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Nomogram to predict central lymph node metastasis in papillary thyroid carcinoma.

Dehui Qiao1, Xian Deng1, Ruichen Liang2

  • 1Department of Thyroid Surgery, Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Luzhou, 646000, Sichuan Province, China.

Clinical & Experimental Metastasis
|April 3, 2024
PubMed
Summary

A new nomogram effectively predicts central lymph node metastasis in papillary thyroid carcinoma (PTC). This tool aids surgeons in making personalized treatment decisions for PTC patients, improving clinical outcomes.

Keywords:
Central lymph node metastasisNomogramPapillary thyroid carcinomaSurgical strategies

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Area of Science:

  • Oncology
  • Surgical Oncology
  • Diagnostic Imaging

Background:

  • Central lymph node metastasis (CLNM) is a frequent occurrence in papillary thyroid carcinoma (PTC).
  • Accurate prediction of CLNM is crucial for effective patient management and surgical planning.

Purpose of the Study:

  • To develop and validate a predictive nomogram for CLNM in PTC patients.
  • To identify independent risk factors associated with CLNM in PTC.

Main Methods:

  • Retrospective analysis of 1,392 PTC patients, divided into training (1,009) and validation (383) cohorts.
  • Logistic regression analysis to identify risk factors, including inflammatory indicators, ultrasonic, and pathological characteristics.
  • Construction and validation of a nomogram using C-index and calibration curves.

Main Results:

  • The nomogram demonstrated good predictive discrimination (C-index = 0.809) and calibration.
  • Independent risk factors for CLNM included Hashimoto's thyroiditis, calcification, multifocality, capsule invasion, platelet-lymphocyte ratio ≤ 130.34, large tumors, and middle/lower tumor positions.
  • Decision curve analysis indicated improved net clinical benefit for the nomogram.

Conclusions:

  • A validated nomogram can accurately predict CLNM in PTC.
  • The nomogram assists surgeons in personalized clinical decision-making for PTC management.
  • Identification of key risk factors provides insights into PTC metastasis patterns.