Novel prediction nomogram model for recurrent/persistent disease versus the American thyroid association recurrence risk stratification in patients with N1b papillary thyroid cancer: a retrospective cohort study.

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most prevalent endocrine malignancy globally with a recurrence rate of up to 30%. Patients with lateral cervical metastasis (N1b PTC) are at a higher risk for reoperation. The aim of this study was to achieve a personalized assessment of recurrence risk in patients with N1b papillary thyroid carcinoma to better guide recurrence risk management.

METHODS

This retrospective study included 558 patients with stage N1b papillary thyroid carcinoma. Independent risk factors for recurrence were identified using least absolute shrinkage and selection operator regression. These factors were used to develop a nomogram to predict the risk of recurrence.

RESULTS

Seven variables were selected to construct the nomogram. The risk factors from the training set were used to develop the nomogram, which was validated with independent test sets. Recurrence risk was dynamically assessed over time, enabling the creation of more personalized treatment and monitoring plans. The nomogram provided more accurate and individualized recurrence predictions than the 2015 American Thyroid Association recurrence risk stratification for patients with N1b papillary thyroid carcinoma.

CONCLUSIONS

Our nomogram effectively complements the 2015 American Thyroid Association recurrence risk stratification, providing a valuable tool for personalized patient management.