ArticleAmerican journal of epidemiology2025
Ovarian cancer risk prediction: a clinical epidemiology perspective.
Article in American journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Review
- Oophorectomy-Corrected Ovarian Cancer Incidence, Survival, and Mortality by Subtype, Race, Ethnicity.Cancer medicine · 2026Article
- Integrated study reveals molecular mechanisms by which bisphenol A promotes ovarian cancer.iScience · 2026Article
- Improving ovarian cancer risk assessment using a machine learning model developed on data from the Prostate Lung Colorectal Ovarian Cancer Screening Trial.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2026Article
- A lasso-based model combining miRNA and clinical variables predicts future risk of breast and ovarian cancer.Scientific reports · 2026Article
- Review
- A Preoperative Nomogram Integrating Clinical and Ultrasonic Features to Predict Extra-Pelvic Metastasis in Ovarian Cancer: A Multicenter Retrospective Study.International journal of women's health · 2026Article
- Natural compounds targeting glycolysis and TME in ovarian cancer: from metabolic crosstalk to therapeutic potential.Frontiers in pharmacology · 2026Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Ovarian cancer is a rare and highly heterogeneous disease usually detected at late stages when outcomes are poor. Population-based screening approaches have not been successful at reducing ovarian cancer mortality, but preventive bilateral salpingo-oophorectomy is highly effective at preventing ovarian cancer in high-risk populations. Ovarian cancer risk prediction models may allow identification of populations at increased risk of ovarian cancer for preventive interventions or targeted early detection. We propose a life-course approach to ovarian cancer risk prediction based on the time at which a risk model should be applied and the risk factors that are available. The discriminative ability of ovarian cancer risk prediction models published so far is limited, with areas under the curve ranging from 0.58 to 0.65 for different combinations of risk factors and genetic susceptibility markers. Currently proposed absolute risk thresholds for preventive surgery are around 4% lifetime risk. The absolute risk predicted by ovarian cancer risk models ranges from 0.6% to 2.5% lifetime risk in the general population, highlighting the need to improve ovarian cancer risk prediction models and evaluating new preventive approaches that can be offered to individuals at lower risk.
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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.