ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2020
Biomarkers and Strategies for Early Detection of Ovarian Cancer.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
58 citing papers in PubMed, 1 synthesis or guideline pooled it, 110 citations in OpenAlex.
- Ultra-radical (extensive) surgery versus standard surgery for the primary cytoreduction of advanced epithelial ovarian cancer.The Cochrane database of systematic reviews · 2022Pooled it
- DNA methylation biomarkers for early detection of ovarian cancer.Molecular biology reports · 2026Review
- Multi-Omics Profiling in a Symptomatic Cohort Identifies Coordinated Biomarker Signatures in Ovarian Cancer Serum.Diagnostics (Basel, Switzerland) · 2026Article
- Deep neural architecture empowered by explainable artificial intelligence for accurate and early diagnosis of gynaecological cancer using medical images.Scientific reports · 2026Article
- Ensemble machine learning algorithms leveraged on serum proteomics for enhanced early detection of ovarian cancer.Scientific reports · 2026Article
- Circulating Tumor DNA in Ovarian Cancer: Emerging Roles in Early Detection, Risk Stratification, and Disease Monitoring.Cancers · 2026Review
- Disposable electrochemical panel immunosensing systems for the simultaneous detection of potential biomarkers of ovarian cancer.Mikrochimica acta · 2026Article
- Global, regional, and national burden of ovarian cancer due to high BMI, 1990-2021 and projections to 2050: a systematic analysis based on the global burden of disease 2021 study.Frontiers in nutrition · 2026Article
- A cross-validated deep learning framework for automated detection of DMBA-induced ovarian cancer from histopathological images with CA-125 biomarker support.Frontiers in artificial intelligence · 2026Article
- Ovarian Tumor Biomarkers: Correlation Between Tumor Type and Marker Expression, and Their Role in Guiding Therapeutic Strategies.International journal of molecular sciences · 2025Review
- Machine-Learning-Assisted Analysis of Patient Clinical Biomarkers to Improve Ovarian Cancer Diagnosis.Precision chemistry · 2025Article
- Exhausted and Senescent CD4Diagnostics (Basel, Switzerland) · 2025Article
- Multi-analyte approach combining cfDNA sequencing and protein testing for early ovarian cancer detection.iScience · 2025Article
- Sensitivity Measures in Studies of Cancer Early Detection Biomarkers.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Article
- A comprehensive overview of ovarian cancer stem cells: correlation with high recurrence rate, underlying mechanisms, and therapeutic opportunities.Molecular cancer · 2025Review
- Long-term trends and projections of ovarian cancer burden in China (1990 to 2040): an age-period-cohort analysis based on GBD 2021 data.Frontiers in oncology · 2025Article
- Multiplexed Biomarker Detection Using DNA Payloads: Design, Assembly, and Analysis.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Folate Receptor Alpha-A Secret Weapon in Ovarian Cancer Treatment?International journal of molecular sciences · 2024Review
- Automated early ovarian cancer detection system based on bioinformatics.Scientific reports · 2024Article
- Diagnostic Utility of Selected Matrix Metalloproteinases (MMP-2, MMP-3, MMP-11, MMP-26), HE4, CA125 and ROMA Algorithm in Diagnosis of Ovarian Cancer.International journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
Early detection of ovarian cancer remains an important unmet medical need. Effective screening could reduce mortality by 10%-30%. Used individually, neither serum CA125 nor transvaginal sonography (TVS) is sufficiently sensitive or specific. Two-stage strategies have proven more effective, where a significant rise above a woman's baseline CA125 prompts TVS and an abnormal sonogram prompts surgery. Two major screening trials have documented that this strategy has adequate specificity, but sensitivity for early-stage (I-II) disease must improve to have a greater impact on mortality. To improve the first stage, different panels of protein biomarkers have detected cases missed by CA125. Autoantibodies against TP53 have detected 20% of early-stage ovarian cancers 8 months before elevation of CA125 and 22 months before clinical diagnosis. Panels of autoantibodies and antigen-autoantibody complexes are being evaluated with the goal of detecting >90% of early-stage ovarian cancers, alone or in combination with CA125, while maintaining 98% specificity in control subjects. Other biomarkers, including micro-RNAs, ctDNA, methylated DNA, and combinations of ctDNA alterations, are being tested to provide an optimal first-stage test. New technologies are also being developed with greater sensitivity than TVS to image small volumes of tumor.
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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.