MedPath

A Nomogram Model to Predict Central Lymphnode Metastasis in Thyroid Papillary Carcinoma

Completed
Conditions
Thyroid Papillary Carcinoma
Interventions
Other: male
Registration Number
NCT05191927
Lead Sponsor
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Brief Summary

To establish and validate a suitable and practical nomogram for primary hospitals to predict the risk of central lymph node metastasis (CLNM) among thyroid papillary carcinoma (PTC) patients based on clinical and ultrasound characteristics among Chinese population,1000 PTC patients were retrospectively reviewed who underwent bilateral thyroidectomy or lobectomy plus central lymph node dissection(CLND) between June 2014 and September 2019 in Sun Yat-sen Memorial Hospital (Guangzhou, South China), and then LASSO regression analysis was performed to screen out the possible predictors. Another 200 PTC patients from the First Affiliated Hospital of Zhengzhou University (Zhengzhou, North China) who underwent bilateral thyroidectomy or lobectomy plus CLND between March 2019 and November 2020 were enrolled to construct the nomogram. The area under the receiver operating characteristic (ROC) curves (AUC), calibration curves and decision curve analysis (DCA) were used to evaluate the nomogram.

Detailed Description

1000 Patients who underwent total thyroidectomy or lobectomy and were diagnosed as PTC by pathological examination between June 2014 and September 2019 in Sun Yat-sen Memorial Hospital (Guangzhou, South China) and 200 patients in the First Affiliated Hospital of Zhengzhou University (Zhengzhou, North China) from March 2019 to November 2020 were selected as the subjects to construct the nomogram. 1000 patients were randomized at 7:3 and divided into a training set and a verification set. Besides, 200 cases that met the inclusion and exclusion criteria above-mentioned in the First affiliated Hospital of Zhengzhou University were enrolled as a external verification set.

The following clinical features for each patient were obtained before surgery: gender, age, occupation, complicated with autoimmune diseases (absent / present), history of radiation exposure (absent / present), family history of thyroid cancer (absent / present), with other tumors (absent / present) and preoperative laboratory examinations including neutrophil count, lymphocyte count, platelet count, thyroid-stimulating hormone (TSH), free triiodothyronine (fT3), free thyroxine (fT4), anti-thyroglobulin antibody (TgAb), thyroid peroxidase antibody (TPOAb).

Preoperative US signatures of thyroid tumors were also included: distribution (unilateral / bilateral), shape (regular / irregular), maximum diameter, number (single / multiple), boundary(clear /heliclear / unclear), component (solid /cystic-solid), calcification (absent / microcalcification / macrocalcification), blood flow (absent / internal / annular), cervical lymph node enlargement (absent / present).

A nomogram were established for predicting CLNM based on the universally available baseline Characteristics of PTC patients at a tertiary hospital in South China and externally validate it with data from North China. Odd ratios (ORs), 95% confidence interval (CI) and probability values were obtained by logistic regression analysis. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated to evaluate the accuracy of the nomogram for predicting CLNM. The calibration curve and Hosmer-Lemeshow tests were performed to evaluate the calibration of the nomogram. The decision curve analysis (DCA) was applied to validate clinical utility of the nomogram.

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
1200
Inclusion Criteria
  • underwent TC operation for the first time
  • confirmed as PTC by postoperative pathological examination
  • underwent ipsilateral or bilateral CLND
Exclusion Criteria
  • complicated with other subtypes of TC or thyroid metastatic cancer
  • received preoperative interventional therapy (such as radiofrequency and microwave therapy) or head and neck radiotherapy

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
male groupmaleall are male
Primary Outcome Measures
NameTimeMethod
Multivariate logistic regression analysis1day

Multivariate logistic regression analysis were conducted to determine the potential nonlinear association between predictors and and the risk of CLNM.

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Sun Yat-sen Memorial Hospital of Sun Yat-Sen University

🇨🇳

Guangzhou, Guangdong, China

© Copyright 2025. All Rights Reserved by MedPath