Related Experiment Video
Updated: Jun 14, 2025
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
Published on: August 16, 2020
Preoperative platelet distribution width predicts bone metastasis in patients with breast cancer
Mei-Yue Song1, Lin Zhao2, Wen-Juan Huang2
1Department of Pathology, The Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Purpose:
Bone metastases occur in 50-70% of patients with breast cancer (BC) and result in high mortality. Platelet distribution width (PDW), a commonly used parameter of activated platelets, has been associated with a poor prognosis in BC. We aim to investigate the prognostic role of PDW for bone metastasis in BC patients.
Methods:
515 patients who received BC surgery in the Harbin Medical University Cancer Hospital from July 1, 2016, to December 31, 2017, were reviewed. Patients' characteristics and platelet indices upon enrollment in this study were collected. The Kaplan-Meier method was used to estimate the 5-year bone metastasis incidence. The univariate and multivariate Cox regression analyses were utilized to identify risk factors associated with bone metastasis.
Results:
The patients with bone metastases exhibited lower PDW levels than the patients without bone metastases. Moreover, decreased PDW was significantly correlated with histologic type, multifocal disease, and lymph node status. In addition, the patients with reduced PDW levels were more likely to develop bone metastasis. Multivariate analysis showed that PDW was an independent predictor for bone metastasis.
Conclusion:
PDW is an independent predictor of bone metastasis in BC. Further research is warranted.
