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Development and validation of a model for the prediction of disease-specific survival in patients with oral squamous cell carcinoma: based on random survival forest analysis

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European Archives of Oto-Rhino-Laryngology Aims and scope Submit manuscript

Abstract

Objective

To establish a model for predicting the disease-specific survival (DSS) of patients with oral squamous cell carcinoma (OSCC).

Methods

Patients diagnosed with OSCC from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into development (n = 14,495) and internal validation cohort (n = 9625). Additionally, a cohort from a hospital located in Southeastern China was utilized for external validation (n = 582).

Results

TNM stage, adjuvant treatment, surgery, tumor sites, age, grade, and gender were used for RSF model construction based on the development cohort. The effectiveness of the model was confirmed through time-dependent ROC curves in different cohorts. The risk score exhibited an almost exponential increase in the hazard ratio of death due to OSCC. In development, internal, and external validation cohorts, the prognosis was significantly worse for patients in groups with higher risk scores (all log-rank P < 0.05).

Conclusion

Based on RSF, a high-performance prediction model for OSCC prognosis was created and verified in this study.

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Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

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Acknowledgements

This study was supported by Fujian Natural Science Foundation Program No., Grant/Award Numbers: 2020J01638, 2022J01235 and 2022J01239; Joint Funds for the Innovation of Science and Technology of Fujian Province, Grant/Award Number: 2021Y9015; Open Project of Key Laboratory of environmental factors and Oncology of Fujian Province (GWSZD-202001).

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Author notes

  1. Na Wang, Yulan Lin and Haoyuan Song have contributed equally to this work.

Authors and Affiliations

  1. Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China

    Na Wang, Yulan Lin, Haoyuan Song, Weihai Huang, Jingyao Huang, Liling Shen, Fa Chen, Fengqiong Liu & Baochang He

  2. Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fujian, China

    Na Wang, Yulan Lin, Haoyuan Song, Weihai Huang, Jingyao Huang, Liling Shen, Fa Chen, Fengqiong Liu & Baochang He

  3. Laboratory Center, The Major Subject of Environment and Health of Fujian Key Universities, School of Public Health, Fujian Medical University, Fujian, China

    Jing Wang

  4. Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Fujian Medical University, Fuzhou, China

    Yu Qiu, Bin Shi, Lisong Lin & Baochang He

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  1. Na Wang
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Contributions

NW, YLL and HYS: study design, data analysis and interpretation, statistical analysis, and manuscript preparation. FC, FQL, and JW: quality control of data and algorithms and manuscript editing. LLS, WHH, JYH, YQ, and BS: data acquisition. LSL and BCH: study concepts, study design, and manuscript review.

Corresponding authors

Correspondence to Lisong Lin or Baochang He.

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Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethical considerations and consent

It is not necessary to get ethical consent to use patient data in the SEER database since the information is anonymous. For patients in external validation, written informed consent was obtained. This research was conducted according to the ethical standards of the Helsinki Declaration, and the ethical approval was approved by the Ethics Committees of Fujian Medical University, Fuzhou, China (Approval ID: 2011053).

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Wang, N., Lin, Y., Song, H. et al. Development and validation of a model for the prediction of disease-specific survival in patients with oral squamous cell carcinoma: based on random survival forest analysis. Eur Arch Otorhinolaryngol 280, 5049–5057 (2023). https://doi.org/10.1007/s00405-023-08087-6

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