Search: onr:"swepub:oai:DiVA.org:uu-486157" >
Data-driven analysi...
-
Enroth, Stefan,1976-Uppsala universitet,Science for Life Laboratory, SciLifeLab,Kollegiet för avancerade studier (SCAS),Institutionen för immunologi, genetik och patologi,Gyllensten
(author)
Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment
- Article/chapterEnglish2022
Publisher, publication year, extent ...
-
2022-10-01
-
Springer Nature,2022
-
electronicrdacarrier
Numbers
-
LIBRIS-ID:oai:DiVA.org:uu-486157
-
https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-486157URI
-
https://doi.org/10.1038/s43856-022-00193-6DOI
Supplementary language notes
-
Language:English
-
Summary in:English
Part of subdatabase
Classification
-
Subject category:ref swepub-contenttype
-
Subject category:art swepub-publicationtype
Notes
-
These authors contributed equally: Karin Stålberg, Karin Sundfeldt, Ulf Gyllensten
-
BackgroundOvarian cancer is the eighth most common cancer among women and due to late detection prognosis is poor with an overall 5-year survival of 30–50%. Novel biomarkers are needed to reduce diagnostic surgery and enable detection of early-stage cancer by population screening. We have previously developed a risk score based on an 11-biomarker plasma protein assay to distinguish benign tumors (cysts) from malignant ovarian cancer in women with adnexal ovarian mass.MethodsProtein concentrations of 11 proteins were characterized in plasma from 1120 clinical samples with a custom version of the proximity extension assay. The performance of the assay was evaluated in terms of prediction accuracy based on receiver operating characteristics (ROC) and multiple hypothesis adjusted Fisher’s Exact tests on achieved sensitivity and specificity.ResultsThe assay’s performance is validated in two independent clinical cohorts with a sensitivity of 0.83/0.91 and specificity of 0.88/0.92. We also show that the risk score follows the clinical development and is reduced upon treatment, and increased with relapse and cancer progression. Data-driven modeling of the risk score patterns during a 2-year follow-up after diagnosis identifies four separate risk score trajectories linked to clinical development and survival. A Cox proportional hazard regression analysis of 5-year survival shows that at time of diagnosis the risk score is the second-strongest predictive variable for survival after tumor stage, whereas MUCIN-16 (CA-125) alone is not significantly predictive.ConclusionThe robust performance of the biomarker assay across clinical cohorts and the correlation with clinical development indicates its usefulness both in the diagnostic work-up of women with adnexal ovarian mass and for predicting their clinical course.
Subject headings and genre
Added entries (persons, corporate bodies, meetings, titles ...)
-
Ivansson, EmmaUppsala universitet,Science for Life Laboratory, SciLifeLab,Institutionen för immunologi, genetik och patologi(Swepub:uu)emfra062
(author)
-
Hedlund Lindberg, JuliaUppsala universitet,Science for Life Laboratory, SciLifeLab,Medicinsk genetik och genomik(Swepub:uu)julin226
(author)
-
Lycke, Maria
(author)
-
Bergman, Jessica
(author)
-
Reneland, Anna
(author)
-
Stålberg, KarinUppsala universitet,Reproduktiv hälsa(Swepub:uu)kariglim
(author)
-
Sundfeldt, Karin
(author)
-
Gyllensten, UlfUppsala universitet,Science for Life Laboratory, SciLifeLab,Medicinsk genetik och genomik(Swepub:uu)ulfgyll
(author)
-
Uppsala universitetScience for Life Laboratory, SciLifeLab
(creator_code:org_t)
Related titles
-
In:Communications Medicine: Springer Nature2:12730-664X
Internet link
Find in a library
To the university's database