A user-friendly nomogram for predicting radioiodine refractory differentiated thyroid cancer

Area of Science:

• Oncology
• Nuclear Medicine
• Medical Diagnostics

Background:

• Radioiodine refractory differentiated thyroid cancer (RAIR-DTC) diagnosis is time-consuming.
• A predictive model is needed for timely RAIR-DTC identification.
• This study aimed to develop a nomogram for RAIR prediction in DTC patients with distant metastases.

Purpose of the Study:

• To develop and validate a nomogram for predicting radioiodine refractory differentiated thyroid cancer (RAIR-DTC).
• To identify independent predictors for RAIR in differentiated thyroid cancer (DTC) patients with distant metastases (DM).
• To stratify RAIR-DTC progression using a novel predictive model.

Main Methods:

• Data from 124 DTC patients (2010-2021) were analyzed.
• Multivariate logistic regression identified predictors: Δs-Tg/Δs-TSH and age at diagnosis.
• A nomogram was developed and validated using ROC curves and decision analysis.

Main Results:

• A nomogram incorporating Δs-Tg/Δs-TSH and age achieved an AUC of 0.830.
• The model demonstrated good predictive efficacy with 83.0% specificity and 75.5% sensitivity.
• A Δs-Tg/Δs-TSH cut-off of 1.50 effectively stratified RAIR-DTC progression (P=0.012).

Conclusions:

• A user-friendly nomogram model provides effective prediction of RAIR.
• The model aids in timely RAIR-DTC diagnosis and management.
• Δs-Tg/Δs-TSH ratio can stratify RAIR-DTC into rapidly or slowly progressive subtypes.