Generation of a Potential Prognostic Matrix for Papillary Thyroid Cancer that Assesses Age, Tumor Size, Transforming Growth Factor-β, and BRAFV600E Mutation.

BACKGROUND

Papillary thyroid cancer (PTC) is the most common differentiated thyroid cancer and is responsible for 80-90% of thyroid cancer cases. Despite typically excellent prognoses, these subclinical low-risk cancers are often treated aggressively by surgical thyroidectomy. Consequently, the objective of this study was to generate a prognostic matrix to be used prior to PTC intervention.

METHODS

In this study, 80 PTC patients were assessed. Following adjustment for sex, logistic regression analysis showed that BRAFV600E mutation, transforming growth factor beta (TGF-β) expression, age, and tumor size are risk factors that can affect tumor clinical stage (p < 0.05). Based on the results of this analysis, we generated a matrix that incorporated 4 variables: patient age, tumor size, BRAFV600E mutation, and TGF-β expression.

RESULTS

We observed that the corresponding area under curve was as high as 0.91. The sensitivity and specificity of the model were 94.74 and 83.61%, respectively. These values are significantly higher than those generated from single indexes.

CONCLUSION

As a result of this analysis, it is hoped that the resultant matrix can be utilized during clinical diagnosis and treatment prior to thyroid nodule surgery.