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Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry

PURPOSE: Sarcomas are a heterogeneous group of malignant neoplasms with a wide range of histological types and occur in almost any anatomic site and side. This study evaluated the prognostic factors in sarcoma patients based on German clinical cancer registry data. METHODS: The German clinical cance...

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Autores principales: Müller, Jörg Andreas, Delank, Karl-Stefan, Laudner, Kevin, Wittenberg, Ian, Zeh, Alexander, Vordermark, Dirk, Medenwald, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657284/
https://www.ncbi.nlm.nih.gov/pubmed/37750956
http://dx.doi.org/10.1007/s00432-023-05350-5
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author Müller, Jörg Andreas
Delank, Karl-Stefan
Laudner, Kevin
Wittenberg, Ian
Zeh, Alexander
Vordermark, Dirk
Medenwald, Daniel
author_facet Müller, Jörg Andreas
Delank, Karl-Stefan
Laudner, Kevin
Wittenberg, Ian
Zeh, Alexander
Vordermark, Dirk
Medenwald, Daniel
author_sort Müller, Jörg Andreas
collection PubMed
description PURPOSE: Sarcomas are a heterogeneous group of malignant neoplasms with a wide range of histological types and occur in almost any anatomic site and side. This study evaluated the prognostic factors in sarcoma patients based on German clinical cancer registry data. METHODS: The German clinical cancer register of Saxony-Anhalt was used for all data analyses. Sarcoma cases of all clinical or pathological T-stages (T1a–T4c), all N-stages (N0-3) and M-stages (0–1b) corresponding to the Union for International Cancer Control (UICC) stages I to IVB were considered. In our analyses, 787 cases diagnosed between 2005 and 2022 were included. Further, we assessed the association of cancer-related parameters with mortality and hazard ratios (HR) from the Cox proportional hazard models. We included sex, age at diagnosis, histological grade, T-, N- and M-stages, tumor size, tumor localization and tumor side as parameters in our regression models. RESULTS: The majority of sarcoma patients were diagnosed with leiomyosarcoma (12%), liposarcoma (11%), angiosarcoma (5.3%) and myxofibrosarcoma (2.7%). In our univariate regression models, tumors localized in more than one location, head, face and neck region as well as the pelvis and lower extremity were associated with increased mortality risk (more than one location: HR 7.10, 95% CI 2.20–22.9; head, face and neck: HR 1.35, 95% CI 0.89–2.06; pelvis: HR 1.27, 95% CI 0.86–1.89; lower extremity: HR 1.44, 95% CI 1.05–1.96). Higher histological grades, UICC-grades and TNM-stages were related to a higher mortality risk. Differing histological subtypes had significant influence on overall survival and progression-free survival. Patients diagnosed with fibromyxoid sarcoma, rhabdomyosarcoma and angiosarcoma were related to higher mortality risk compared to other histological subtypes (fibromyxoid sarcoma: HR 5.2, 95% CI 0.71–38.1; rhabdomyosarcoma: HR 2.93, 95% CI 1.44–6.00; angiosarcoma: HR 1.07, 95% CI 0.53–2.18). CONCLUSIONS: Histological grade, tumor size, nodal and distant metastasis, tumor localization and histological subtype were determined as prognostic factors in terms of survival.
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spelling pubmed-106572842023-09-26 Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry Müller, Jörg Andreas Delank, Karl-Stefan Laudner, Kevin Wittenberg, Ian Zeh, Alexander Vordermark, Dirk Medenwald, Daniel J Cancer Res Clin Oncol Research PURPOSE: Sarcomas are a heterogeneous group of malignant neoplasms with a wide range of histological types and occur in almost any anatomic site and side. This study evaluated the prognostic factors in sarcoma patients based on German clinical cancer registry data. METHODS: The German clinical cancer register of Saxony-Anhalt was used for all data analyses. Sarcoma cases of all clinical or pathological T-stages (T1a–T4c), all N-stages (N0-3) and M-stages (0–1b) corresponding to the Union for International Cancer Control (UICC) stages I to IVB were considered. In our analyses, 787 cases diagnosed between 2005 and 2022 were included. Further, we assessed the association of cancer-related parameters with mortality and hazard ratios (HR) from the Cox proportional hazard models. We included sex, age at diagnosis, histological grade, T-, N- and M-stages, tumor size, tumor localization and tumor side as parameters in our regression models. RESULTS: The majority of sarcoma patients were diagnosed with leiomyosarcoma (12%), liposarcoma (11%), angiosarcoma (5.3%) and myxofibrosarcoma (2.7%). In our univariate regression models, tumors localized in more than one location, head, face and neck region as well as the pelvis and lower extremity were associated with increased mortality risk (more than one location: HR 7.10, 95% CI 2.20–22.9; head, face and neck: HR 1.35, 95% CI 0.89–2.06; pelvis: HR 1.27, 95% CI 0.86–1.89; lower extremity: HR 1.44, 95% CI 1.05–1.96). Higher histological grades, UICC-grades and TNM-stages were related to a higher mortality risk. Differing histological subtypes had significant influence on overall survival and progression-free survival. Patients diagnosed with fibromyxoid sarcoma, rhabdomyosarcoma and angiosarcoma were related to higher mortality risk compared to other histological subtypes (fibromyxoid sarcoma: HR 5.2, 95% CI 0.71–38.1; rhabdomyosarcoma: HR 2.93, 95% CI 1.44–6.00; angiosarcoma: HR 1.07, 95% CI 0.53–2.18). CONCLUSIONS: Histological grade, tumor size, nodal and distant metastasis, tumor localization and histological subtype were determined as prognostic factors in terms of survival. Springer Berlin Heidelberg 2023-09-26 2023 /pmc/articles/PMC10657284/ /pubmed/37750956 http://dx.doi.org/10.1007/s00432-023-05350-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Müller, Jörg Andreas
Delank, Karl-Stefan
Laudner, Kevin
Wittenberg, Ian
Zeh, Alexander
Vordermark, Dirk
Medenwald, Daniel
Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry
title Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry
title_full Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry
title_fullStr Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry
title_full_unstemmed Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry
title_short Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry
title_sort clinical characteristics of sarcoma patients: a population-based data analysis from a german clinical cancer registry
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657284/
https://www.ncbi.nlm.nih.gov/pubmed/37750956
http://dx.doi.org/10.1007/s00432-023-05350-5
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