Establishment and validation of a nomogram to predict structural incomplete response in papillary thyroid carcinoma patients: a retrospective study

Abstract

Objective To identify risk factors related to structural incomplete response (SIR) in papillary thyroid carcinoma (PTC) and develop a nomogram for PTC patients. Methods In this respective study, clinical, ultrasonic, and pathological data of PTC patients treated at our institute between 2016 and 2020 were analyzed. Patients were randomly split into training and validation sets at a ratio of 7:3. Multivariate Cox regression analysis was conducted to determine independent prognostic factors. On the basis of these factors, a nomogram was built to predict SIR. P value, concordance index, calibration plots and decision curve analysis were used to evaluate the model. Results Multivariate Cox regression analysis showed that BRAF V600E status, lymph node metastasis, sex, tumor size, margin, and surgical procedure were independent prognostic factors. In the validation set, the concordance index of the nomogram was 0.774 (95% confidence interval: 0.703–0.845). Calibration plots at 3 and 5 years showed no apparent difference between predicted SIR probability and the actual SIR proportion. Additionally, the nomogram had good net clinical benefit according to the decision curve analysis compared with cases that were treat-all or treat-none. Conclusion We build a nomogram to predict individualized outcomes and help postoperative surveillance in PTC patients.