Variability in resistance training trajectories of breast cancer patients undergoing therapy

Abstract

Purpose: In resistance training (RT), the change in volume-load from training sessions (TS) to TS is an indicator of training progress. Resulting growth trajectories are likely to differ between individuals. Understanding this variation is important for exercise planning in general, but even more for clinical populations. We investigated this variation in breast cancer patients undergoing treatment.

Methods: Data of 69 patients from two randomized controlled trails were investigated. They conducted a 12-week RT program. We fitted a quadratic Bayesian regression model to the baseline standardized volume-load over the course of the intervention. We allowed all parameters to vary both between exercises and between individuals.

Results: We observed a positive linear component of 0.093 (95% uncertainty interval (UI) 0.058 to 0.120) and a negative quadratic component of - 0.002 (95% UI -0.008 to 0.001) for the mean trajectory of the change in volume-load. For the different exercises, we observed a dispersion for both the linear (0.043, 95% UI 0.018 to 0.082) and the quadratic component (0.002, 95% UI < 0.001 to 0.004). Variation between individual appears to be approximately four times larger. We also observed between-exercise variation within individuals. Extrapolation of the regression model indicates training progression stagnates after 20.6 TS (95% UI 14.8 to 44.4).

Conclusion: There is substantial variation in RT response between breast cancer patients undergoing tumor therapy and in-between exercises. The non-linear trajectory indicates that training progression will eventually plateau, demanding periodization and timely modification.

Trial registration: BEATE Study: NCT01106820, Date: April 20, 2010; BEST Study: NCT01468766, Date: November 9, 2011.

Keywords: Adjuvant tumor treatment; Bayesian statistics; Exercise oncology; Hierarchical model; Response variability.

Fig. 1

Patient flow. Caption: ^aHD: Heidelberg, ^b100% refers to the maximum of 24 training sessions)

Fig. 2

Posterior distribution of a the linear and b quadratic component for each exercise. Caption: The dashed black line marks the zero line, and the dashed red line the population level estimate

Fig. 3

Variation of posterior distributions per exercise within individuals. Exemplary plots for 3 patients: a Above average response, b average response, c below average response. Caption: The dashed black line marks the zero line, and the dashed red line the population level estimate. A blue area under the curve characterizes positive parameter values, whereas a grey area under the curve characterizes negative values

Fig. 4

Predicted quadratic trajectory for each exercise. Caption: Due to the quadratic model the volume-load will decrease after it reached the peak. This is certainly not a depiction of the real training trajectory