Clinical Report: Factors Affecting and Predictive Modeling of Postoperative Efficacy of Adjuvant ¹³¹I Treatment in Differentiated Thyroid Cancer Patients
Overview
This study investigates factors influencing the efficacy of postoperative adjuvant ¹³¹I therapy in differentiated thyroid cancer (DTC) patients. It identifies independent risk factors and constructs predictive models.
Background
Postoperative adjuvant therapy aims to eradicate residual or metastatic lesions in DTC patients, improving survival rates and reducing recurrence. The 2025 ATA guidelines recommend tailored radioiodine therapy based on individual risk stratification.
Data Highlights
Factor
OR
BMI
1.112
Number of Lymph Node Metastases (LNM)
1.061
Stimulated Thyroglobulin (s-Tg)
1.198
BRAF Mutation
3.041
Mean Residual ¹³¹I Uptake Count (C-mean)
1.103
Maximum Residual ¹³¹I Uptake Count (C-max)
0.995
Key Findings
The incidence of non-excellent response (nER) was 48.40% among DTC patients.
Independent risk factors for nER included BMI, number of metastatic lymph nodes, stimulated thyroglobulin, BRAF mutation, and mean residual ¹³¹I uptake count.
The logistic regression model achieved an AUC of 86.30% for predicting treatment response.
The random forest model demonstrated superior predictive performance with an AUC of 90.77%.
Patients with high s-Tg, multiple LNM, and elevated BMI had a 100% risk of nER.
Clinical Implications
Identifying independent risk factors can assist in understanding treatment responses in DTC patients.
Conclusion
A significant proportion of DTC patients do not achieve an excellent response post-therapy.
