Total Metabolic Tumor Volume on F-FDG PET/CT is a Game-changer for Patients with Metastatic Lung Cancer Treated with Immunotherapy

Overview

Journal J Immunother Cancer

Specialties Allergy & Immunology
Oncology
Pharmacology

Date 2024 Apr 22

PMID 38649279

Authors

Pierre Tricarico

David Chardin

Nicolas Martin

Sara Contu

Florent Hugonnet

Josiane Otto

Olivier Humbert

Affiliations

Soon will be listed here.

Abstract

Purpose: Because of atypical response imaging patterns in patients with metastatic non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs), new biomarkers are needed for a better monitoring of treatment efficacy. The aim of this prospective study was to evaluate the prognostic value of volume-derived positron-emission tomography (PET) parameters on baseline and follow-up F-fluoro-deoxy-glucose PET (F-FDG-PET) scans and compare it with the conventional PET Response Criteria in Solid Tumors (PERCIST).

Methods: Patients with metastatic NSCLC were included in two different single-center prospective trials. F-FDG-PET studies were performed before the start of immunotherapy (PET), after 6-8 weeks (PET1) and after 12-16 weeks (PET2) of treatment, using PERCIST criteria for tumor response assessment. Different metabolic parameters were evaluated: absolute values of maximum standardized uptake value (SUVmax) of the most intense lesion, total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), but also their percentage changes between PET studies (ΔSUVmax, ΔTMTV and ΔTLG). The median follow-up of patients was 31 (7.3-31.8) months. Prognostic values and optimal thresholds of PET parameters were estimated by ROC (Receiver Operating Characteristic) curve analysis of 12-month overall survival (12M-OS) and 6-month progression-free survival (6M-PFS). Tumor progression needed to be confirmed by a multidisciplinary tumor board, considering atypical response patterns on imaging.

Results: 110 patients were prospectively included. On PET, TMTV was predictive of 12M-OS [AUC (Area Under Curve) =0.64; 95% CI: 0.61 to 0.66] whereas SUVmax and TLG were not. On PET1 and PET2, all metabolic parameters were predictive for 12M-OS and 6M-PFS, the residual TMTV on PET1 (TMTV) being the strongest prognostic biomarker (AUC=0.83 and 0.82; 95% CI: 0.74 to 0.91, for 12M-OS and 6M-PFS, respectively). Using the optimal threshold by ROC curve to classify patients into three TMTV subgroups (0 cm; 0-57 cm; >57 cm), TMTV prognostic stratification was independent of PERCIST criteria on both PFS and OS, and significantly outperformed them. Subgroup analysis demonstrated that TMTV remained a strong prognostic biomarker of 12M-OS for non-responding patients (p=0.0003) according to PERCIST criteria. In the specific group of patients with PERCIST progression on PET1, low residual tumor volume (<57 cm) was still associated with a very favorable patients' outcome (6M-PFS=73%; 24M-OS=55%).

Conclusion: The absolute value of residual metabolic tumor volume, assessed 6-8 weeks after the start of ICPI, is an optimal and independent prognostic measure, exceeding and complementing conventional PERCIST criteria. Oncologists should consider it in patients with first tumor progression according to PERCIST criteria, as it helps identify patients who benefit from continued treatment.

Trial Registration Number: 2018-A02116-49; NCT03584334.

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References

Horn L, Spigel D, Vokes E, Holgado E, Ready N, Steins M . Nivolumab Versus Docetaxel in Previously Treated Patients With Advanced Non-Small-Cell Lung Cancer: Two-Year Outcomes From Two Randomized, Open-Label, Phase III Trials (CheckMate 017 and CheckMate 057). J Clin Oncol. 2017; 35(35):3924-3933. PMC: 6075826. DOI: 10.1200/JCO.2017.74.3062. View

Eisenhauer E, Therasse P, Bogaerts J, Schwartz L, Sargent D, Ford R . New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2008; 45(2):228-47. DOI: 10.1016/j.ejca.2008.10.026. View

Gibney G, Weiner L, Atkins M . Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol. 2016; 17(12):e542-e551. PMC: 5702534. DOI: 10.1016/S1470-2045(16)30406-5. View

Guibert N, Delaunay M, Lusque A, Boubekeur N, Rouquette I, Clermont E . PD-L1 expression in circulating tumor cells of advanced non-small cell lung cancer patients treated with nivolumab. Lung Cancer. 2018; 120:108-112. DOI: 10.1016/j.lungcan.2018.04.001. View

DallOlio F, Marabelle A, Caramella C, Garcia C, Aldea M, Chaput N . Tumour burden and efficacy of immune-checkpoint inhibitors. Nat Rev Clin Oncol. 2021; 19(2):75-90. DOI: 10.1038/s41571-021-00564-3. View

Bianchi A, De Rimini M, Sciuto R, Annovazzi A, Di Traglia S, Bauckneht M . Can Baseline [F]FDG PET/CT Predict Response to Immunotherapy After 6 Months and Overall Survival in Patients with Lung Cancer or Malignant Melanoma? A Multicenter Retrospective Study. Cancer Biother Radiopharm. 2023; 38(4):256-267. DOI: 10.1089/cbr.2022.0092. View

Davis A, Patel V . The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors. J Immunother Cancer. 2019; 7(1):278. PMC: 6815032. DOI: 10.1186/s40425-019-0768-9. View

Monaco L, Gemelli M, Gotuzzo I, Bauckneht M, Crivellaro C, Genova C . Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience. Cancers (Basel). 2021; 13(7). PMC: 8037395. DOI: 10.3390/cancers13071634. View

Reck M, Rodriguez-Abreu D, Robinson A, Hui R, Csoszi T, Fulop A . Updated Analysis of KEYNOTE-024: Pembrolizumab Versus Platinum-Based Chemotherapy for Advanced Non-Small-Cell Lung Cancer With PD-L1 Tumor Proportion Score of 50% or Greater. J Clin Oncol. 2019; 37(7):537-546. DOI: 10.1200/JCO.18.00149. View

10.

Lang D, Ritzberger L, Rambousek V, Horner A, Wass R, Akbari K . First-Line Pembrolizumab Mono- or Combination Therapy of Non-Small Cell Lung Cancer: Baseline Metabolic Biomarkers Predict Outcomes. Cancers (Basel). 2021; 13(23). PMC: 8656760. DOI: 10.3390/cancers13236096. View

11.

Hashimoto K, Kaira K, Yamaguchi O, Mouri A, Shiono A, Miura Y . Potential of FDG-PET as Prognostic Significance after anti-PD-1 Antibody against Patients with Previously Treated Non-Small Cell Lung Cancer. J Clin Med. 2020; 9(3). PMC: 7141299. DOI: 10.3390/jcm9030725. View

12.

Seban R, Mezquita L, Berenbaum A, Dercle L, Botticella A, Le Pechoux C . Baseline metabolic tumor burden on FDG PET/CT scans predicts outcome in advanced NSCLC patients treated with immune checkpoint inhibitors. Eur J Nucl Med Mol Imaging. 2019; 47(5):1147-1157. DOI: 10.1007/s00259-019-04615-x. View

13.

Capobianco N, Meignan M, Cottereau A, Vercellino L, Sibille L, Spottiswoode B . Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma. J Nucl Med. 2020; 62(1):30-36. PMC: 8679589. DOI: 10.2967/jnumed.120.242412. View

14.

Onesti C, Freres P, Jerusalem G . Atypical patterns of response to immune checkpoint inhibitors: interpreting pseudoprogression and hyperprogression in decision making for patients' treatment. J Thorac Dis. 2019; 11(1):35-38. PMC: 6384391. DOI: 10.21037/jtd.2018.12.47. View

15.

Humbert O, Cadour N, Paquet M, Schiappa R, Poudenx M, Chardin D . FDG PET/CT in the early assessment of non-small cell lung cancer response to immunotherapy: frequency and clinical significance of atypical evolutive patterns. Eur J Nucl Med Mol Imaging. 2019; 47(5):1158-1167. DOI: 10.1007/s00259-019-04573-4. View

16.

Chardin D, Paquet M, Schiappa R, Darcourt J, Bailleux C, Poudenx M . 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. J Immunother Cancer. 2020; 8(2). PMC: 7380842. DOI: 10.1136/jitc-2020-000645. View

17.

Castello A, Carbone F, Rossi S, Monterisi S, Federico D, Toschi L . Circulating Tumor Cells and Metabolic Parameters in NSCLC Patients Treated with Checkpoint Inhibitors. Cancers (Basel). 2020; 12(2). PMC: 7072667. DOI: 10.3390/cancers12020487. View

18.

Herbst R, Giaccone G, de Marinis F, Reinmuth N, Vergnenegre A, Barrios C . Atezolizumab for First-Line Treatment of PD-L1-Selected Patients with NSCLC. N Engl J Med. 2020; 383(14):1328-1339. DOI: 10.1056/NEJMoa1917346. View

19.

Tazdait M, Mezquita L, Lahmar J, Ferrara R, Bidault F, Ammari S . Patterns of responses in metastatic NSCLC during PD-1 or PDL-1 inhibitor therapy: Comparison of RECIST 1.1, irRECIST and iRECIST criteria. Eur J Cancer. 2017; 88:38-47. DOI: 10.1016/j.ejca.2017.10.017. View

20.

Reck M, Rodriguez-Abreu D, Robinson A, Hui R, Csoszi T, Fulop A . Pembrolizumab versus Chemotherapy for PD-L1-Positive Non-Small-Cell Lung Cancer. N Engl J Med. 2016; 375(19):1823-1833. DOI: 10.1056/NEJMoa1606774. View