About this trial
An AI model was developed to predict the likelihood of distant metastasis in patients with nasopharyngeal cancer based on pathology slides and MRI scans of the primary tumor. The model was validated using data from multiple centers. It was then applied to patients with advanced stages who were recommended to undergo PET/CT scans based on the NCCN or CSCO guidelines. This AI model can accurately screen patients with high risk of distant metastasis at the time of initial diagnosis to receive PET/CT, avoid excessive examination of patients with low risk of distant metastasis, save medical resources and reduce the economic burden on patients.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
None
Disqualifiers
None
Trial population
Patients with pathologically confirmed nasopharyngeal carcinoma
Trial design
Cohort
Prospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
Negative predictive value
NPV measures the proportion of predicted negative cases that are actually negative. It tells us how reliable the model is when it predicts a negative outcome.
Secondary outcomes
Sensitivity, specificity, and positive predictive value
Sensitivity, specificity, and positive predictive value of AI in predicting distant metastasis at the threshold corresponding to a negative predictive value of 95%.
Sponsors and contacts
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Sun Yat-sen University
Lead sponsor
First Affiliated Hospital, Sun Yat-Sen University
Collaborator
Fifth Affiliated Hospital, Sun Yat-Sen University
Collaborator
Affiliated Cancer Hospital & Institute of Guangzhou Medical University
Collaborator
The Affiliated Panyu Center Hospital of Guangzhou Medical University
Collaborator
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Collaborator
Qingyuan People's Hospital
Collaborator