Role of bone turnover markers in prediction of fracture healing: a contemporary evidence-based perspective

Authors

  • Hamza Ali Department of Orthopaedics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
  • Adarsh Kumar Singh Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
  • Anurag Baghel Department of Orthopaedics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
  • Shafaque Asif Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

DOI:

https://doi.org/10.18203/issn.2455-4510.IntJResOrthop20261244

Keywords:

Bone biomarkers, Bone healing, Fracture, Prognosis, Bone turnover

Abstract

Early and accurate assessment of fracture healing is limited by reliance on plain radiography, which detects only late mineralized changes and fails to capture early biological events, contributing to delayed union and non-union in 5-10% of cases. Bone turnover markers such as PINP, BALP, CTX, and TRACP-5b provide dynamic biochemical insight into osteoblast osteoclast activity and offer potential for earlier prediction of fracture healing outcomes. This review used a structured search of PubMed/MEDLINE, Scopus, Web of Science, and EMBASE up to December 2025 to synthesize mechanistic, diagnostic, and clinical evidence on BTMs in fracture healing. Successful fracture healing shows reproducible temporal BTM patterns, with early rises in CTX and TRACP-5b during days 3-7, followed by a 30-70% increase in PINP and BALP during weeks 2-4. Impaired healing is associated with blunted PINP and BALP responses and/or persistently elevated CTX beyond week 6, with reported odds ratios of 3-5 for delayed or non-union. Clinical application is limited by assay heterogeneity, circadian and metabolic variability, inconsistent sampling protocols, and the lack of fracture-specific cut-off values. An integrated Biochemical Biomechanical Radiological (BBR) Trifecta Model combining BTMs, mechanical stability metrics, and advanced imaging is proposed to improve prognostic accuracy. BTMs offer biologically sensitive and time-dependent information that complements radiography and enable early identification of patients at risk for delayed or impaired fracture healing. Integration through the proposed BBR model, supported by emerging biomarkers and AI-based analytics, may allow precise and personalized fracture monitoring.

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2026-04-27

How to Cite

Ali, H., Singh, A. K., Baghel, A., & Asif, S. (2026). Role of bone turnover markers in prediction of fracture healing: a contemporary evidence-based perspective. International Journal of Research in Orthopaedics, 12(3), 848–859. https://doi.org/10.18203/issn.2455-4510.IntJResOrthop20261244

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Review Articles