{
    "abstract": "Staging of non-small cell lung cancer (NSCLC) is commonly based on [\nRetrospective evaluation of 235 patients with histologically proven, locally advanced NSCLC from the multi-centre randomized clinical PETPLAN trial and a clinical cohort from a hospital registry. The PET parameters SUVmax, SULpeak, MTV and TLG above liver background uptake were determined. Kaplan-Meier curves and stratified Cox proportional hazard regression models were used to investigate the prognostic value of PET parameters and TNM along with clinical variables. Subgroup analyses were performed to compare hazard ratios according to TNM, MTV, and the two variables combined.\nIn the multivariable Cox regression analysis, MTV was associated with significantly worse overall survival independent of stage and other prognostic variables. In locally advanced disease stages treated with chemoradiotherapy, higher MTV was significantly associated with worse survival (median 17 vs. 32 months). Using simple cut-off values (45\u00a0ml for stage IIIa, 48\u00a0ml for stage IIIb, and 105\u00a0ml for stage IIIc), MTV was able to further predict differences in survival for stages IIIa-c. The combination of TNM and MTV staging system showed better discrimination for overall survival in locally advanced disease stages, compared to TNM alone.\nHigher metabolic tumor volume is significantly associated with worse overall survival and combined with TNM staging, it provides more precise information about the disease prognosis in locally advanced NSCLC treated with chemoradiotherapy compared to TNM alone. As a PET parameter with volumetric information, MTV represents a useful addition to TNM.",
    "authors": [
        {
            "affiliation": "Department of Translational Imaging in Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstra\u00dfe 74, Dresden, 01307, Germany. alexander.brose@radiol.med.uni-giessen.de.\nGerman Cancer Research Center (DKFZ), Heidelberg, Germany. alexander.brose@radiol.med.uni-giessen.de.\nHelmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany. alexander.brose@radiol.med.uni-giessen.de.\nDepartment of Diagnostic and Interventional Radiology, University Hospital Giessen, Justus Liebig University, Klinikstrasse 33, Giessen, 35392, Germany. alexander.brose@radiol.med.uni-giessen.de.\nMember of the German Center for Lung Research (DZL), Giessen, Germany. alexander.brose@radiol.med.uni-giessen.de.",
            "firstname": "Alexander",
            "initials": "A",
            "lastname": "Brose"
        },
        {
            "affiliation": "Department of Nuclear Medicine, University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany.",
            "firstname": "Isabelle",
            "initials": "I",
            "lastname": "Miederer"
        },
        {
            "affiliation": "Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany.",
            "firstname": "Jochem",
            "initials": "J",
            "lastname": "K\u00f6nig"
        },
        {
            "affiliation": "Department of Radiation Oncology, University Hospital Bonn, Bonn, Germany.\nDepartment of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany.",
            "firstname": "Eleni",
            "initials": "E",
            "lastname": "Gkika"
        },
        {
            "affiliation": "Institute of Medical Biometry and Statistics (IMBI), Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.",
            "firstname": "J\u00f6rg",
            "initials": "J",
            "lastname": "Sahlmann"
        },
        {
            "affiliation": "Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany.",
            "firstname": "Tanja",
            "initials": "T",
            "lastname": "Schimek-Jasch"
        },
        {
            "affiliation": "Department of Nuclear Medicine, University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany.",
            "firstname": "Mathias",
            "initials": "M",
            "lastname": "Schreckenberger"
        },
        {
            "affiliation": "Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany.\nDepartment of Radiation Oncology, Kliniken Maria Hilf, M\u00f6nchengladbach, Germany.",
            "firstname": "Ursula",
            "initials": "U",
            "lastname": "Nestle"
        },
        {
            "affiliation": "Department of Pulmonary Medicine, Theresienkrankenhaus, Mannheim, Germany.\nDepartment of Internal Medicine/ Pulmonary Medicine, Catholic Hospital Koblenz-Montabaur, Koblenz, Germany.",
            "firstname": "Jutta",
            "initials": "J",
            "lastname": "Kappes"
        },
        {
            "affiliation": "Department of Translational Imaging in Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstra\u00dfe 74, Dresden, 01307, Germany.\nGerman Cancer Research Center (DKFZ), Heidelberg, Germany.\nHelmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.\nDepartment of Nuclear Medicine, University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany.",
            "firstname": "Matthias",
            "initials": "M",
            "lastname": "Miederer"
        }
    ],
    "conclusions": "Higher metabolic tumor volume is significantly associated with worse overall survival and combined with TNM staging, it provides more precise information about the disease prognosis in locally advanced NSCLC treated with chemoradiotherapy compared to TNM alone. As a PET parameter with volumetric information, MTV represents a useful addition to TNM.",
    "copyrights": "\u00a9 2024. The Author(s).",
    "doi": "10.1186/s40644-024-00811-7",
    "journal": "Cancer imaging : the official publication of the International Cancer Imaging Society",
    "keywords": [
        "Lung cancer",
        "Metabolic tumor volume",
        "NSCLC",
        "PET/CT",
        "Prognosis",
        "TNM"
    ],
    "methods": null,
    "publication_date": "2024-12-22",
    "pubmed_id": "39709461\n34481037\n26277100\n36307040\n36252995\n30280658\n32171429\n36859341\n29876620\n33573333\n30389239\n28125698\n30887722\n26727114\n25193652\n27645692\n31612416\n28785842\n26295651\n28265739\n29882161\n21946983\n36226146\n34922117\n35847839\n24990401\n30853810\n31758225\n30207286\n29759331\n32056506\n29391907\n26909647\n37198668\n16085592\n31818695\n25936471\n22446512\n25569120\n37202226\n19403881",
    "results": "In the multivariable Cox regression analysis, MTV was associated with significantly worse overall survival independent of stage and other prognostic variables. In locally advanced disease stages treated with chemoradiotherapy, higher MTV was significantly associated with worse survival (median 17 vs. 32 months). Using simple cut-off values (45\u00a0ml for stage IIIa, 48\u00a0ml for stage IIIb, and 105\u00a0ml for stage IIIc), MTV was able to further predict differences in survival for stages IIIa-c. The combination of TNM and MTV staging system showed better discrimination for overall survival in locally advanced disease stages, compared to TNM alone.",
    "title": "Prognostic value of metabolic tumor volume on [",
    "xml": "<Element 'PubmedArticle' at 0x78850373e660>"
}