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The novel dynamic nomogram and risk classification system constructed for predicting post-surgical overall survival and mortality risk in primary chondrosarcoma: a population study based on SEER database

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Abstract

Background

Surgery is the predominant method to improve the prognosis of primary chondrosarcoma patients. We aimed to construct the first reliable nomogram to predict the post-surgical overall survival (OS) of primary chondrosarcoma patients.

Methods

We downloaded all primary chondrosarcoma patients treated with surgery between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database, and randomized them into training set (60%) and validation set (40%). Cox proportional regression analysis was applied to the training set to identify independent prognostic variables, and then constructed a nomogram for predicting 3-, 5-, and 8-year OS. The Harrell's concordance index (C-index), receiver operating characteristic curve (ROC), the area under curve (AUC), calibration curve and decision curve analysis (DCA) was used to assess the predictive efficacy and clinical applicability of the nomogram. The nomogram was also compared with The American Joint Committee on Cancer (AJCC) staging system.

Results

A total of 1005 post-surgical primary chondrosarcoma patients were included in this study. We finally identified five independent prognostic variables to construct the nomogram, being age, grade, tumor size, disease stage and histological type. The C-index results showed that the prediction performance of the nomogram was significantly better than the AJCC staging system. In the training set, (C-index: 0.805, 95% CI 0.879–0.730 vs 0.686, 95% CI 0.606–0.766); in the validation set, (C-index: 0.811, 95% CI 0.895–0.727 vs 0.697, 95% CI 0.647–0.799). Additionally, the AUC values generated by the ROC were all greater than 0.8, which also indicated the excellent predictive performance of the nomogram. The calibration curves showed that the predicted survival rate was highly similar to the actual. Time-dependent ROC and DCA showed that the nomogram has better predictive performance and net clinical benefits than the AJCC staging system. Finally, a risk stratification system based on nomogram was constructed.

Conclusion

We successfully constructed and validated the first nomogram that could reliably predict 3-, 5-, and 8-year post-surgical OS in primary chondrosarcoma patients. Furthermore, the web-based dynamic nomogram could be more conveniently applied to clinic, providing assistance to surgeons and patients.

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Data availability

The raw data for this study were obtained from publicly available databases (https://seer.cancer.gov/).

References

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Acknowledgements

We sincerely thank the SEER database for providing the data for our study. Also thank the continued support of Jun Yang.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

Authors

Contributions

LMJ and DXZ conceived and designed the study. LMJ, YG and JJJ reviewed the literature. LMJ and YG analyzed the data. LMJ and JJJ generated the figures. LMJ wrote the manuscript. LMJ, YG, JJJ and DX Z revised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Dongxu Zhao.

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Conflict of interest

The authors declare that they have no potential commercial or financial conflicts of interest regarding this study.

Ethical approval

The raw data for this study were obtained from the publicly available SEER database. Thus, the ethical approval and informed consent was not applicable.

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Jiang, L., Gong, Y., Jiang, J. et al. The novel dynamic nomogram and risk classification system constructed for predicting post-surgical overall survival and mortality risk in primary chondrosarcoma: a population study based on SEER database. J Cancer Res Clin Oncol 149, 12765–12778 (2023). https://doi.org/10.1007/s00432-023-05143-w

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