Title |
Metabolic activity by 18F–FDG-PET/CT is predictive of early response after nivolumab in previously treated NSCLC
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Published in |
European Journal of Nuclear Medicine and Molecular Imaging, August 2017
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DOI | 10.1007/s00259-017-3806-1 |
Pubmed ID | |
Authors |
Kyoichi Kaira, Tetsuya Higuchi, Ichiro Naruse, Yukiko Arisaka, Azusa Tokue, Bolag Altan, Satoshi Suda, Akira Mogi, Kimihiro Shimizu, Noriaki Sunaga, Takeshi Hisada, Shigehisa Kitano, Hideru Obinata, Takehiko Yokobori, Keita Mori, Masahiko Nishiyama, Yoshihito Tsushima, Takayuki Asao |
Abstract |
Nivolumab, an anti-programmed death-1 (PD-1) antibody, is administered in patients with previously treated non-small cell lung cancer. However, little is known about the established biomarker predicting the efficacy of nivolumab. Here, we conducted a preliminary study to investigate whether (18)F-FDG-PET/CT could predict the therapeutic response of nivolumab at the early phase. Twenty-four patients were enrolled in this study. (18)F-FDG-PET/CT was carried out before and 1 month after nivolumab therapy. SUVmax, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were calculated. Immunohistochemical analysis of PD-L1 expression and tumour-infiltrating lymphocytes was conducted. Among all patients, a partial metabolic response to nivolumab was observed in 29% on SUVmax, 25% on MTV, and 33% on TLG, whereas seven (29%) patients achieved a partial response (PR) based on RECIST v1.1. The predictive probability of PR (100% vs. 29%, p = 0.021) and progressive disease (100% vs. 22.2%, p = 0.002) at 1 month after nivolumab initiation was significantly higher in (18)F-FDG on PET/CT than in CT scans. Multivariate analysis confirmed that (18)F-FDG uptake after administration of nivolumab was an independent prognostic factor. PD-L1 expression and nivolumab plasma concentration could not precisely predict the early therapeutic efficacy of nivolumab. Metabolic response by (18)F-FDG was effective in predicting efficacy and survival at 1 month after nivolumab treatment. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 101 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 13 | 13% |
Researcher | 13 | 13% |
Other | 12 | 12% |
Student > Master | 10 | 10% |
Student > Bachelor | 8 | 8% |
Other | 20 | 20% |
Unknown | 25 | 25% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 51 | 50% |
Biochemistry, Genetics and Molecular Biology | 4 | 4% |
Agricultural and Biological Sciences | 4 | 4% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 3% |
Immunology and Microbiology | 3 | 3% |
Other | 7 | 7% |
Unknown | 29 | 29% |