Factors predicting clinically significant fatigue in women following treatment for primary breast cancer

Cancer-related fatigue is common, complex, and distressing. It affects 70–100% of patients receiving chemotherapy and a significant number who have completed their treatments. We assessed a number of variables in women newly diagnosed with primary breast cancer (BrCa) to determine whether biological and/or functional measures are likely to be associated with the development of clinically significant fatigue (CSF). Two hundred twenty-three women participated in a study designed to document the impact of the diagnosis and treatment of primary breast cancer on function. Forty-four had complete data on all variables of interest at the time of confirmed diagnosis but prior to treatment (baseline) and ≥9 months post-diagnosis. Objective measures and descriptive variables included history, physical examination, limb volume, hemoglobin, white blood cell count, and glucose. Patient-reported outcomes included a verbal numerical rating of fatigue (0–10, a score of ≥4 was CSF), five subscales of the SF-36, Physical Activity Survey, and Sleep Questionnaire. At baseline, the entire cohort (n = 223) and the subset (n = 44) were not significantly different for demographic, biological, and self-reported data, except for younger age (p = 0.03) and ER+ (p = 0.01). Forty-five percent had body mass index (BMI) ≥ 25, 52% were post-menopause, and 52% received modified radical mastectomy, 39% lumpectomy, 52% chemotherapy, 68% radiation, and 86% hormonal therapy. Number of patients with CSF increased from 1 at baseline to 11 at ≥9 months of follow-up. CSF at ≥9 months significantly correlated with BMI ≥ 25, abnormal white blood cell count, and increase in limb volume and inversely correlated with vigorous activity and physical function (p < 0.05). Fatigue increases significantly following the treatment of BrCa. Predictors of CSF include high BMI and WBC count, increase in limb volume, and low level of physical activity. These are remediable

Differences in limb volume trajectories after breast cancer treatment

PURPOSE: ~20% of patients develop lymphedema (LE) following breast cancer (BC) surgery. An evaluation of distinct trajectories of volume change may improve our ability to diagnose LE sooner. The purposes of this study were to identify subgroups of women with distinct trajectories of limb volume changes following BC surgery and to evaluate for phenotypic differences among these classes. METHODS: In this prospective longitudinal study, 380 women were enrolled prior to unilateral BC surgery. Upper limb bioimpedance was measured preoperatively and serially for one year postoperatively. Resistance ratios (RR) were calculated. A RR of >1 indicates affected limb volume > unaffected limb volume. Latent class growth analysis (LCGA) was used to identify classes of women with distinct postoperative RR trajectories. Differences among classes were evaluated using analyses of variance and Chi square analyses. RESULTS: Three distinct classes were identified: RR <0.95 (37.9%), RR ~1.00 (46.8%), RR >1.05 (15.3%). Patients in the RR >1.05 class were more likely to have diabetes (p=0.036); were more likely to have BC on their dominant side (P<0.001); had higher RR ratios at the preoperative and one-month assessments (P<0.001); and were more likely to be diagnosed with LE (p<0.001). CONCLUSIONS: LCGA is a useful analytic technique to identify subgroups of women who may be at higher risk for the development of LE, based on trajectories of limb volume change after BC surgery. IMPLICATIONS FOR CANCER SURVIVORS: Assessment of preoperative and one-month bioimpedance RRs may allow for the earlier identification of patients who are at higher risk for the development of LE