ArticleAmerican journal of cancer research2026
Epidemiology, risk factor and prognostic factor of young differentiated thyroid carcinoma with distant metastasis: a retrospective cohort study.
Article in American journal of cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study aimed to characterize the epidemiology, risk factors, and survival outcomes of differentiated thyroid carcinoma (DTC) patients aged <55 years with distant metastasis (DM). The Surveillance, Epidemiology, and End Results (SEER) database was researched retrospectively for young DTC patients. Multivariate Logistic and Cox regression analyses were used to identify DM predictors and survival determinants. The overall survival (OS) and cancer-specific survival (CSS) were evaluated and compared by Kaplan-Meier analysis and Log-Rank test, respectively. The risk and prognostic nomogram were constructed and validated using ROC curves, calibration plots, and decision curve analysis. A total of 68,373 young DTC patients were identified. The DM prevalence was 0.65% (95% CI: 0.59-0.72%), predominantly involving the lungs (35.8%). Independent risk factors for DM included male sex (OR=1.84), follicular histology (OR=2.43), advanced T4 (OR=22.3) and N1 stages (OR=4.91). The 5-year and 10-year OS rates for young DTC patients with DM were 83.6% and 73.3%, while the 5-year and 10-year CSS rates were 85.0% and 79.9%, respectively. Multivariate Cox analysis identified several independent prognostic factors for both OS and CSS including age, the presence of lung, bone, liver, and brain metastases, as well as the use of surgery and chemotherapy. Established prognostic nomograms demonstrated robust performance (C-index =0.87 for OS; C-index =0.85 for CSS), with time-dependent area under the curves (AUCs) exceeding 0.80 at 5, and 10 years. In conclusion, this study presents the first population-level analysis of young DTC patients with distant metastases and establishes SEER-derived predictive models for assessing risk and survival among these patients.
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