Purpose: this study was conducted to assess the impact of AIs on body mass index and high sensitivity as prognostic predictors to be incorporated into point of care technology (POCT) testing in postmenopausal breast cancer women after a 24 month follow up in Africa. An observational cohort study was conducted; including 126 female BC patients with stages ranging from 0-III initially subjected to AIs and subsequently followed up for 24 months. Multiple imputation model was conducted to predict missing data.
Results: Random effects model was used to monitor the changes over the time. The study revealed stronger statistically association between BMI and homocysteine (p = 0.021, 95%CI: 0.0083 to 0.1029). Weight and total body fat were strongly associated after 24 months follow up. Hs-CRP was associated with BMI (p = 0.0001), and hs-CRP was associated with other biomedical markers such as calcium (p = 0.021, 95% CI: 0.01 to 0.10), phosphate (p = 0.039, 95%CI: 0.01 to 0.10), and ferritin (p = 0.002, 95%CI: 0.02 to 0.08) and calcium. The patients subjected to AIs are likely to develop cardiovascular adverse events. POCT of care strategy which include clinical, biomedical and genetic predictor's measurement is required to improve BC survivorship.
Keywords: And multiple imputations; Aromatase inhibitors; Body mass index; High sensitivity C-reactive protein; Postmenopausal breast cancer.
© 2023. The Author(s).