Development and Validation of a Nomogram for Prognosis Prediction in Patients with Synchronous Primary Thyroid and Breast Cancer Based on SEER Database

Abstract

This study aimed to develop prognostic prediction models for patients diagnosed with synchronous thyroid and breast cancer (TBC). Utilizing the SEER database, key predictive factors were identified, including T stage of thyroid cancer, T stage of breast cancer, M stage of breast cancer, patient age, thyroid cancer surgery type, and isotope therapy. A nomogram predicting 5-year and 10-year survival rates was constructed and validated, exhibiting strong performance (C-statistic: 0.79 in the development cohort (95% CI: 0.74-0.84), and 0.82 in the validation cohort (95% CI: 0.77-0.89)). The area under the Receiver Operator Characteristic (ROC) curve ranged from 0.798 to 0.883 for both cohorts. Calibration and decision curve analyses further affirmed the model’s clinical utility. Stratifying patients into high-risk and low-risk groups using the nomogram revealed significant differences in survival rates (P < 0.0001). The successful development and validation of this nomogram for predicting 5-year and 10-year survival rates in patients with synchronous TBC hold promise for similar patient populations, contributing significantly to cancer research.

Keywords:

• Synchronous multiple primary cancers
• prognosis prediction
• SEER
• thyroid cancer
• breast cancer

Acknowledgments

Special thanks to Fuhao Xu, who is pursuing a degree in Applied Statistics at Zhejiang University of Finance and Economics, for skillfully utilizing Python software to accurately split and merge our data.

Authors’ contributions

Zhang Jianfei contributed to the research design; Minna Hou contributed to data extraction; Miao Huo and Jiao Guo contributed to data analysis and writing. Ning Bai, Ruifen Xu and Jianhui Li are responsible for the revision of the document. Each author contributed important intellectual content during manuscript drafting or revision and accepts personal accountability for the overall work, and agrees to ensure that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.

Declaration 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.

Data availability statement

All data included in this study are available upon request by contact with the corresponding author.

Additional information

Funding

This research was supported by the Key Research and Development Program of Shaanxi Province (Grant No. 2020SF-296) and the Scientific and Technological Talent Support Program of Shaanxi Provincial People’s Hospital (Project No. 2023JY-37).