{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T15:26:58Z","timestamp":1791473218318,"version":"4.3.4"},"reference-count":45,"publisher":"BMJ","issue":"9","license":[{"start":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T00:00:00Z","timestamp":1694044800000},"content-version":"unspecified","delay-in-days":6,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"European Regional Development Fund (ERDF) with the Normandy region","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Immunother Cancer"],"accepted":{"date-parts":[[2023,8,14]]},"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p&lt;0.001) for patients with low SFM (&lt;3.95\u2009kg\/m<jats:sup>2<\/jats:sup>), low FBM (&lt;3.26\u2009kg\/m<jats:sup>2<\/jats:sup>), low VFM (&lt;0.91\u2009kg\/m<jats:sup>2<\/jats:sup>), low MBM (&lt;5.85\u2009kg\/m<jats:sup>2<\/jats:sup>) and low BMI (&lt;24.97\u2009kg\/m<jats:sup>2<\/jats:sup>). The same parameters were significant in the Cox univariate analysis (p&lt;0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p&lt;0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (&lt;5.22\u2009kg\/m<jats:sup>2<\/jats:sup>) and MBM (&lt;6.86\u2009kg\/m<jats:sup>2<\/jats:sup>) (p&lt;0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1\u2009year versus 25% (p=0.0029).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/jitc-2023-007315","type":"journal-article","created":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T11:42:17Z","timestamp":1694086937000},"page":"e007315","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":22,"title":["Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer"],"prefix":"10.1136","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5323-9910","authenticated-orcid":false,"given":"Pierre","family":"Decazes","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, Henri Becquerel Cancer Center, 76000 Rouen, France"},{"name":"QuantIF-LITIS (EA[Equipe d'Accueil] 4108), Faculty of Medicine, University of Rouen, 76000 Rouen, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samy","family":"Ammari","sequence":"additional","affiliation":[{"name":"Biomaps, UMR1281 INSERM, CEA, CNRS, University of Paris-Saclay, 94800 Villejuif, France"},{"name":"Department of Imaging, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Younes","family":"Belkouchi","sequence":"additional","affiliation":[{"name":"Biomaps, UMR1281 INSERM, CEA, CNRS, University of Paris-Saclay, 94800 Villejuif, France"},{"name":"Centre de Vision Num\u00e9rique, CentraleSup\u00e9lec, Inria, Universit\u00e9 Paris-Saclay, 91190 Gif-Sur-Yvette, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L\u00e9o","family":"Mottay","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Henri Becquerel Cancer Center, 76000 Rouen, France"},{"name":"QuantIF-LITIS (EA[Equipe d'Accueil] 4108), Faculty of Medicine, University of Rouen, 76000 Rouen, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Littisha","family":"Lawrance","sequence":"additional","affiliation":[{"name":"Biomaps, UMR1281 INSERM, CEA, CNRS, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoine","family":"de Pr\u00e9via","sequence":"additional","affiliation":[{"name":"Biomaps, UMR1281 INSERM, CEA, CNRS, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hugues","family":"Talbot","sequence":"additional","affiliation":[{"name":"Centre de Vision Num\u00e9rique, CentraleSup\u00e9lec, Inria, Universit\u00e9 Paris-Saclay, 91190 Gif-Sur-Yvette, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siham","family":"Farhane","sequence":"additional","affiliation":[{"name":"D\u00e9partement des Innovations Th\u00e9rapeutiques et Essais Pr\u00e9coces, Gustave Roussy, Universit\u00e9 Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul-Henry","family":"Courn\u00e8de","sequence":"additional","affiliation":[{"name":"MICS Lab, CentraleSupelec, Universite Paris-Saclay, 91190 Gif-Sur-Yvette, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5816-3019","authenticated-orcid":false,"given":"Aurelien","family":"Marabelle","sequence":"additional","affiliation":[{"name":"Department of Cancer Medicine, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florian","family":"Guisier","sequence":"additional","affiliation":[{"name":"QuantIF-LITIS (EA[Equipe d'Accueil] 4108), Faculty of Medicine, University of Rouen, 76000 Rouen, France"},{"name":"Department of Pneumology and Inserm CIC-CRB 1404, CHU Rouen, 76000 Rouen, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Planchard","sequence":"additional","affiliation":[{"name":"Department of Cancer Medicine, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tony","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Department of Cancer Medicine, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline","family":"Robert","sequence":"additional","affiliation":[{"name":"Department of Cancer Medicine, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabrice","family":"Barlesi","sequence":"additional","affiliation":[{"name":"Department of Cancer Medicine, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Vera","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Henri Becquerel Cancer Center, 76000 Rouen, France"},{"name":"QuantIF-LITIS (EA[Equipe d'Accueil] 4108), Faculty of Medicine, University of Rouen, 76000 Rouen, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathalie","family":"Lassau","sequence":"additional","affiliation":[{"name":"Biomaps, UMR1281 INSERM, CEA, CNRS, University of Paris-Saclay, 94800 Villejuif, France"},{"name":"Department of Imaging, Gustave Roussy Cancer Campus, University of Paris-Saclay, 94800 Villejuif, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2023,9,7]]},"reference":[{"key":"2025100313152320000_11.9.e007315.1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"2025100313152320000_11.9.e007315.2","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ctrv.2017.10.002","article-title":"PD-1 blockade in advanced NSCLC: A focus on Pembrolizumab","volume":"62","author":"Peters","year":"2018","journal-title":"Cancer Treat Rev"},{"key":"2025100313152320000_11.9.e007315.3","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(21)01206-X"},{"key":"2025100313152320000_11.9.e007315.4","doi-asserted-by":"publisher","DOI":"10.1038\/s41416-018-0294-4"},{"key":"2025100313152320000_11.9.e007315.5","doi-asserted-by":"crossref","first-page":"1321","DOI":"10.1093\/annonc\/mdz167","article-title":"Immune checkpoint inhibitors for patients with advanced lung cancer and oncogenic driver alterations: results from the IMMUNOTARGET registry","volume":"30","author":"Mazieres","year":"2019","journal-title":"Ann Oncol"},{"key":"2025100313152320000_11.9.e007315.6","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(16)30406-5"},{"key":"2025100313152320000_11.9.e007315.7","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1007\/s12149-021-01694-5","article-title":"Prognostic value of total tumour volume, adding necrosis to metabolic tumour volume, in advanced or metastatic non-small cell lung cancer treated with first-line pembrolizumab","volume":"36","author":"Eude","year":"2022","journal-title":"Ann Nucl Med"},{"key":"2025100313152320000_11.9.e007315.8","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1038\/s41571-021-00564-3","article-title":"Tumour burden and efficacy of immune-checkpoint inhibitors","volume":"19","author":"Dall\u2019Olio","year":"2022","journal-title":"Nat Rev Clin Oncol"},{"key":"2025100313152320000_11.9.e007315.9","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2022.982790","article-title":"Predicting Immunotherapy outcomes in patients with MSI tumors using NLR and CT global tumor volume","volume":"12","author":"Belkouchi","year":"2022","journal-title":"Front Oncol"},{"key":"2025100313152320000_11.9.e007315.10","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/S1470-2045(18)30078-0","article-title":"Association of body-mass index and outcomes in patients with metastatic melanoma treated with targeted therapy, immunotherapy, or chemotherapy: a retrospective, multicohort analysis","volume":"19","author":"McQuade","year":"2018","journal-title":"Lancet Oncol"},{"key":"2025100313152320000_11.9.e007315.11","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1007\/s10637-017-0464-x","article-title":"Sarcopenic overweight is associated with early acute limiting toxicity of anti-Pd1 checkpoint inhibitors in Melanoma patients","volume":"35","author":"Heidelberger","year":"2017","journal-title":"Invest New Drugs"},{"key":"2025100313152320000_11.9.e007315.12","doi-asserted-by":"crossref","DOI":"10.1186\/s40425-019-0527-y","article-title":"A multicenter study of body mass index in cancer patients treated with anti-PD-1\/PD-L1 immune checkpoint inhibitors: when overweight becomes favorable","volume":"7","author":"Cortellini","year":"2019","journal-title":"J Immunother Cancer"},{"key":"2025100313152320000_11.9.e007315.13","doi-asserted-by":"crossref","DOI":"10.1080\/2162402X.2019.1580128","article-title":"Sub-cutaneous fat mass measured on Multislice computed tomography of pretreatment PET\/CT is a prognostic factor of stage IV non-small cell lung cancer treated by nivolumab","volume":"8","author":"Popinat","year":"2019","journal-title":"Oncoimmunology"},{"key":"2025100313152320000_11.9.e007315.14","doi-asserted-by":"crossref","DOI":"10.3390\/cancers13246355","article-title":"Impact of Sarcopenia and inflammation on patients with advanced non-small cell lung cancer (NCSCL) treated with immune checkpoint inhibitors (Icis): a prospective study","volume":"13","author":"Tenuta","year":"2021","journal-title":"Cancers (Basel)"},{"key":"2025100313152320000_11.9.e007315.15","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1002\/cncr.32576","article-title":"Adiposity may predict survival in patients with advanced stage cancer treated with Immunotherapy in phase 1 clinical trials","volume":"126","author":"Martini","year":"2020","journal-title":"Cancer"},{"key":"2025100313152320000_11.9.e007315.16","doi-asserted-by":"crossref","DOI":"10.1136\/jitc-2020-000821","article-title":"Impact of body composition on outcomes from anti-Pd1 +\/- anti-CTLA-4 treatment in melanoma","volume":"8","author":"Young","year":"2020","journal-title":"J Immunother Cancer"},{"key":"2025100313152320000_11.9.e007315.17","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1016\/j.diii.2020.04.011","article-title":"Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment","volume":"101","author":"Blanc-Durand","year":"2020","journal-title":"Diagn Interv Imaging"},{"key":"2025100313152320000_11.9.e007315.18","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1097\/RCT.0000000000000652","article-title":"Automatic measurement of the total visceral Adipose tissue from computed tomography images by using a multi-Atlas Segmentation method","volume":"42","author":"Decazes","year":"2018","journal-title":"J Comput Assist Tomogr"},{"key":"2025100313152320000_11.9.e007315.19","doi-asserted-by":"crossref","first-page":"2458","DOI":"10.1038\/oby.2012.168","article-title":"A single MRI slice does not accurately predict visceral and subcutaneous adipose tissue changes during weight loss","volume":"20","author":"Shen","year":"2012","journal-title":"Obesity"},{"key":"2025100313152320000_11.9.e007315.20","doi-asserted-by":"publisher","DOI":"10.1038\/sj.ijo.802229"},{"key":"2025100313152320000_11.9.e007315.21","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1002\/nbm.3286","article-title":"Predictive accuracy of Single- and multi-slice MRI for the estimation of total visceral adipose tissue in overweight to severely obese patients","volume":"28","author":"Schaudinn","year":"2015","journal-title":"NMR Biomed"},{"key":"2025100313152320000_11.9.e007315.22","doi-asserted-by":"crossref","first-page":"5038","DOI":"10.1016\/j.clnu.2021.06.025","article-title":"Deep neural network for automatic volumetric Segmentation of whole-body CT images for body composition assessment","volume":"40","author":"Lee","year":"2021","journal-title":"Clin Nutr"},{"key":"2025100313152320000_11.9.e007315.23","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.ejca.2022.10.013","article-title":"Protective effect of obesity on survival in cancers treated with Immunotherapy vanishes when controlling for type of cancer, weight loss and reduced skeletal muscle","volume":"178","author":"Antoun","year":"2023","journal-title":"Eur J Cancer"},{"key":"2025100313152320000_11.9.e007315.24","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10278-019-00178-3","article-title":"Anthropometer3D: automatic multi-slice Segmentation software for the measurement of anthropometric parameters from CT of PET\/CT","volume":"32","author":"Decazes","year":"2019","journal-title":"J Digit Imaging"},{"key":"2025100313152320000_11.9.e007315.25","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-90187-6","article-title":"Prognostic value of low Skeletal muscle mass in patient treated by exclusive curative radiochemotherapy for a NSCLC","volume":"11","author":"Mallet","year":"2021","journal-title":"Sci Rep"},{"key":"2025100313152320000_11.9.e007315.26","unstructured":"Ronneberger O , Fischer P , Brox T . U-Net: Convolutional networks for BIOMEDICAL image segmentation. Available: http:\/\/arxiv.org\/abs\/1505.04597 [Accessed 1 Feb 2020]."},{"key":"2025100313152320000_11.9.e007315.27","doi-asserted-by":"crossref","DOI":"10.3390\/diagnostics13020205","article-title":"Body composition to define prognosis of cancers treated by anti-angiogenic drugs","volume":"13","author":"Decazes","year":"2023","journal-title":"Diagnostics (Basel)"},{"key":"2025100313152320000_11.9.e007315.28","doi-asserted-by":"publisher","DOI":"10.1093\/ageing\/afq034"},{"key":"2025100313152320000_11.9.e007315.29","doi-asserted-by":"crossref","first-page":"1122","DOI":"10.1002\/jcsm.12755","article-title":"Predictive impact of Sarcopenia in solid cancers treated with immune checkpoint inhibitors: a meta-analysis","volume":"12","author":"Takenaka","year":"2021","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"2025100313152320000_11.9.e007315.30","doi-asserted-by":"crossref","first-page":"111345","DOI":"10.1016\/j.nut.2021.111345","article-title":"Sarcopenia and prognosis of advanced cancer patients receiving immune Checkpoint inhibitors: a comprehensive systematic review and meta-analysis","volume":"90","author":"Deng","year":"2021","journal-title":"Nutrition"},{"key":"2025100313152320000_11.9.e007315.31","doi-asserted-by":"publisher","DOI":"10.1016\/j.lungcan.2020.03.003"},{"key":"2025100313152320000_11.9.e007315.32","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.clnesp.2021.02.017","article-title":"Impact of body composition, nutritional and inflammatory status on outcome of non-small cell lung cancer patients treated with Immunotherapy","volume":"43","author":"Baldessari","year":"2021","journal-title":"Clin Nutr ESPEN"},{"key":"2025100313152320000_11.9.e007315.33","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2022.986236","article-title":"Association of Sarcopenia with survival in advanced NSCLC patients receiving concurrent Immunotherapy and chemotherapy","volume":"12","author":"Bolte","year":"2022","journal-title":"Front Oncol"},{"key":"2025100313152320000_11.9.e007315.34","doi-asserted-by":"crossref","first-page":"7108","DOI":"10.1002\/mp.15821","article-title":"Estimating 3-D whole-body composition from a chest CT scan","volume":"49","author":"Pu","year":"2022","journal-title":"Med Phys"},{"key":"2025100313152320000_11.9.e007315.35","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(08)70153-0"},{"key":"2025100313152320000_11.9.e007315.36","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djt310"},{"key":"2025100313152320000_11.9.e007315.37","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-17-0200"},{"key":"2025100313152320000_11.9.e007315.38","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.lungcan.2016.11.017","article-title":"Obesity is associated with long-term improved survival in definitively treated locally advanced non-small cell lung cancer (NSCLC)","volume":"104","author":"Lam","year":"2017","journal-title":"Lung Cancer"},{"key":"2025100313152320000_11.9.e007315.39","doi-asserted-by":"crossref","DOI":"10.1136\/jitc-2021-004374","article-title":"Prognostic effect of body mass index in patients with advanced NSCLC treated with chemoimmunotherapy combinations","volume":"10","author":"Cortellini","year":"2022","journal-title":"J Immunother Cancer"},{"key":"2025100313152320000_11.9.e007315.40","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1016\/j.jtho.2021.04.020","article-title":"Visceral obesity promotes lung cancer progression-toward resolution of the obesity paradox in lung cancer","volume":"16","author":"Barbi","year":"2021","journal-title":"J Thorac Oncol"},{"key":"2025100313152320000_11.9.e007315.41","doi-asserted-by":"crossref","unstructured":"Li L , Li W , Xu D , et al . Association between visceral fat area and cancer prognosis: a population-based multicenter prospective study. Am J Clin Nutr 2023. doi:10.1016\/j.ajcnut.2023.07.001","DOI":"10.1016\/j.ajcnut.2023.07.001"},{"key":"2025100313152320000_11.9.e007315.42","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0169136","article-title":"Prognostic impact of CT-quantified muscle and fat distribution before and after first-line-chemotherapy in lung cancer patients","volume":"12","author":"Nattenm\u00fcller","year":"2017","journal-title":"PLoS ONE"},{"key":"2025100313152320000_11.9.e007315.43","doi-asserted-by":"crossref","first-page":"139","DOI":"10.14740\/wjon1289","article-title":"Sarcopenia and visceral Adiposity are not independent Prognostic markers for extensive disease of small-cell lung cancer: a single-centered retrospective cohort study","volume":"11","author":"Minami","year":"2020","journal-title":"World J Oncol"},{"key":"2025100313152320000_11.9.e007315.44","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0277708","article-title":"Effect of body tissue composition on the outcome of patients with metastatic non-small cell lung cancer treated with PD-1\/PD-L1 inhibitors","volume":"18","author":"Makrakis","year":"2023","journal-title":"PLoS One"},{"key":"2025100313152320000_11.9.e007315.45","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1801946"}],"container-title":["Journal for ImmunoTherapy of Cancer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1136\/jitc-2023-007315","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T20:15:33Z","timestamp":1759522533000},"score":1,"resource":{"primary":{"URL":"https:\/\/jitc.bmj.com\/lookup\/doi\/10.1136\/jitc-2023-007315"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":45,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2023,9,7]]},"published-print":{"date-parts":[[2023,9]]}},"alternative-id":["10.1136\/jitc-2023-007315"],"URL":"https:\/\/doi.org\/10.1136\/jitc-2023-007315","relation":{},"ISSN":["2051-1426"],"issn-type":[{"value":"2051-1426","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]}}}