Radiomics Model for Assessing Lymph Node Status in cN0 Patients withHNSCC

NCT06757530 | Completed DMC

• 1 other identifier: 2024-Chenxin
• Study Type: observational
• Target: 700
• Locations: 1 country
• Sites: 1

Brief Summary

Occult lymph node metastasis (LNM) remains one of the most critical and challenging aspects of managing head and neck squamous cell carcinoma (HNSCC). Defined as the presence of metastatic disease in lymph nodes that are clinically undetectable through routine imaging or physical examination, occult LNM has profound implications for treatment planning, prognosis, and overall patient management. In HNSCC, accurate detection and prediction of occult LNM are crucial as they significantly influence decisions regarding the extent of neck dissection, the need for adjuvant therapies, and the overall therapeutic strategy. Undiagnosed or underestimated LNM can result in inadequate treatment, increasing the risk of locoregional recurrence and poor survival outcomes.

Conditions

HNSCC

Keywords

Radiogenomics, Occult lymph node metastasis

Outcome Measures

Primary Outcomes (1)

• AUC

  AUC (Area Under the Curve) is a performance metric used in classification tasks to evaluate the ability of a model to distinguish between classes. Specifically, it measures the area under the Receiver Operating Characteristic (ROC) curve, which plots the true positive rate (sensitivity) against the false positive rate (1-specificity) at various threshold settings.

  The prediction results can be obtained immediately after the model completes processing.

Study Arms (3)

Training set

The training set comprised approximately 500 cN0 patients diagnosed with head and neck squamous cell carcinoma (HNSCC), including approximately 150 patients with lymph node metastasis and approximately 350 patients without metastasis. All patients underwent preoperative contrast-enhanced CT scans.

Diagnostic Test: AI

internal test set

The internal validation set included approximately 150 patients, randomly selected from the training cohort. This set was used for model evaluation and tuning.

Diagnostic Test: AI

external test set

The external validation set consisted of approximately 200 patients with HNSCC. These patients were enrolled from other centers, and their data included preoperative contrast-enhanced CT images. This independent dataset was used to assess the generalizability of the radiomics model.

Diagnostic Test: AI

Interventions

AI DIAGNOSTIC_TEST

Using artificial intelligence models to distinguish between patients with lymph node metastasis and those without lymph node metastasis.

Training set; external test set; internal test set

Eligibility Criteria

• Age: 18 Years - 89 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All patients with pathologically confirmed laryngeal carcinoma between January 2016 and December 2024 from three hospitals were collected and were divided into different test groups.

You may qualify if:

• Availability of complete clinical data;
• Diagnosis of laryngeal squamous cell carcinoma confirmed by surgery or biopsy;
• CT contrast-enhanced examination performed within two weeks prior to surgery.
• All patients underwent neck lymph node dissection surgery.

You may not qualify if:

• Patients who received other treatments before surgery;
• CT images with significant artifacts;
• Patients with tumor recurrence.

Sponsors & Collaborators

• First Affiliated Hospital of Chongqing Medical University: lead
• Zigong The Fourth People's Hospital: collaborator

Study Sites (1)

The First Affiliated Hospital of Chongqing Medical University

Chongqing, China

Location

MeSH Terms

Conditions

Squamous Cell Carcinoma of Head and Neck

Condition Hierarchy (Ancestors)

Carcinoma, Squamous Cell; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Head and Neck Neoplasms; Neoplasms by Site

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Day
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD

Study Record Dates

• First Submitted: December 27, 2024
• First Posted: January 3, 2025
• Study Start: November 27, 2024
• Primary Completion: April 15, 2025
• Study Completion: April 15, 2025
• Last Updated: May 28, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)