Prognostic evaluation models for primary thyroid lymphoma, based on the SEER database and an external validation
Yunshu Zhu1, Sheng Yang1, Xiaohui He2
1Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Primary thyroid lymphoma (PTL) incidence is rising. This study developed a prognostic model to identify high-risk PTL patients, aiding in improved patient outcomes and survival predictions.
Area of Science:
- Oncology
- Epidemiology
- Biostatistics
Background:
- Primary thyroid lymphoma (PTL) is a rare cancer with limited literature.
- Existing research primarily consists of small case series and reports.
Purpose of the Study:
- To assess the epidemiological characteristics of PTL.
- To evaluate survival rates and identify prognostic factors for PTL patients.
- To develop a predictive model for PTL outcomes.
Main Methods:
- Analysis of 2215 PTL patients from the Surveillance, Epidemiology, and End Results (SEER) database (1983-2015).
- External validation using 105 PTL patients from the Cancer Hospital, Chinese Academy of Medical Sciences.
- Construction of nomograms to predict 1-, 5-, and 10-year overall survival (OS) and lymphoma-specific survival (LSS).
Main Results:
- PTL incidence increased by 3.2% annually from 1977 to 1994.
- 1-, 5-, and 10-year OS rates were 84.66%, 71.61%, and 55.95%, respectively.
- Key prognostic factors for shorter OS included age ≥ 60, unmarried status, advanced Ann Arbor stage (III-IV), diffuse large B-cell lymphoma, and T-cell non-Hodgkin lymphoma. Age, stage, diagnosis year, treatment modalities (surgery, radiation, chemotherapy), and histology predicted PTL-specific mortality risk.
Conclusions:
- The study developed the first externally validated prognostic model for PTL.
- This model can assist clinicians in identifying high-risk PTL patients.
- The prognostic model aims to improve patient outcomes and guide treatment strategies.
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