Background: Post-diagnosis weight gain in breast cancer patients has been associated with increased cancer recurrence and mortality. Our study was designed to identify risk factors for this weight gain and create a predictive model to identify a high-risk population for targeted interventions.
Methods: Chart review was conducted on 459 breast cancer patients from Northwestern Robert H. Lurie Cancer Centre to obtain weights and body mass indices (BMIs) over an 18-month period from diagnosis. We also recorded tumour characteristics, demographics, clinical factors, and treatment regimens. Blood samples were genotyped for 14 single-nucleotide polymorphisms (SNPs) in fat mass and obesity-associated protein (FTO) and adiponectin pathway genes (ADIPOQ and ADIPOR1).
Results: In all, 56% of patients had >0.5 kg m(-2) increase in BMI from diagnosis to 18 months, with average BMI and weight gain of 1.9 kg m(-2) and 5.1 kg, respectively. Our best predictive model was a primarily SNP-based model incorporating all 14 FTO and adiponectin pathway SNPs studied, their epistatic interactions, and age and BMI at diagnosis, with area under receiver operating characteristic curve of 0.85 for 18-month weight gain.
Conclusion: We created a powerful risk prediction model that can identify breast cancer patients at high risk for weight gain.