Cardiorespiratory Fitness, Physical Activity, Sedentary Behavior, and Diabetes Risk Among Breast Cancer Survivors Treated with Endocrine Therapies.

[PURPOSE] Endocrine therapies for breast cancer (BC) (i.e., selective estrogen receptor modulators (SERMs) or aromatase inhibitors (AI)) lower the risk for cancer recurrence but are linked to an increased risk of type 2 diabetes (T2D). This study examined associations between cardiorespiratory fitness (CRF), physical activity (PA), and sedentary behavior with T2D risk markers, and whether the magnitude of these associations varied between SERM and AI.

[METHODS] This study was a cross-sectional study. Participants were BC survivors receiving either SERM or AI for ≥1 yr. A graded exercise test determined CRF (peak oxygen consumption). Participants wore an accelerometer for 14 d to assess time in sedentary behavior, light PA, moderate to vigorous PA, and number of sit-to-stand transitions. T2D risk was measured by an oral glucose tolerance test to determine fasting glucose, glucose area under the curve, insulin sensitivity (Matsuda Index), and insulin resistance (homeostatic model assessment of insulin resistance). Regression models estimated associations between CRF/activity behaviors and markers of T2D by endocrine therapy type adjusting for age, fat mass (measured using dual-energy x-ray absorptiometry scan, time receiving therapy, and amount of moderate or vigorous PA.

[RESULTS] Participants (SERM ( n = 19) or AI ( n = 20)) were M = 54 ± 12 yr old and had received therapy for M = 3.2 ± 2.8 yr. Sit-to-stand transitions were associated with lower glucose tolerance (-221.52; 95% confidence interval (CI), -442.44 to -0.59; P = 0.049), higher insulin sensitivity (0.45; 95% CI, 0.25 to 0.66; P < 0.001), and lower insulin resistance (-0.06; 95% CI, -0.13 to 0; P = 0.047) but only for those on SERMs.

[CONCLUSIONS] Breaking up sedentary time may be a promising intervention target to lowering T2D risk among BC survivors treated with SERMs. Further studies are needed to better understand how SERMS and AI are differentially influencing glucoregulatory pathways.