Bone turnover biomarkers and semi-quantitative bone histomorphometry in chronic kidney disease: Comparison between patients with and without fractures - Sushil Sharma; Premjit Sujir; Pranav Rajasekharan; Prem Kotian; Manikanta Bhupal; G. N. Sudhanva; Karthik Parimi (Sage Open Medicine, 2026)
Background Chronic kidney disease (CKD) is associated with increased fracture risk not fully explained by reduced bone mineral density. CKD–mineral and bone disorder (CKD-MBD), involving abnormalities in bone turnover, mineralization, and microarchitecture, contributes to skeletal fragility. However, the relationship between routine biochemical markers and semi-quantitative bone histomorphometry remains inadequately defined, particularly in resource-limited settings and the Indian population. The objective of this study was to compare biochemical markers and semi-quantitative bone histomorphometric findings in CKD patients with and without fractures. Methods In this hospital-based comparative cross-sectional study, 48 patients with CKD stage 3–4 were divided into fracture (n = 24) and non-fracture groups (n = 24). Serum calcium, 25-hydroxyvitamin D, parathyroid hormone (PTH), and alkaline phosphatase (ALP) were measured. Bone samples were obtained intraoperatively or via transiliac crest biopsy. Semi-quantitative bone histomorphometry was assessed by a pathologist. Statistical analysis included appropriate group comparisons. Results Fracture patients had significantly lower vitamin D (p = 0.007) and calcium (p = 0.005), and higher PTH (p = 0.002) and ALP (p = 0.001). Semi-quantitative histomorphometric evaluation showed increased osteoid volume, reduced trabecular thickness, and elevated osteoblastic and osteoclastic activity. Conclusion In our study cohort, CKD patients with fractures exhibited a high-turnover bone phenotype with increased osteoid volume and altered bone histology. Biochemical markers may serve as cost-effective adjuncts for fracture risk stratification, particularly where advanced diagnostics are limited. Findings should be interpreted cautiously given the cross-sectional design and small sample size.