Intramuscular adipose tissue, muscle area, and power as predictors of performance in breast cancer survivors.

Purpose: The decline in physical performance, assessed by physical tests such as the timed up and go (TUG) test, is a consequence of reduced physiological reserves at higher levels of a hierarchical process. This occurs due to changes in muscle architecture, including atrophy and fat infiltration into the muscles, which in turn lead to changes in muscle function, resulting in reduced muscle strength and power and, consequently, affecting physical performance. This study investigated predictive factors for physical performance in breast cancer survivor (BCS), focusing on intramuscular adipose tissue (IMAT), quadríceps muscle area (QMA), and muscular power.
Methods: This observational, analytical, and cross-sectional study included 23 women without a history of cancer (age, 58.5 ± 8.3 years; BMI, 27.2 ± 5.1 kg/m ² ) and 56 BCS (age, 58.5 ± 8.3 years; BMI, 27.2 ± 5.1 kg/m ² ). QMA and IMAT were assessed using computed tomography images. Muscular power and physical performance were measured using the 5-repetition sit-to-stand and TUG tests, respectively.
Results: IMAT (r = 0.4, P < 0.01) and muscular power (r =  - 0.4, P < 0.01) were associated with TUG performance in BCS, whereas QMA (r =  - 0.22, P = 0.10) showed no significant association. QMA (r = 0.55, P < 0.01) was associated with muscular power, while no significant association was found between IMAT and muscular power (r =  - 0.05, P = 0.73). Age explained 19% (P < 0.01) of TUG performance variability. Adding muscular power increased explanatory power by 12% (P < 0.01), and including IMAT further increased it by 7% (P = 0.02) for TUG performance. Collectively, age, muscular power, and IMAT accounted for 38% of the performance variance in the TUG test (age, B = 0.06, P = 0.043; muscular power, B =  - 0.01, P = 0.002; IMAT, B =  - 0.05, P = 0.020).
Conclusions: Our findings suggest that IMAT and muscular power predict the physical performance of BCS, while QMA does not have the same predictive capability.
(© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)