ArticleJournal of clinical medicine2020
Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers.
Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Sample-Treatment with the Virucidal β-Propiolactone Does Not Preclude Analysis by Large Panel Affinity Proteomics, Including the Discovery of Biomarker Candidates.Analytical chemistry · 2024Article
- Toward ovarian cancer screening with protein biomarkers using dried, self-sampled cervico-vaginal fluid.iScience · 2024Article
- Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer.Cancers · 2022Article
- Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment.Communications medicine · 2022Article
- Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer.Cancers · 2021Article
- Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers.Proteomes · 2021Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
Ovarian cancer is the most lethal gynecologic cancer. Pre-diagnostic testing lacks sensitivity and specificity, and surgery is often the only way to secure the diagnosis. Exploring new biomarkers is of great importance, but the rationale of combining validated well-established biomarkers and algorithms could be a more effective way forward. We hypothesized that we can improve differential diagnostics and reduce false positives by combining (a) risk of malignancy index (RMI) with serum HE4, (b) risk of ovarian malignancy algorithm (ROMA) with a transvaginal ultrasound score or (c) adding HE4 to CA125 in a simple algorithm. With logistic regression modeling, new algorithms were explored and validated using leave-one-out cross validation. The analyses were performed in an existing cohort prospectively collected prior to surgery, 2013-2016. A total of 445 benign tumors and 135 ovarian cancers were included. All presented models improved specificity at cut-off compared to the original algorithm, and goodness of fit was significant (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.