CA-125 glycovariant assays enhance diagnostic sensitivity in the detection of epithelial ovarian cancer

This is the first study describing the clinical performance of GLYVAR Ovarian I and II assays in ovarian cancer diagnostics. The results indicate that the CA-125 glycovariant assays have remarkable potential to improve ovarian cancer diagnostics.

Authors

Institutions

Publication Details

Journal
Clinical Chemistry and Laboratory Medicine (CCLM)
Published
2025-09-18
DOI
https://doi.org/10.1515/cclm-2025-0561
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CA-125 glycovariant assays enhance diagnostic sensitivity in the detection of epithelial ovarian cancer

Sabine Kasimir‐Bauer, Paul Buderath, Kaisa Huhtinen, Rainer Kimmig et al.
Clinical Chemistry and Laboratory Medicine (CCLM)
Ovarian cancer diagnosis and treatment
article

CA-125 glycovariant assays enhance diagnostic sensitivity in the detection of epithelial ovarian cancer

Sabine Kasimir‐Bauer, Paul Buderath, Kaisa Huhtinen, Rainer Kimmig, Stefanos Ioannis Moukas, Katri Kuningas, M Helle, Leena Kokko
article en

Abstract

This is the first study describing the clinical performance of GLYVAR Ovarian I and II assays in ovarian cancer diagnostics. The results indicate that the CA-125 glycovariant assays have remarkable potential to improve ovarian cancer diagnostics.

Clinical Chemistry and Laboratory Medicine (CCLM)Vol. 64(1)
University of Turku (FI), University of Duisburg-Essen (DE)
Openalex Percentile: Top 67%
Ovarian cancer diagnosis and treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.