Building a Predictive Model and Survival Analysis for Distant Metastases
in Differentiated Thyroid Carcinoma: A Three Center Retrospective Study
Abstract
BACKGROUNDː Distant metastases (DM) occur rarely and are
associated with poor outcomes in patients with differentiated thyroid
carcinoma (DTC). The aim of this study was to explore potential risk
factors of DM in DTC and build a decision-tree model. METHODSː
The medical records of 15,591 patients who were diagnosed with DTC after
initial surgery in three medical centers (2000 to 2018) were reviewed
and 37 patients (test group) and 14 patients (validation group) with DM
and detailed clinicopathologic characteristics were identified. Patients
with no evidence of disease (NED) postoperatively were randomly sampled
to create a control group in a 4:1 ratio. RESULTSː Multiple
factors, including median age, extrathyroidal extension (ETE), AJCC
stage, position, histological type, and diameter differed significantly
between the DM and NED groups (P˂0.001) in univariate and multivariate
analysis. AJCC stage and diameter of the primary tumor made the greatest
contributions to prognosis according to decision-tree analysis and a
random forest algorithm. The predictive model constructed from these
data achieved 100% accuracy of classification. External validation
confirmed that this model has 100% accuracy of classification. In
addition, histology and ETE were found to be independent predictors of
survival in patients with metachronous metastases. CONCLUSIONSː
This study optimized the weight of risk factors, including AJCC stage
and diameter of primary tumor, in predicting DM in patients with DTC.
Our predictive model provides a strong tool for prediction that may
potentially affect clinical decision-making.