Low-dose aspirin and risk of breast cancer: a Norwegian population-based cohort study of one million women.
L Lukas LøflingNathalie C StøerSara NafisiGiske UrsinSolveig HofvindEdoardo BotteriPublished in: European journal of epidemiology (2023)
Several studies evaluated the association between aspirin use and risk of breast cancer (BC), with inconsistent results. We identified women aged ≥ 50 years residing in Norway between 2004 and 2018, and linked data from nationwide registries; including the Cancer Registry of Norway, the Norwegian Prescription Database, and national health surveys. We used Cox regression models to estimate the association between low-dose aspirin use and BC risk, overall and by BC characteristics, women's age and body mass index (BMI), adjusting for sociodemographic factors and use of other medications. We included 1,083,629 women. During a median follow-up of 11.6 years, 257,442 (24%) women used aspirin, and 29,533 (3%) BCs occurred. For current use of aspirin, compared to never use, we found an indication of a reduced risk of oestrogen receptor-positive (ER +) BC (hazard ratio [HR] = 0.96, 95% confidence interval [CI]: 0.92-1.00), but not ER-negative BC (HR = 1.01, 95%CI: 0.90-1.13). The association with ER + BC was only found in women aged ≥ 65 years (HR = 0.95, 95%CI: 0.90-0.99), and became stronger as the duration of use increased (use of ≥ 4 years HR = 0.91, 95%CI: 0.85-0.98). BMI was available for 450,080 (42%) women. Current use of aspirin was associated with a reduced risk of ER + BC in women with BMI ≥ 25 (HR = 0.91, 95%CI: 0.83-0.99; HR = 0.86, 95%CI: 0.75-0.97 for use of ≥ 4 years), but not in women with BMI < 25.Use of low-dose aspirin was associated with reduced risk of ER + BC, in particular in women aged ≥ 65 years and overweight women.
Keyphrases
- low dose
- polycystic ovary syndrome
- body mass index
- pregnancy outcomes
- breast cancer risk
- cervical cancer screening
- high dose
- cardiovascular events
- antiplatelet therapy
- weight gain
- emergency department
- cross sectional
- breast cancer cells
- acute coronary syndrome
- estrogen receptor
- pregnant women
- skeletal muscle
- squamous cell carcinoma
- coronary artery disease
- young adults
- papillary thyroid
- machine learning
- percutaneous coronary intervention
- deep learning
- big data
- atrial fibrillation