Nivo) has demonstrated with its efficacy against metastatic non-small cell lung cancer (NSCLC). However, it has been also reported that Nivo does not show beneficial effects in approximately 80% of patients. The predictive ability of biomarkers still is yet unclear; thus identifying biomarkers which better predict overall survival (OS) of such patients treated with Nivo is crucial. In this study, we conducted multivariable cox regression analysis including biomarkers and clinical factors measured at the time of initiating treatment with Nivo to assess predictive ability of OS of patients. Results of the multivariable analysis were elucidated with a nomogram which estimates the OS of Nivo in previously treated patients with advanced NSCLC. Methods: In this study, data for 201 patients treated with nivolumab during 17 December 2015 to 31 July 2016 at three respiratory medical centers in Japan were retrospectively reviewed. We collected clinical data at the time of nivolumab treatment commencement, and we evaluated two programmed cell death ligand 1 (PD-L1) immunohistochemistry (IHC) assay systems (22C3 and 28-8). Results: The median age at the time of administration nivolumab was 68 years, 135 patients were male, 157 patients had a smoking history, and 152 patients had a performance status (PS) score of 0–1. 39 patients had EGFR (37) or ALK (2) mutation positive. For 22C3 and 28-8, 36.3% and 36.8% of patients were negative, 17.4% and 14.4% had PD-L1 status of 1-49%, and 11.9% and 14.9% had PD-L1 status of ≥50%, 34.3% and 33.8% had PD-L1 status of missing, respectively. Kendall’s rank correlation coefficient between 22C3 and 28-8 was 0.8414. The median OS of all patients was 333 (95% confidence interval (CI): 116-520) days. In the multivariate analysis, PS score ≥2 (hazard ratio (HR): 2.23; 95%CI: 1.36-3.66 p < 0.001), high LDH level at baseline (HR: 1.13 95%CI: 1.03-1.24; p = 0.008, and progression disease (PD) of pre-treatment response (HR: 3.64 95%CI: 2.29-5.79 p < 0.001) were significantly associated with poor OS. There was not significant distance between PD-L1 status and OS of Nivo. Based on these analyses, we created the nomogram to estimate the OS of Nivo in previously treated patients with advanced NSCLC. Conclusions: PS score ≥2, high LDH levels at baseline, and PD of pre-treatment response were predictive of poor OS of Nivo, moreover the nomogram might be useful to estimate the OS of Nivo in previously treated patients with advanced NSCLC.