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A nomogram model based on the preoperative clinical characteristics of papillary thyroid carcinoma with Hashimoto's
Wanjun Zhao1, Linye He1, Jingqiang Zhu1
1Department of Thyroid Surgery, West China Hospital, Sichuan University, Chengdu, China.
Objective:
Preoperative prediction of central lymph node (LN) metastasis in papillary thyroid carcinoma (PTC) with Hashimoto's thyroiditis (HT) provides an important basis for surgical decision-making, especially regarding the extent of tumour resection. We aimed to develop and validate a nomogram model for the preoperative assessment of central LN metastasis.
Methods:
We retrospectively collected the data of 994 PTC patients with HT who underwent surgery at the West China Hospital from January 2008 to December 2017. Among them, 606 patients who underwent surgeries relatively earlier comprised the training cohort for nomogram development, while the other 388 who underwent surgeries relatively later formed the validation cohort to validate the model's performance. Univariate and multivariate logistic regression analyses were conducted using the data of the two respective cohorts, as well as the data of the combined cohort. The relevant preoperative potential risk factors include demographic characteristics, medical history information, thyroid function test, ultrasound characteristics and BRAF V600E gene detection. A nomogram model was subsequently developed. The performance, discrimination and calibration of the nomogram model were assessed in the training and validation cohorts and in the combined cohort.
Results:
The central LN metastasis rate of PTC with HT was 49.7% (301/606) and 48.7% (193/388) in the training and validation cohorts, respectively. The univariate and multivariate logistic regression analyses indicated that younger age, normal body mass index, BRAF V600E mutation, larger maximum diameter, left lobe tumour, aspect ratio >1, capsular invasion and calcification were significant risk factors for central LN metastasis in PTC patients with HT. The preoperative nomogram showed good calibration and discrimination for the training and validation cohorts, as well as for the combined data set.
Conclusion:
The nomogram we developed and validated with a comprehensive set of preoperative factors is effective in predicting central LN metastasis in PTC patients with HT.
