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Development of a Machine Learning Model for Nasopharyngeal Carcinoma Screening Based on Tongue Imaging

NCT06129201 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 5000

Last updated 2023-11-13

No results posted yet for this study

Summary

Nasopharyngeal cancer is common in China, Southeast Asia, and North Africa, and is usually associated with Epstein-Barr virus (EBV) infection. Using EBV specific antibodies or EBV DNA screening can increase the proportion of patients diagnosed with early nasopharyngeal carcinoma from approximately 20% to over 70%. However, the application of nasopharyngeal carcinoma screening in clinical practice is hindered by low positive predictive values, even in areas where the EB virus is prevalent in China, the positive predictive value is only 4.8%. Therefore, there is an urgent need to identify new biomarkers or strategies with high sensitivity and positive predictive value for nasopharyngeal carcinoma screening.

A study published in the Lancet sub journal 《eClinicalMedicine》 in 2023 showed that a tongue image model based on machine learning can serve as a stable diagnostic method for gastric cancer (AUC=0.89), and has been clinically validated in multiple centers. This study inspires researchers to introduce artificial intelligence machine learning technology into the diagnosis and treatment of nasopharyngeal cancer.

In summary, this plan explores the establishment of tongue image machine learning models in nasopharyngeal carcinoma patients to help improve the positive predictive value of nasopharyngeal carcinoma screening.

Conditions

  • Nasopharyngeal Carcinoma

Interventions

OTHER

Tongue image

Using intelligent imaging devices to collect subject tongue images

Sponsors & Collaborators

  • Fifth Affiliated Hospital, Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • Qi Zeng, Doctor · Fifth Affiliated Hospital, Sun Yat-Sen University

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-11-15
Primary Completion
2024-11-15
Completion
2025-12-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06129201 on ClinicalTrials.gov