Liver function indicators in patients with breast cancer before and after detection of hepatic metastases-a retrospective study.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 09 05 2022
accepted: 16 11 2022
entrez: 3 3 2023
pubmed: 4 3 2023
medline: 8 3 2023
Statut: epublish

Résumé

Liver metastases are common in patients with breast cancer, and determining the factors associated with such metastases may improve both their early detection and treatment. Given that liver function protein level changes in these patients have not been determined, the aim of our study was to investigate liver function protein level changes over time, spanning 6 months before the detection of liver metastasis to 12 months after. We retrospectively studied 104 patients with hepatic metastasis from breast cancer who were treated at the Departments of Internal Medicine I and the Department of Obstetrics and Gynecology at the Medical University of Vienna between 1980 and 2019. Data were extracted from patient records. Aspartate aminotransferase, alanine aminotransferase, gamma-glutamyltransferase, lactate dehydrogenase and alkaline phosphatase were significantly elevated when compared to normal range 6 months before the detection of liver metastases (p<0.001) Albumin was decreased (p<0.001). The values of aspartate aminotransferase, gamma-glutamyltransferase, and lactate dehydrogenase were significantly increased at the time of diagnosis compared to 6 months prior (p<0.001). Patient- and tumor-specific parameters had no influence on these liver function indicators. Elevated aspartate aminotransferase (p = 0.002) and reduced albumin (p = 0.002) levels at the time of diagnosis were associated with shorter overall survival. Liver function protein levels should be considered as potential indicators when screening for liver metastasis in patients with breast cancer. With the new treatment options available, it could lead to prolonged life.

Sections du résumé

BACKGROUND
Liver metastases are common in patients with breast cancer, and determining the factors associated with such metastases may improve both their early detection and treatment. Given that liver function protein level changes in these patients have not been determined, the aim of our study was to investigate liver function protein level changes over time, spanning 6 months before the detection of liver metastasis to 12 months after.
METHODS
We retrospectively studied 104 patients with hepatic metastasis from breast cancer who were treated at the Departments of Internal Medicine I and the Department of Obstetrics and Gynecology at the Medical University of Vienna between 1980 and 2019. Data were extracted from patient records.
RESULTS
Aspartate aminotransferase, alanine aminotransferase, gamma-glutamyltransferase, lactate dehydrogenase and alkaline phosphatase were significantly elevated when compared to normal range 6 months before the detection of liver metastases (p<0.001) Albumin was decreased (p<0.001). The values of aspartate aminotransferase, gamma-glutamyltransferase, and lactate dehydrogenase were significantly increased at the time of diagnosis compared to 6 months prior (p<0.001). Patient- and tumor-specific parameters had no influence on these liver function indicators. Elevated aspartate aminotransferase (p = 0.002) and reduced albumin (p = 0.002) levels at the time of diagnosis were associated with shorter overall survival.
CONCLUSION
Liver function protein levels should be considered as potential indicators when screening for liver metastasis in patients with breast cancer. With the new treatment options available, it could lead to prolonged life.

Identifiants

pubmed: 36867604
doi: 10.1371/journal.pone.0278454
pii: PONE-D-22-13541
pmc: PMC9983906
doi:

Substances chimiques

gamma-Glutamyltransferase EC 2.3.2.2
Albumins 0
Aspartate Aminotransferases EC 2.6.1.1
L-Lactate Dehydrogenase EC 1.1.1.27

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0278454

Informations de copyright

Copyright: © 2023 Leser et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Carmen Leser (C)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

Georg Dorffner (G)

Section for Artificial Intelligence and Decision Support, Medical University of Vienna, Vienna, Austria.

Maximilian Marhold (M)

Medical University of Vienna Department of Medicine I, Clinical Division of Oncology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.

Anemone Rutter (A)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

Mert Döger (M)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

Christian Singer (C)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

Deirdre Maria König-Castillo (DM)

Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.

Christine Deutschmann (C)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

Iris Holzer (I)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

Daniel König-Castillo (D)

Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.

Daphne Gschwantler-Kaulich (D)

Department of Obstetrics and Gynecology, Cancer Comprehensive Center, Medical University of Vienna, Vienna, Austria.

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Classifications MeSH