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

NCT05191927 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1200

Last updated 2022-01-14

No results posted yet for this study

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.

Conditions

  • Thyroid Papillary Carcinoma

Interventions

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.

Sponsors & Collaborators

  • The First Affiliated Hospital of Zhengzhou University

    collaborator OTHER
  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • mingtong xu, professor · Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-01-01
Primary Completion
2021-01-01
Completion
2021-08-01

Countries

  • China

Study Locations

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Read the full study record

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View NCT05191927 on ClinicalTrials.gov