PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Tokarz, J. ; Adamski, J. ; Rižner, T.L.*

Metabolomics for diagnosis and prognosis of uterine diseases? A systematic review.

J. Pers. Med. 10:294 (2020)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
4.433
1.306
5
9
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Adenomyosis ; Algorithms ; Biomarker ; Biomarker Discovery ; Cervical Cancer ; Endometrial Cancer ; Endometriosis ; Leiomyoma ; Omics ; Uterine Fibroids; Cervical Intraepithelial Neoplasia; Quality-of-life; Endometrial Cancer; Ovarian Endometriosis; Current Management; Mass-spectrometry; Peritoneal-fluid; Biomarkers; Adenomyosis; Plasma
Sprache englisch
Veröffentlichungsjahr 2020
HGF-Berichtsjahr 2020
ISSN (print) / ISBN 2075-4426
e-ISSN 2075-4426
Zeitschrift Journal of Personalized Medicine
Quellenangaben Band: 10, Heft: 4, Seiten: , Artikelnummer: 294 Supplement: ,
Verlag MDPI
Verlagsort Basel, Switzerland
Begutachtungsstatus Peer reviewed
Institut(e) Molekulare Endokrinologie und Metabolismus (MEM)
POF Topic(s) 30201 - Metabolic Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-505600-003
Förderungen DAAD
Federal Ministry for Education and Research (BMBF), Germany
ERA-NET Transcan2 BioEndoCar project - Ministry of Education, Science and Sport Slovenia
Slovenian Research Agency
DOI 10.3390/jpm10040294
WOS ID WOS:000602203800001
Scopus ID 85098576318
PubMed ID 33371433
Erfassungsdatum 2021-02-06
[➜Korrektur melden]