Background <p>Pulmonary metastases are the leading cause of mortality in osteosarcoma patients. Identifying high-risk factors is essential for optimizing surveillance and treatment. To systematically review and analyze clinical and pathological risk factors associated with pulmonary metastases in osteosarcoma.</p> Methods <p>A systematic digital screening of PubMed, Scopus, and EMBASE was carried out without restrictions, supplemented by manual and grey literature searches. Observational studies reporting odds ratios (ORs) with 95% confidence intervals (CIs) for pulmonary metastases were included. A qualitative and quantitative analysis was carried out by pooling the effect estimates using forest plots. The quality of the studies was assessed by the Newcastle- Ottawa scale.</p> Results <p>Fifteen studies involving over 12,000 patients were included. In univariate analyses, larger tumor size, positive N stage, higher T stage, and treatment with radiation or chemotherapy were significantly associated with increased risk of lung metastasis, whereas surgery was associated with reduced risk. Patients aged 18–40 years showed a lower risk in univariate analysis, while gender and tumor location were not significantly associated. In multivariate analyses, tumor size greater than 10&#xa0;cm, positive N stage, higher histologic grade (particularly Grades III and IV), and advanced T stage remained independent predictors of lung metastasis. Age and gender were not independently associated after adjustment. Surgery continued to demonstrate a protective association, whereas radiation and chemotherapy were associated with increased odds of lung metastasis.</p> Conclusion <p>Tumor size, stage, nodal status, and histological grade are strong predictors of pulmonary metastases in osteosarcoma, while surgery is protective. These findings support the use of risk-stratified follow-up and further research on integrating molecular markers into prognostic models.</p> Prospero registration <p>CRD420251053452.</p>

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Risk factors for pulmonary metastases in osteosarcoma: a systematic review and meta-analysis

  • Peijun Dai,
  • Huipeng Zhou,
  • Qiujian Lian,
  • Zhifeng Zhang,
  • Xiangfeng Jia,
  • Junyong Ge

摘要

Background

Pulmonary metastases are the leading cause of mortality in osteosarcoma patients. Identifying high-risk factors is essential for optimizing surveillance and treatment. To systematically review and analyze clinical and pathological risk factors associated with pulmonary metastases in osteosarcoma.

Methods

A systematic digital screening of PubMed, Scopus, and EMBASE was carried out without restrictions, supplemented by manual and grey literature searches. Observational studies reporting odds ratios (ORs) with 95% confidence intervals (CIs) for pulmonary metastases were included. A qualitative and quantitative analysis was carried out by pooling the effect estimates using forest plots. The quality of the studies was assessed by the Newcastle- Ottawa scale.

Results

Fifteen studies involving over 12,000 patients were included. In univariate analyses, larger tumor size, positive N stage, higher T stage, and treatment with radiation or chemotherapy were significantly associated with increased risk of lung metastasis, whereas surgery was associated with reduced risk. Patients aged 18–40 years showed a lower risk in univariate analysis, while gender and tumor location were not significantly associated. In multivariate analyses, tumor size greater than 10 cm, positive N stage, higher histologic grade (particularly Grades III and IV), and advanced T stage remained independent predictors of lung metastasis. Age and gender were not independently associated after adjustment. Surgery continued to demonstrate a protective association, whereas radiation and chemotherapy were associated with increased odds of lung metastasis.

Conclusion

Tumor size, stage, nodal status, and histological grade are strong predictors of pulmonary metastases in osteosarcoma, while surgery is protective. These findings support the use of risk-stratified follow-up and further research on integrating molecular markers into prognostic models.

Prospero registration

CRD420251053452.