Purpose: Although osteosarcoma patients receive a standardized treatment, metachronous metastatic relapse still impairs the overall survival (OS). This study aimed to explore the clinicopathological features and prognostic factors of osteosarcoma patients with metachronous metastatic relapse. Patients and methods: We retrospectively analyzed 59 patients, between January 1st, 2004 and December 31st, 2013. Employed Chi-square test to recognize the differences in clinicopathological characteristics between early and late metastatic patients, and the differences between shorter and longer survival patients. Used the Kaplan-Meier method to evaluate the survival data, cox step proportional hazard test to analyze the prognostic factors associated with OS. Results: We found that early metastatic patients were prominently correlated with the male, tumor size ≥8 cm, histological grade G2, Enneking stages II, anatomic location of the distal femur, pathological of conventional types, and elevated alkaline phosphatase (ALP) level at diagnosis, (p<0.05). In parallel, the shorter survival patients were primarily linked to tumor size ≥8 cm, histological grade G2, Enneking stages II, early metastasis, multiple pulmonary metastases, lack of curative treatment after metastasis, increased level of ALP at diagnosis and LDH after metastasis, (p<0.05). The univariate analyses of the prognostic factors showed that patients who had these clinicopathological characteristics, such as male, tumor size ≥8 cm, Enneking stage IIB, multiple pulmonary metastases, lack of curative treatment after metastasis, the elevated ALP at diagnosis, elevated ALP and LDH after metastasis, had a worse OS in osteosarcoma patient with metachronous metastatic relapse, (p<0.05). The multivariate analyses showed that tumor size, type of metastasis and ALP level at diagnosis were independent factors for OS in osteosarcoma patient with metachronous metastatic relapse (p<0.05). Conclusion: These results indicated that osteosarcoma patients with metachronous metastatic relapse have special features which might be utilized to effectively predict the likelihood of early metastatic relapse and the prognosis.

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