What question did this study set out to answer?

To evaluate a polygenic risk integrated clinical model for ovarian cancer prediction.

November 11, 2025Cancer Prevention ResearchOpen Access

Validation of a clinical and polygenic risk prediction model for ovarian cancer in the Nurses’ Health Study

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Authors

KPKrishna Patel GDGillian S. Dite ESErika L. Spaeth

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Implication

Validation demonstrates improved risk stratification for ovarian cancer, indicating that polygenic risk scores may enhance targeted prevention efforts.

Key Points

To evaluate a polygenic risk integrated clinical model for ovarian cancer prediction.
Cross-validated a polygenic risk model in a nested case-control population
Compared refined risk model with clinical and polygenic risk score models
Calculated odds ratios and AUCs for each model
Odds ratios per standard deviation were 1.26 for refined risk model
Corresponding AUCs were 0.56 for refined risk model
Population screening showed stage shifting but unclear mortality benefit

Cite This Study

Patel et al. (2025) studied this question.

synapsesocial.com/papers/69252e9ec0ce034ddc356492 https://doi.org/10.1158/1940-6207.capr-24-0528

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Implication

Validation demonstrates improved risk stratification for ovarian cancer, indicating that polygenic risk scores may enhance targeted prevention efforts.

Validation of a clinical and polygenic risk prediction model for ovarian cancer in the Nurses’ Health Study

Discussion

Member takes

Implication

Key Points

Cite This Study

Validation of a clinical and polygenic risk prediction model for ovarian cancer in the Nurses’ Health Study

Discussion

Member takes

Implication

Key Points

Cite This Study

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