Step Count and Treatment Response in Neoadjuvant Breast Cancer

Physical activity and sleep quality are important prognostic factors in oncology, but objective and continuous monitoring during neoadjuvant systemic therapy is limited. Wearable devices provide non-invasive, real-time data on step counts, heart rate, and sleep. This study will evaluate whether daily step counts and digital health metrics predict pathological response in non-metastatic Human Epidermal Growth Factor Receptor 2 (HER2)-negative breast cancer. Primary Objective: To assess the association between daily step counts and pathological response, including pathological complete response (pCR, defined as no residual invasive carcinoma in the breast and axillary nodes) and Miller-Payne score (range 1-5; higher scores indicate greater regression). Secondary Objectives: To explore associations between physical activity and sleep quality (Pittsburgh Sleep Quality Index, PSQI), quality of life (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire - Core 30, EORTC QLQ-C30), and perioperative outcomes; and to evaluate feasibility and adherence to smartwatch monitoring. Methods: This is a multicenter prospective observational cohort study enrolling 82 female patients aged ≥18 years with non-metastatic HER2-negative breast cancer scheduled to receive neoadjuvant systemic therapy followed by surgery. Smartwatches (Huawei Fit 2) will continuously monitor activity, sleep, and heart rate. Questionnaires will be administered at baseline and at the end of treatment. PSQI: Global score 0-21; higher scores indicate worse sleep quality; a cut-off \>5 defines poor sleep. A validated Turkish version is available. EORTC QLQ-C30: Standardized 0-100 scoring system; higher scores on functional scales indicate better functioning, while higher scores on symptom scales indicate greater symptom burden. A validated Turkish version is available. Pathological response will be determined at surgery using pCR and Miller-Payne criteria. Sample Size and Statistics: A priori power analysis (effect size d = 0.5, α = 0.05, power = 0.80) indicates a minimum of 82 patients. Regression analyses and subgroup evaluations will test associations with step counts, questionnaire scores, and perioperative outcomes. Significance: This study (NEOBRE-STEP) is among the first multicenter efforts to integrate wearable health monitoring into breast cancer supportive care. By combining objective activity and sleep data with validated patient-reported outcomes, the study may provide new prognostic insights and support the integration of digital health tools into oncology practice.