Breast cancer: changes in BMI, an indicator to watch closely

A study looked into changes in Body Mass Index, once breast cancer treatment has been initiated; with surprising results.

Patients' BMI at the time of diagnosis

The study ‘The challenge of weight gain in hormone receptor-positive breast cancer’1 analysed the medical records of 140 patients diagnosed between 2010 and 2020 with early-stage invasive breast cancer, HER-2 negative and RH+ (ER and/or PR). From the start of treatment, disparities in terms of obesity according to ethnic origin were observed. At diagnosis, 55.6% of black patients were obese (BMI ≥30 kg/m²), compared with 30.3% of other patients. Obesity is a major risk factor, and there is evidence that black women have a 40% higher mortality rate from breast cancer than white women, and more than twice that of Asian women2.

Changes in BMI during treatment

Surprisingly, the study results showed that patients who were obese at the time of diagnosis were the most likely to lose weight after diagnosis. Their BMI fell by an average of 0.6 points, and only 31% of obese patients saw their BMI increase by at least 0.1 per year. Conversely, patients with a normal or overweight BMI at the time of diagnosis were more likely to gain weight after treatment. Thus, 71.4% of overweight (but not obese) patients and 45.5% of those with a healthy BMI saw their BMI increase.

Ethnic disparities and risk of recurrence

The study also revealed that black women had a significantly higher risk of recurrence than other ethnic groups (OR 7.21; 95% CI: 1.48-35.09). This risk could be attributed to a number of factors, including access to care, disparities in management, and obesity-related co-morbidities. Indeed, at the time of diagnosis, 55.6% of black patients were obese, compared with 30.3% of other patients, a significant difference (p = 0.034). However, although the interaction between race and obesity was observed, it did not reach statistical significance (p = 0.998). Nevertheless, these results highlight the importance of paying particular attention to specific risk factors in black patients.

Clinical implications: BMI monitoring and weight management strategies

Increase in patients with a normal or overweight BMI at the time of diagnosis highlights the importance of proactive weight management following a breast cancer diagnosis. Another longitudinal epidemiological study3 supports these conclusions, indicating that patients with a healthy BMI, or who are moderately overweight are most at risk of post-diagnosis weight gain. On the other hand, patients who are obese at diagnosis are often the most likely to lose weight, often involuntarily, due to the effects of the disease or treatment.

Furthermore, a secondary analysis of a prospective cohort4 confirmed that 52% of women with stage 0-III HR+ cancer gained clinically significant weight (≥5% of baseline weight) within five years of treatment. This weight gain is often associated with a deterioration in quality of life, particularly after initiation of adjuvant endocrine therapy.

Obesity as a risk factor: a multidimensional approach

In light of these data, it is crucial to rethink weight management strategies for patients with breast cancer. Some options, such as glucagon-like peptide receptor agonists and bariatric surgery, seem promising for managing patients' weight. However, their safety in the post-breast cancer setting needs to be rigorously monitored. Young women diagnosed before the menopause require specific strategies, as their risk of weight gain is particularly high.

Finally, it is important to remember that BMI, although widely used, does not always accurately reflect the distribution of fat and muscle mass. More specific methods of assessing body composition could improve the prediction of outcomes for breast cancer patients.

Sources
  1. The challenge of weight gain in hormone receptor-positive breast cancer; Oncoscience; September 23, 2024, Terrence C. Tsou, Avonne Connor and Jennifer Y. Sheng, https://www.oncoscience.us/article/608/text/
  2. Giaquinto AN, et al. CA Cancer J Clin. 2022; 72:524–41. https://doi.org/10.3322/caac.21754. PMID:36190501
  3. Stenholm S, et al. Epidemiology. 2015; 26:165–68. https://doi.org/10.1097/EDE.0000000000000228. PMID:25643097
  4. Uhelski AR, et al. J Cancer Surviv. 2023. https://doi.org/10.1007/s11764-023-01408-y. PMID:37261654.