ArticleNPJ breast cancer2024
A polygenic score associated with fracture risk in breast cancer patients treated with aromatase inhibitors.
Article in NPJ breast cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Polygenic Risk Score as a Predictor of Bone Fracture or Osteoporosis in Prostate Cancer Patients Receiving Androgen Deprivation Therapy.Cancer medicine · 2025Article
- The association between sex hormones and bone mineral density in US females.Scientific reports · 2025Article
- A contemporary review of breast cancer risk factors and the role of artificial intelligence.Frontiers in oncology · 2024Review
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
Abstract
Identifying women at high risk of osteoporotic fracture from aromatase inhibitor (AI) therapy for breast cancer is largely based on known risk factors for healthy postmenopausal women, which might not accurately reflect the risk in breast cancer patients post-AI therapy. To determine whether a polygenic score associated with fracture in healthy women is also significant in women treated with AIs for breast cancer, we used data from a prospective observational cohort of 2152 women diagnosed with hormonal receptor positive breast cancer treated with AIs as the initial endocrine therapy and examined a polygenic score of heel quantitative ultrasound speed of sound (gSOS) in relation to incident osteoporotic fracture after AI therapy during a median 6.1 years of follow up after AI initiation. In multivariable models, patients with the second and third highest tertiles (T) versus the lowest tertile of gSOS had significantly lower risk of fracture (T2: adjusted HR = 0.61, 95% CI: 0.46-0.80; T3: adjusted HR = 0.53, 95% CI: 0.40-0.70). The lower risk of fracture in patients with the highest tertile of gSOS remained significant after further adjustment for BMD at the hip (T3: adjusted HR = 0.62, 95% CI: 0.42-0.91). In conclusion, our analysis showed gSOS as a novel genetic predictor for fracture risk independent of BMD among breast cancer patients treated with AIs. Future studies are warranted to evaluate the performance of incorporating gSOS in prediction models for the risk of AI-related fracture in breast cancer patients.
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Registered trials
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