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© 2020 Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Background

Reliable predictive and prognostic markers are still lacking for patients treated with programmed death receptor 1 (PD1) inhibitors for non-small cell lung cancer (NSCLC). The purpose of this study was to investigate the prognostic and predictive values of different baseline metabolic parameters, including metabolic tumor volume (MTV), from 18F-fluorodeoxyglucose positron emission tomography–computed tomography (18F-FDG PET/CT) scans in patients with NSCLC treated with PD1 inhibitors.

Methods

Maximum and peak standardized uptake values, MTV and total lesion glycolysis (TLG), as well as clinical and biological parameters, were recorded in 75 prospectively included patients with NSCLC treated with PD1 inhibitors. Associations between these parameters and overall survival (OS) were evaluated as well as their accuracy to predict early treatment discontinuation (ETD).

Results

A high MTV and a high TLG were significantly associated with a lower OS (p<0.001). The median OS in patients with MTV above the median (36.5 cm3) was 10.5 months (95% CI: 6.2 to upper limit: unreached), while the median OS in patients with MTV below the median was not reached. Patients with no prior chemotherapy had a poorer OS than patients who had received prior systemic treatment (p=0.04). MTV and TLG could reliably predict ETD (area under the receiver operating characteristic curve=0.76, 95% CI: 0.65 to 0.87 and 0.72, 95% CI: 0.62 to 0.84, respectively).

Conclusion

MTV is a strong prognostic and predictive factor in patients with NSCLC treated with PD1 inhibitors and can be easily determined from routine 18F-FDG PET/CT scans. MTV, could help to personalize immunotherapy and be used to stratify patients in future clinical studies.

Details

Title
Baseline metabolic tumor volume as a strong predictive and prognostic biomarker in patients with non-small cell lung cancer treated with PD1 inhibitors: a prospective study
Author
Chardin, David 1   VIAFID ORCID Logo  ; Paquet, Marie 2 ; Schiappa, Renaud 3 ; Darcourt, Jacques 1 ; Bailleux, Caroline 4 ; Poudenx, Michel 5 ; Sciazza, Aurélie 2 ; Ilie, Marius 6 ; Benzaquen, Jonathan 7 ; Martin, Nicolas 5 ; Otto, Josiane 5 ; Humbert, Olivier 1 

 Department of Nuclear Medicine, Centre Antoine-Lacassagne, Université Côte d'Azur (UCA), Nice, France; Laboratoire TIRO (UMR E 4320), Université Côté d'Azur (UCA), Nice, France 
 Department of Nuclear Medicine, Centre Antoine-Lacassagne, Université Côte d'Azur (UCA), Nice, France 
 Department of Epidemiology, Biostatistics and Health Data, Centre Antoine-Lacassagne, Université Côte d'Azur (UCA), Nice, Provence-Alpes-Côte d'Azur, France 
 Laboratoire TIRO (UMR E 4320), Université Côté d'Azur (UCA), Nice, France; Department of Medical Oncology, Centre Antoine-Lacassagne, Université Côte d'Azur (UCA), Nice, France 
 Department of Medical Oncology, Centre Antoine-Lacassagne, Université Côte d'Azur (UCA), Nice, France 
 Laboratory of Clinical and Experimental Pathology, Hospital-Integrated Biobank (BB-0033-00025), Centre Hospitalier Universitaire de Nice, Université Côte d'Azur (UCA), Nice, France 
 Department of Pulmonology and Thoracic Oncology, Centre Hospitalier Universitaire de Nice, Université Côte d'Azur (UCA), Nice, France 
First page
e000645
Section
Immunotherapy biomarkers
Publication year
2020
Publication date
Jul 2020
Publisher
BMJ Publishing Group LTD
e-ISSN
20511426
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2552991811
Copyright
© 2020 Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.