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Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value

SIMPLE SUMMARY: Sarcoma is a rare cancer originating in soft tissue or bone. Prognostic models are used to modify therapy and improve survival. The present study aimed to evaluate if the combination of PET parameters and circulating biomarkers can improve the prognostic accuracy. When PET parameters...

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Autores principales: Pedersen, Mette Abildgaard, Baad-Hansen, Thomas, Gormsen, Lars C., Bærentzen, Steen, Sandfeld-Paulsen, Birgitte, Aggerholm-Pedersen, Ninna, Vendelbo, Mikkel Holm
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913525/
https://www.ncbi.nlm.nih.gov/pubmed/36765774
http://dx.doi.org/10.3390/cancers15030816
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author Pedersen, Mette Abildgaard
Baad-Hansen, Thomas
Gormsen, Lars C.
Bærentzen, Steen
Sandfeld-Paulsen, Birgitte
Aggerholm-Pedersen, Ninna
Vendelbo, Mikkel Holm
author_facet Pedersen, Mette Abildgaard
Baad-Hansen, Thomas
Gormsen, Lars C.
Bærentzen, Steen
Sandfeld-Paulsen, Birgitte
Aggerholm-Pedersen, Ninna
Vendelbo, Mikkel Holm
author_sort Pedersen, Mette Abildgaard
collection PubMed
description SIMPLE SUMMARY: Sarcoma is a rare cancer originating in soft tissue or bone. Prognostic models are used to modify therapy and improve survival. The present study aimed to evaluate if the combination of PET parameters and circulating biomarkers can improve the prognostic accuracy. When PET parameters were added to the existing models, the prognostic value increased in all models. A new prognostic model (SBSpib), including the biomarkers albumin, lymphocytes, and one PET parameter, metabolic tumor volume, was developed. SBSpib separates patients into four different groups, where the chance of survival increases with decreasing scores. Overall, combining PET parameters and circulating biomarkers improves the prognostic value. However, SBSpib must be validated before implementation. ABSTRACT: Sarcomas are rare and have a high mortality rate. Further prognostic classification, with readily available parameters, is warranted, and several studies have examined circulating biomarkers and PET parameters separately. This single-site, retrospective study aimed to examine the prognostic values of several scoring systems in combination with PET parameters. We included 148 patients with sarcoma, who were treated and scanned at Aarhus University Hospital from 1 January 2016 to 31 December 2019. The Akaike information criterion and Harrell’s concordance index were used to evaluate whether the PET parameters added prognostic information to existing prognostic models using circulating biomarkers. Of the PET parameters, metabolic tumor volume (MTV) performed best, and when combined with the existing prognostic models, the prognostic value improved in all models. Backward stepwise selection was used to create a new model, SBSpib, which included albumin, lymphocytes, and one PET parameter, MTV. It has scores ranging from zero to three and increasing hazard ratios; HR = 4.83 (1.02–22.75) for group one, HR = 7.40 (1.6–33.42) for group two, and HR = 17.32 (3.45–86.93) for group three. Consequently, implementing PET parameters in prognostic models improved the prognostic value. SBSpib is a new prognostic model that includes both circulating biomarkers and PET parameters; however, validation in another sarcoma cohort is warranted.
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spelling pubmed-99135252023-02-11 Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value Pedersen, Mette Abildgaard Baad-Hansen, Thomas Gormsen, Lars C. Bærentzen, Steen Sandfeld-Paulsen, Birgitte Aggerholm-Pedersen, Ninna Vendelbo, Mikkel Holm Cancers (Basel) Article SIMPLE SUMMARY: Sarcoma is a rare cancer originating in soft tissue or bone. Prognostic models are used to modify therapy and improve survival. The present study aimed to evaluate if the combination of PET parameters and circulating biomarkers can improve the prognostic accuracy. When PET parameters were added to the existing models, the prognostic value increased in all models. A new prognostic model (SBSpib), including the biomarkers albumin, lymphocytes, and one PET parameter, metabolic tumor volume, was developed. SBSpib separates patients into four different groups, where the chance of survival increases with decreasing scores. Overall, combining PET parameters and circulating biomarkers improves the prognostic value. However, SBSpib must be validated before implementation. ABSTRACT: Sarcomas are rare and have a high mortality rate. Further prognostic classification, with readily available parameters, is warranted, and several studies have examined circulating biomarkers and PET parameters separately. This single-site, retrospective study aimed to examine the prognostic values of several scoring systems in combination with PET parameters. We included 148 patients with sarcoma, who were treated and scanned at Aarhus University Hospital from 1 January 2016 to 31 December 2019. The Akaike information criterion and Harrell’s concordance index were used to evaluate whether the PET parameters added prognostic information to existing prognostic models using circulating biomarkers. Of the PET parameters, metabolic tumor volume (MTV) performed best, and when combined with the existing prognostic models, the prognostic value improved in all models. Backward stepwise selection was used to create a new model, SBSpib, which included albumin, lymphocytes, and one PET parameter, MTV. It has scores ranging from zero to three and increasing hazard ratios; HR = 4.83 (1.02–22.75) for group one, HR = 7.40 (1.6–33.42) for group two, and HR = 17.32 (3.45–86.93) for group three. Consequently, implementing PET parameters in prognostic models improved the prognostic value. SBSpib is a new prognostic model that includes both circulating biomarkers and PET parameters; however, validation in another sarcoma cohort is warranted. MDPI 2023-01-28 /pmc/articles/PMC9913525/ /pubmed/36765774 http://dx.doi.org/10.3390/cancers15030816 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pedersen, Mette Abildgaard
Baad-Hansen, Thomas
Gormsen, Lars C.
Bærentzen, Steen
Sandfeld-Paulsen, Birgitte
Aggerholm-Pedersen, Ninna
Vendelbo, Mikkel Holm
Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value
title Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value
title_full Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value
title_fullStr Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value
title_full_unstemmed Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value
title_short Inclusion of Metabolic Tumor Volume in Prognostic Models of Bone and Soft Tissue Sarcoma Increases the Prognostic Value
title_sort inclusion of metabolic tumor volume in prognostic models of bone and soft tissue sarcoma increases the prognostic value
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913525/
https://www.ncbi.nlm.nih.gov/pubmed/36765774
http://dx.doi.org/10.3390/cancers15030816
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