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Metabolic tumor volume and sites of organ involvement predict outcome in NSCLC immune-checkpoint inhibitor therapy.
Kifjak, Daria; Hochmair, Maximilian; Sobotka, Daniel; Haug, Alexander R; Ambros, Raphael; Prayer, Florian; Heidinger, Benedikt H; Roehrich, Sebastian; Milos, Ruxandra-Iulia; Wadsak, Wolfgang; Fuereder, Thorsten; Krenbek, Dagmar; Fazekas, Andreas; Meilinger, Michael; Mayerhoefer, Marius E; Langs, Georg; Herold, Christian; Prosch, Helmut; Beer, Lucian.
Afiliação
  • Kifjak D; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Radiology, UMass Memorial Medical Center and University of Massachusetts Chan Medical School, Worcester, MA, USA; Christian Doppler Laboratory for Machine Learning Driven Precision
  • Hochmair M; Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria.
  • Sobotka D; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Haug AR; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Ambros R; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Prayer F; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Heidinger BH; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Roehrich S; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Milos RI; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Wadsak W; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomarker Research in Medicine, CBmed, Graz, Austria.
  • Fuereder T; Department of Internal Medicine I & Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.
  • Krenbek D; Department of Pathology and Bacteriology, Klinik Floridsdorf, Brünner Strasse 68, 1210 Vienna, Austria.
  • Fazekas A; Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria.
  • Meilinger M; Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria.
  • Mayerhoefer ME; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Langs G; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna,
  • Herold C; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Prosch H; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria. Electronic address
  • Beer L; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria.
Eur J Radiol ; 170: 111198, 2024 Jan.
Article em En | MEDLINE | ID: mdl-37992608
PURPOSE: The purpose of this study was to assess the ability of pretreatment PET parameters and peripheral blood biomarkers to predict progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with ICIT. METHODS: We prospectively included 87 patients in this study who underwent pre-treatment [18F]-FDG PET/CT. Organ-specific and total metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured using a semiautomatic software. Sites of organ involvement (SOI) were assessed by PET/CT. The log-rank test and Cox-regression analysis were used to assess associations between clinical, laboratory, and imaging parameters with PFS and OS. Time dependent ROC were calculated and model performance was evaluated in terms of its clinical utility. RESULTS: MTV increased with the number of SOI and was correlated with neutrophil and lymphocyte cell count (Spearman's rho = 0.27 or 0.32; p =.02 or 0.003; respectively). Even after adjustment for known risk factors, such as PD-1 expression and neutrophil cell count, the MTV and the number of SOI were independent risk factors for progression (per 100 cm3; adjusted hazard ratio [aHR]: 1.13; 95% confidence interval [95%CI]: 1.01-1.28; p =.04; single SOI vs. ≥ 4 SOI: aHR: 2.26, 95%CI: 1.04-4.94; p =.04). MTV and the number of SOI were independent risk factors for overall survival (per 100 cm3 aHR: 1.11, 95%CI: 1.01-1.23; p =.03; single SOI vs. ≥ 4 SOI: aHR: 4.54, 95%CI: 1.64-12.58; p =.04). The combination of MTV and the number of SOI improved the risk stratification for PFS and OS (log-rank test p <.001; C-index: 0.64 and 0.67). CONCLUSION: The MTV and the number of SOI are simple imaging markers that provide complementary information to facilitate risk stratification in NSCLC patients scheduled for ICIT.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article