Clinicopathological Profiling and Skeletal Tropism of Bone Metastases in Breast Cancer: A 5-Year Retrospective Institutional Analysis in Central Java - Gana Adyaksa; Benny Rizkillah Pratamayoga (Bioscientia Medicina : Journal of Biomedicine and Translational Research, 2026)
Background: The skeletal system is the most frequent site of distant metastasis in breast cancer, precipitating severe skeletal-related events. Characterizing histological subtypes, molecular profiles, and precise skeletal distribution is essential for targeted surveillance. Methods: A retrospective analytical cohort study of 200 consecutive patients with radiologically documented bone metastasis was conducted at Dr. Kariadi General Hospital, Semarang, Central Java (2021–2025). Diagnosis required definitive confirmation via CT-scan or bone scintigraphy; clinical-only diagnoses were excluded. Primary metastatic burden was objectively defined by the largest lesion volume on imaging. World Health Organization (WHO) criteria were applied, subsuming invasive ductal carcinoma (IDC) into invasive breast carcinoma of no special type (NST). Immunohistochemical profiling and demographic data were extracted. Inferential statistics included Pearson Chi-Square and multivariate logistic regression to identify independent predictors of anatomical tropism, reporting Adjusted Odds Ratios (aOR) with 95% Confidence Intervals (CI). Results: The cohort was predominantly female (n=199, 99.5%), with a mean age of 54.2 (SD ± 8.5) years. Following WHO consolidation, NST comprised 90.0% (n=180) and Invasive Lobular Carcinoma (ILC) 10.0% (n=20). The axial skeleton harbored the primary burden in 82.5% of cases. ILC demonstrated a significantly distinct tropism, showing 50.0% appendicular involvement compared to 13.9% in NST. Multivariate logistic regression confirmed ILC as an independent predictor for appendicular metastasis (aOR 4.21, 95% CI 1.85–9.60, p=0.012). Conclusion: While NST exhibits a strong predilection for the axial skeleton, ILC uniquely favors appendicular dissemination. These findings mandate histology-specific diagnostic algorithms and targeted orthopedic surveillance.