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

A Nomogram Model to Predict Central Lymphnode Metastasis in Thyroid Papillary Carcinoma Suitable for Primary Hospitals

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.

Study Overview

• Status: Completed
• Conditions: Thyroid Papillary Carcinoma
• Intervention / Treatment: Other: male

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.

• Study Type: Observational
• Enrollment (Actual): 1200

Contacts and Locations

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China
      • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Patients who underwent total thyroidectomy or lobectomy and were diagnosed as PTC by pathological examination in Sun Yat-sen Memorial Hospital (Guangzhou, South China) and in the First Affiliated Hospital of Zhengzhou University (Zhengzhou, North China) .

Description

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 Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Retrospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
female group; all are female
male group; all are male	Other: male; Nine preoperative predictors were identified for the nomogram: gender, age, platelet counts, TPOAb level and US signatures including maximum diameter, boundary, component, calcification and cervical lymph node enlargement.; Other Names: young; high platelet count; low TPOAb level; larger maximum diameter; unclear boundary; solidity; calcification; cervical lymph node enlargement

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Multivariate logistic regression analysis	Multivariate logistic regression analysis were conducted to determine the potential nonlinear association between predictors and and the risk of CLNM.	1day

Collaborators and Investigators

• Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
• Collaborators: The First Affiliated Hospital of Zhengzhou University
• Investigators: Study Chair: mingtong xu, professor, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2020
• Primary Completion (Actual): January 1, 2021
• Study Completion (Actual): August 1, 2021

Study Registration Dates

• First Submitted: November 17, 2021
• First Submitted That Met QC Criteria: December 29, 2021
• First Posted (Actual): January 14, 2022

Study Record Updates

• Last Update Posted (Actual): January 14, 2022
• Last Update Submitted That Met QC Criteria: December 29, 2021
• Last Verified: December 1, 2021

More Information

Terms related to this study

• Keywords: Thyroid Papillary Carcinoma; nomogram; central lymph node metastasis; predictor
• Additional Relevant MeSH Terms: Pathologic Processes; Neoplasms by Histologic Type; Neoplasms; Neoplasms by Site; Adenocarcinoma; Neoplasms, Glandular and Epithelial; Endocrine System Diseases; Endocrine Gland Neoplasms; Head and Neck Neoplasms; Neoplastic Processes; Neoplasms, Squamous Cell; Adenocarcinoma, Papillary; Thyroid Neoplasms; Carcinoma; Neoplasm Metastasis; Thyroid Diseases; Lymphatic Metastasis; Thyroid Cancer, Papillary; Carcinoma, Papillary
• Other Study ID Numbers: NO.SYSEC-KY-KS-2021-180

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No