NSCLC PD-1 PD-L1 PET/CT immunotherapy response to therapy

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
05 May 2020
Historique:
received: 11 03 2020
revised: 21 04 2020
accepted: 30 04 2020
entrez: 9 5 2020
pubmed: 10 5 2020
medline: 10 5 2020
Statut: epublish

Résumé

(1.1) to evaluate the association between baseline 18F-FDG PET/CT semi-quantitative parameters of the primary lesion with progression free survival (PFS), overall survival (OS) and response to immunotherapy, in advanced non-small cell lung carcinoma (NSCLC) patients eligible for immunotherapy; (1.2) to evaluate the application of radiomics analysis of the primary lesion to identify features predictive of response to immunotherapy; (1.3) to evaluate if tumor burden assessed by 18F-FDG PET/CT (N and M factors) is associated with PFS and OS. we retrospectively analyzed clinical records of advanced NCSLC patients (stage IIIb/c or stage IV) candidate to immunotherapy who performed 18F-FDG PET/CT before treatment to stage the disease. Fifty-seven (57) patients were included in the analysis (F:M 17:40; median age = 69 years old). Notably, 38/57 of patients had adenocarcinoma (AC), 10/57 squamous cell carcinoma (SCC) and 9/57 were not otherwise specified (NOS). Overall, 47.4% patients were stage IVA, 42.1% IVB and 8.8% IIIB. Immunotherapy was performed as front-line therapy in 42/57 patients and as second line therapy after chemotherapy platinum-based in 15/57. The median follow up after starting immunotherapy was 10 months (range: 1.5-68.6). Therapy response was assessed by RECIST 1.1 criteria (CT evaluation every 4 cycles of therapy) in 48/57 patients or when not feasible by clinical and laboratory data (fast disease progression or worsening of patient clinical condition in nine patients). Radiomics analysis was performed by applying regions of interest (ROIs) of the primary tumor delineated manually by two operators and semi-automatically applying a threshold at 40% of SUVmax. (1.1) metabolic tumor volume (MTV) ( 18F-FDG PET/CT performed before the start of immunotherapy might be an important prognostic tool able to predict the disease progression and response to immunotherapy in patients with advanced NSCLC, since MTV, TLG and radiomics features (volume and heterogeneity) are associated with disease progression.

Identifiants

pubmed: 32380754
pii: cancers12051163
doi: 10.3390/cancers12051163
pmc: PMC7281558
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

Eur J Nucl Med Mol Imaging. 2018 Sep;45(10):1649-1660
pubmed: 29623375
N Engl J Med. 2018 Nov 22;379(21):2040-2051
pubmed: 30280635
Radiology. 2012 Aug;264(2):559-66
pubmed: 22692034
EJNMMI Res. 2016 Dec;6(1):53
pubmed: 27334609
Eur J Nucl Med Mol Imaging. 2012 Jan;39(1):27-38
pubmed: 21946983
Eur J Nucl Med Mol Imaging. 2017 Nov;44(12):1969-1983
pubmed: 28689281
Curr Oncol. 2019 Feb;26(1):e57-e63
pubmed: 30853810
Eur J Nucl Med Mol Imaging. 2020 May;47(5):1168-1182
pubmed: 31807885
Radiat Oncol. 2015 Apr 22;10:100
pubmed: 25900186
JAMA. 2013 Sep 4;310(9):982
pubmed: 24002295
Eur J Cancer. 2009 Jan;45(2):228-47
pubmed: 19097774
J Nucl Med. 2008 Jun;49(6):892-8
pubmed: 18483085
JAMA Oncol. 2018 Mar 1;4(3):351-357
pubmed: 29327044
Eur J Nucl Med Mol Imaging. 2013 Jan;40(2):290-301
pubmed: 23151913
Oncology. 2017;92(1):39-47
pubmed: 27832654
CA Cancer J Clin. 2018 Jan;68(1):7-30
pubmed: 29313949
Ann Oncol. 2019 Jun 1;30(6):879-881
pubmed: 31124559
Radiol Oncol. 2015 Nov 27;49(4):320-6
pubmed: 26834517
Sci Rep. 2017 Mar 23;7(1):358
pubmed: 28336974
Quant Imaging Med Surg. 2016 Feb;6(1):6-15
pubmed: 26981450
Chest. 2017 Jan;151(1):193-203
pubmed: 27780786
N Engl J Med. 2016 Nov 10;375(19):1823-1833
pubmed: 27718847
Eur J Nucl Med Mol Imaging. 2011 Sep;38(9):1628-35
pubmed: 21617977
Nucl Med Commun. 2019 Aug;40(8):802-807
pubmed: 31045745
Cancer Res. 2018 Aug 15;78(16):4786-4789
pubmed: 29959149
Nat Commun. 2014 Jun 03;5:4006
pubmed: 24892406
Ann Oncol. 2019 Jun 1;30(6):998-1004
pubmed: 30895304
Cancer Immunol Immunother. 2019 Sep;68(9):1537-1545
pubmed: 31482306
Eur J Nucl Med Mol Imaging. 2018 Jun;45(6):1072-1075
pubmed: 29532102
Clin Nucl Med. 2018 Jan;43(1):e8-e17
pubmed: 29112011

Auteurs

Giulia Polverari (G)

Division of Nuclear Medicine, Department of Medical Sciences, University of Turin, AOU Città della Salute e della Scienza, 10126 Turin, Italy.
PET/CT Center, Affidea IRMET, 10135 Turin, Italy.

Francesco Ceci (F)

Division of Nuclear Medicine, Department of Medical Sciences, University of Turin, AOU Città della Salute e della Scienza, 10126 Turin, Italy.

Valentina Bertaglia (V)

Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, 10043 Torino, Italy.

Maria Lucia Reale (ML)

Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, 10043 Torino, Italy.

Osvaldo Rampado (O)

Medical Physics Unit, S.C. Fisica Sanitaria, A.O.U. Città della Salute e della Scienza, 10135 Turin, Italy.

Elena Gallio (E)

Medical Physics Unit, S.C. Fisica Sanitaria, A.O.U. Città della Salute e della Scienza, 10135 Turin, Italy.

Roberto Passera (R)

Division of Nuclear Medicine, Department of Medical Sciences, University of Turin, AOU Città della Salute e della Scienza, 10126 Turin, Italy.

Virginia Liberini (V)

Division of Nuclear Medicine, Department of Medical Sciences, University of Turin, AOU Città della Salute e della Scienza, 10126 Turin, Italy.

Paola Scapoli (P)

Nuclear Medicine, Istituto per la Ricerca e la Cura del Cancro (IRCC), 10060 Candiolo, Italy.

Vincenzo Arena (V)

PET/CT Center, Affidea IRMET, 10135 Turin, Italy.

Manuela Racca (M)

Nuclear Medicine, Istituto per la Ricerca e la Cura del Cancro (IRCC), 10060 Candiolo, Italy.

Andrea Veltri (A)

Radiology Unit, Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, 10043 Torino, Italy.

Silvia Novello (S)

Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, 10043 Torino, Italy.

Désirée Deandreis (D)

Division of Nuclear Medicine, Department of Medical Sciences, University of Turin, AOU Città della Salute e della Scienza, 10126 Turin, Italy.

Classifications MeSH