Ovarian Cancer

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Among 35 patients with ovarian cancer treated with an antibody-based combination, the overall response rate was 23%, with a clinical benefit rate of 31%.
Botensilimab/Balstilimab Exhibits Meaningful Activity in Ovarian Cancer

December 24th 2025

Among 35 patients with ovarian cancer treated with an antibody-based combination, the overall response rate was 23%, with a clinical benefit rate of 31%.

Pooled analysis data from the phase 1 JSKN003-101 and phase 1/2 JSKN003-102 trials support the regulatory decision.
JSKN003 Earns FDA Breakthrough Therapy Designation for HER2-Expressing PROC

December 22nd 2025

Fuzuloparib monotherapy and as a combination with apatinib improved PFS as maintenance therapy in patients with ovarian cancer harboring BRCA1/2 mutations.
Fuzuloparib Maintenance Therapies Improve PFS in Newly Diagnosed Ovarian Cancer

December 17th 2025

Although both immune priming strategies numerically improved ORR and PFS vs olaparib monotherapy, the study was not powered for comparisons between arms.
Immune Priming Strategies Numerically Improve PFS in Ovarian Cancer

November 24th 2025

The median PFS for patients with ovarian cancer who received niraparib maintenance in the real-world setting was 25.7 months.
Real-World Niraparib Efficacy Similar to Phase 3 Data in Ovarian Cancer

November 18th 2025

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Mathematical Modeling for Breast Cancer Risk Assessment

August 1st 2002

Women at increased risk of breast cancer have important opportunities for early detection and prevention. There are, however, serious drawbacks to the available interventions. The magnitude of breast cancer risk is a crucial factor in the optimization of medical benefit when considering the efficacy of risk-reduction methods, the adverse effects of intervention, and economic and quality-of-life outcomes. Breast cancer risk assessment has become increasingly quantitative and is amenable to computerization. The assembly of risk factor information into practical, quantitative models for clinical and scientific use is relatively advanced for breast cancer, and represents a paradigm for broader risk management in medicine. Using a case-based approach, we will summarize the major breast cancer risk assessment models, compare and contrast their utility, and illustrate the role of genetic testing in risk management. Important considerations relevant to clinical oncology practice include the role of risk assessment in cancer prevention, the logistics of implementing risk assessment, the ramifications of conveying risk information with limited genetic counseling, and the mechanisms for genetics referral. Medical professionals can embrace new preventive medicine techniques more effectively by utilizing quantitative methods to assess their patients’ risks. [ONCOLOGY 16:1082-1099, 2002]