Evaluation of the Temporal Muscle Thickness as an Independent Prognostic Biomarker in Patients with Primary Central Nervous System Lymphoma.

overall survival primary central nervous system lymphoma prognostic parameter sarcopenia temporal muscle thickness

Journal

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

Informations de publication

Date de publication:
02 Feb 2021
Historique:
received: 12 12 2020
revised: 19 01 2021
accepted: 20 01 2021
entrez: 5 2 2021
pubmed: 6 2 2021
medline: 6 2 2021
Statut: epublish

Résumé

In this study, we assessed the prognostic relevance of temporal muscle thickness (TMT), likely reflecting patient's frailty, in patients with primary central nervous system lymphoma (PCNSL). In 128 newly diagnosed PCNSL patients TMT was analyzed on cranial magnetic resonance images. Predefined sex-specific TMT cutoff values were used to categorize the patient cohort. Survival analyses, using a log-rank test as well as Cox models adjusted for further prognostic parameters, were performed. The risk of death was significantly increased for PCNSL patients with reduced muscle thickness (hazard ratio of 3.189, 95% CI: 2-097-4.848,

Identifiants

pubmed: 33540564
pii: cancers13030566
doi: 10.3390/cancers13030566
pmc: PMC7867149
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Julia Furtner (J)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Karl-Heinz Nenning (KH)

Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Thomas Roetzer (T)

Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.

Johanna Gesperger (J)

Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.

Lukas Seebrecht (L)

Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.

Michael Weber (M)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Astrid Grams (A)

Department of Neuroradiology, Medical University of Innsbruck, 6020 Innsbruck, Austria.

Stefan L Leber (SL)

Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, 8036 Graz, Austria.

Franz Marhold (F)

Division of Neurosurgery, University Hospital St. Poelten, Karl Landsteiner University of Health Sciences, 3100 St. Poelten, Austria.

Camillo Sherif (C)

Department of Neurosurgery, Krankenanstalt Rudolfstiftung, 1030 Wien, Austria.

Johannes Trenkler (J)

Institute of Neuroradiology, NeuromedCampus, Kepler University Hospital, Johannes Kepler Universität of Linz, 4020 Linz, Austria.

Barbara Kiesel (B)

Department of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.

Georg Widhalm (G)

Department of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.

Ulrika Asenbaum (U)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Ramona Woitek (R)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Anna S Berghoff (AS)

Department of Medicine I, Division of Oncology, Medical University of Vienna, 1090 Vienna, Austria.

Daniela Prayer (D)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Georg Langs (G)

Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.

Matthias Preusser (M)

Department of Medicine I, Division of Oncology, Medical University of Vienna, 1090 Vienna, Austria.

Adelheid Wöhrer (A)

Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.

Classifications MeSH