Nasopharyngeal CarcinomaNCT06129201
Development of a Machine Learning Model for Nasopharyngeal Carcinoma Screening Based on Tongue Imaging
An observational study of Nasopharyngeal Carcinoma, run by Fifth Affiliated Hospital, Sun Yat-Sen University at 1 site in China.
Trial 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%. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Nasopharyngeal Carcinoma
- What is being tested?
- Tongue image
- How many people
- 5,000 participants
- Where
- 1 siteChina
- Study dates
- 15 Nov 2023to 1 Dec 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: This study plans to include a training group consisting of 600 newly diagnosed nasopharyngeal carcinoma patients and 800 healthy individuals, as well as 800 individuals with common nasopharyngeal diseases and other tumors. According to the training group: validation group=6:4, configure the number of validation group members. There are approximately 5000 people in total.
Who may be able to join
- Cancer patients confirmed by histology/cytology
- Patients with nasopharyngeal carcinoma in the training group are initially diagnosed
- Subjects voluntarily participate in the study
Who cannot join
- Subjects taking medication or diet may affect their tongue image (such as aluminum magnesium carbonate, traditional Chinese medicine rhubarb, etc.)
- The researchers determined that the subjects had other factors that could force them to terminate the study.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Development of a Machine Learning Model for Nasopharyngeal Carcinoma Screening Based on Tongue Imaging: a Prospective Multicenter Cross-sectional Study
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.
Read the detailed description
Nasopharyngeal cancer is common in China, Southeast Asia, and North Africa, and is generally 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%. In previous studies, researchers found that participants who underwent screening were more likely to achieve long-term survival after being diagnosed with nasopharyngeal carcinoma compared to the control group, and the risk of nasopharyngeal carcinoma specific death was lower among screened patients (relative risk 0.22). 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%. More than 95% of high-risk participants identified through primary serological screening underwent unnecessary and time-consuming clinical examinations and follow-up. The combination of various biomarkers, multi-step screening, and identification of new biomarkers are used to improve the performance of nasopharyngeal cancer screening strategies. However, the progress achieved so far is still unsatisfactory, characterized by low sensitivity, complex operation, or high cost. Therefore, there is an urgent need to identify new biomarkers or strategies with high sensitivity and positive predictive value for nasopharyngeal carcinoma screening.
In 《The New England Journal of Medicine》 in 2023, Professor Xia Ningshao's team reported on the identification and validation of anti BNLF2 total antibody (P85Ab) as a new serological biomarker for nasopharyngeal cancer screening.The sensitivity of P85-Ab nasopharyngeal carcinoma is 97.9%, with a positive predictive value of 10.0%. Furthermore, on the basis of P85-Ab positivity, if further detection of EB double antibodies (EBV nuclear antigen 1 [EBNA1]-IgA and EBV-specific viral capsid antigen [VCA]-IgA) is carried out, intermediate or medium high risk individuals with EB double antibodies can undergo nasopharyngoscopy examination, which can increase the positive predictive value of nasopharyngeal carcinoma screening to 29.6% -44.6%, that is, for every 2-3 nasopharyngoscopes performed, one case of nasopharyngeal carcinoma can be diagnosed. The sensitivity of this study is very high, but the positive predictive value is only 10%. Even when combined with traditional EB dual antibody monitoring and nasal endoscopy, one-third to one-half of non nasopharyngeal carcinoma patients still undergo unnecessary and time-consuming clinical examinations. Therefore, it is still necessary to explore simple and cost-effective methods to improve the strategy of 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
- Being tested
- Tongue image
- Keywords
- Artificial Intelligence， Tongue Image
- Medical subject headings
- Nasopharyngeal Carcinoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Tongue imageOther
Using intelligent imaging devices to collect subject tongue images
| Study group | Role | What they receive |
|---|---|---|
| Training group | Experimental group: population of initially diagnosed nasopharyngeal carcinoma [600 people]; Control group: 2400 healthy individuals+nasopharyngeal disease patients+other tumors. Receives: Other: Tongue image | |
| Validation group | Validation group: Experimental group: Nasopharyngeal cancer population [400 people]; Control group: 1600 healthy individuals+patients with nasopharyngeal diseases+other tumors. Receives: Other: Tongue image |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area Under Curve (AUC) of Diagnostic Model
Determine the screening effectiveness of the nasopharyngeal carcinoma tongue image model
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Nov 2023
- Study start15 Nov 2023 (estimated)
- Primary completion15 Nov 2024 (estimated)
- Study completion1 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (16)Papers the sponsor has linked to this study.
- Other trials for Nasopharyngeal CarcinomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 5,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fifth Affiliated Hospital, Sun Yat-Sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Qi Zeng, Doctor, Principal investigator, Fifth Affiliated Hospital, Sun Yat-Sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06129201
- Sponsor's protocol ID
- ZDWY.ZYZLK.006
- Status last verified
- Nov 2023
- First submitted
- 2 Nov 2023
- Last updated
- 13 Nov 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015 Mar;65(2):87-108. doi: 10.3322/caac.21262. Epub 2015 Feb 4.
PubMed 25651787Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J. Nasopharyngeal carcinoma. Lancet. 2019 Jul 6;394(10192):64-80. doi: 10.1016/S0140-6736(19)30956-0. Epub 2019 Jun 6.
PubMed 31178151Zeng Y, Zhang LG, Wu YC, Huang YS, Huang NQ, Li JY, Wang YB, Jiang MK, Fang Z, Meng NN. Prospective studies on nasopharyngeal carcinoma in Epstein-Barr virus IgA/VCA antibody-positive persons in Wuzhou City, China. Int J Cancer. 1985 Nov 15;36(5):545-7. doi: 10.1002/ijc.2910360505.
PubMed 4055129Liu Z, Ji MF, Huang QH, Fang F, Liu Q, Jia WH, Guo X, Xie SH, Chen F, Liu Y, Mo HY, Liu WL, Yu YL, Cheng WM, Yang YY, Wu BH, Wei KR, Ling W, Lin X, Lin EH, Ye W, Hong MH, Zeng YX, Cao SM. Two Epstein-Barr virus-related serologic antibody tests in nasopharyngeal carcinoma screening: results from the initial phase of a cluster randomized controlled trial in Southern China. Am J Epidemiol. 2013 Feb 1;177(3):242-50. doi: 10.1093/aje/kws404. Epub 2012 Dec 19.
PubMed 23255783Ji MF, Sheng W, Cheng WM, Ng MH, Wu BH, Yu X, Wei KR, Li FG, Lian SF, Wang PP, Quan W, Deng L, Li XH, Liu XD, Xie YL, Huang SJ, Ge SX, Huang SL, Liang XJ, He SM, Huang HW, Xia SL, Ng PS, Chen HL, Xie SH, Liu Q, Hong MH, Ma J, Yuan Y, Xia NS, Zhang J, Cao SM. Incidence and mortality of nasopharyngeal carcinoma: interim analysis of a cluster randomized controlled screening trial (PRO-NPC-001) in southern China. Ann Oncol. 2019 Oct 1;30(10):1630-1637. doi: 10.1093/annonc/mdz231.
PubMed 31373615Chan KCA, Woo JKS, King A, Zee BCY, Lam WKJ, Chan SL, Chu SWI, Mak C, Tse IOL, Leung SYM, Chan G, Hui EP, Ma BBY, Chiu RWK, Leung SF, van Hasselt AC, Chan ATC, Lo YMD. Analysis of Plasma Epstein-Barr Virus DNA to Screen for Nasopharyngeal Cancer. N Engl J Med. 2017 Aug 10;377(6):513-522. doi: 10.1056/NEJMoa1701717.
PubMed 28792880Miller JA, Le QT, Pinsky BA, Wang H. Cost-Effectiveness of Nasopharyngeal Carcinoma Screening With Epstein-Barr Virus Polymerase Chain Reaction or Serology in High-Incidence Populations Worldwide. J Natl Cancer Inst. 2021 Jul 1;113(7):852-862. doi: 10.1093/jnci/djaa198.
PubMed 33351145Simon J, Liu Z, Brenner N, Yu KJ, Hsu WL, Wang CP, Chien YC, Coghill AE, Chen CJ, Butt J, Proietti C, Doolan DL, Hildesheim A, Waterboer T. Validation of an Epstein-Barr Virus Antibody Risk Stratification Signature for Nasopharyngeal Carcinoma by Use of Multiplex Serology. J Clin Microbiol. 2020 Apr 23;58(5):e00077-20. doi: 10.1128/JCM.00077-20. Print 2020 Apr 23.
PubMed 32102852Coghill AE, Pfeiffer RM, Proietti C, Hsu WL, Chien YC, Lekieffre L, Krause L, Teng A, Pablo J, Yu KJ, Lou PJ, Wang CP, Liu Z, Chen CJ, Middeldorp J, Mulvenna J, Bethony J, Hildesheim A, Doolan DL. Identification of a Novel, EBV-Based Antibody Risk Stratification Signature for Early Detection of Nasopharyngeal Carcinoma in Taiwan. Clin Cancer Res. 2018 Mar 15;24(6):1305-1314. doi: 10.1158/1078-0432.CCR-17-1929. Epub 2018 Jan 4.
PubMed 29301829He YQ, Wang TM, Ji M, Mai ZM, Tang M, Wang R, Zhou Y, Zheng Y, Xiao R, Yang D, Wu Z, Deng C, Zhang J, Xue W, Dong S, Zhan J, Cai Y, Li F, Wu B, Liao Y, Zhou T, Zheng M, Jia Y, Li D, Cao L, Yuan L, Zhang W, Luo L, Tong X, Wu Y, Li X, Zhang P, Zheng X, Zhang S, Hu Y, Qin W, Deng B, Liang X, Fan P, Feng Y, Song J, Xie SH, Chang ET, Zhang Z, Huang G, Xu M, Feng L, Jin G, Bei J, Cao S, Liu Q, Kozlakidis Z, Mai H, Sun Y, Ma J, Hu Z, Liu J, Lung ML, Adami HO, Shen H, Ye W, Lam TH, Zeng YX, Jia WH. A polygenic risk score for nasopharyngeal carcinoma shows potential for risk stratification and personalized screening. Nat Commun. 2022 Apr 12;13(1):1966. doi: 10.1038/s41467-022-29570-4.
PubMed 35414057Zhou X, Cao SM, Cai YL, Zhang X, Zhang S, Feng GF, Chen Y, Feng QS, Chen Y, Chang ET, Liu Z, Adami HO, Liu J, Ye W, Zhang Z, Zeng YX, Xu M. A comprehensive risk score for effective risk stratification and screening of nasopharyngeal carcinoma. Nat Commun. 2021 Aug 31;12(1):5189. doi: 10.1038/s41467-021-25402-z.
PubMed 34465768Lam WKJ, Jiang P, Chan KCA, Cheng SH, Zhang H, Peng W, Tse OYO, Tong YK, Gai W, Zee BCY, Ma BBY, Hui EP, Chan ATC, Woo JKS, Chiu RWK, Lo YMD. Sequencing-based counting and size profiling of plasma Epstein-Barr virus DNA enhance population screening of nasopharyngeal carcinoma. Proc Natl Acad Sci U S A. 2018 May 29;115(22):E5115-E5124. doi: 10.1073/pnas.1804184115. Epub 2018 May 14.
PubMed 29760067Lam WKJ, Jiang P, Chan KCA, Peng W, Shang H, Heung MMS, Cheng SH, Zhang H, Tse OYO, Raghupathy R, Ma BBY, Hui EP, Chan ATC, Woo JKS, Chiu RWK, Lo YMD. Methylation analysis of plasma DNA informs etiologies of Epstein-Barr virus-associated diseases. Nat Commun. 2019 Jul 22;10(1):3256. doi: 10.1038/s41467-019-11226-5.
PubMed 31332191Chen GH, Liu Z, Yu KJ, Coghill AE, Chen XX, Xie SH, Lin DF, Huang QH, Lu YQ, Ling W, Lin CY, Lu ZJ, Fan YY, Tang LQ, Sampson JN, Li H, King AD, Middeldorp JM, Hildesheim A, Cao SM. Utility of Epstein-Barr Virus DNA in Nasopharynx Swabs as a Reflex Test to Triage Seropositive Individuals in Nasopharyngeal Carcinoma Screening Programs. Clin Chem. 2022 Jul 3;68(7):953-962. doi: 10.1093/clinchem/hvac032.
PubMed 35325087Li T, Li F, Guo X, Hong C, Yu X, Wu B, Lian S, Song L, Tang J, Wen S, Gao K, Hao M, Cheng W, Su Y, Zhang S, Huang S, Fang M, Wang Y, Ng MH, Chen H, Luo W, Ge S, Zhang J, Xia N, Ji M. Anti-Epstein-Barr Virus BNLF2b for Mass Screening for Nasopharyngeal Cancer. N Engl J Med. 2023 Aug 31;389(9):808-819. doi: 10.1056/NEJMoa2301496.
PubMed 37646678
Study at a glance
From the registry record, last updated by the sponsor on 13 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Machine Learning Model for Nasopharyngeal Carcinoma Screening Based on Tongue Imaging: a Prospective Multicenter Cross-sectional Study
- ClinicalTrials.gov ID
- NCT06129201
- Acronym / sponsor ID
- ZDWY.ZYZLK.006
- Conditions
- Nasopharyngeal Carcinoma
- Keywords
- Artificial Intelligence， Tongue Image
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 5,000 participants (estimated)
- Lead sponsor
- Fifth Affiliated Hospital, Sun Yat-Sen UniversityUniversity, hospital or other
- Study start
- 15 Nov 2023 (estimated)
- Primary completion
- 15 Nov 2024 (estimated)
- Study completion
- 1 Dec 2025 (estimated)
- First posted
- 13 Nov 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Nasopharyngeal cancer is common in China, Southeast Asia, and North Africa, and is generally 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%. In previous studies, researchers found that participants who underwent screening were more likely to achieve long-term survival after being diagnosed with nasopharyngeal carcinoma compared to the control group, and the risk of nasopharyngeal carcinoma specific death was lower among screened patients (relative risk 0.22). 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%. More than 95% of high-risk participants identified through primary serological screening underwent unnecessary and time-consuming clinical examinations and follow-up. The combination of various biomarkers, multi-step screening, and identification of new biomarkers are used to improve the performance of nasopharyngeal cancer screening strategies. However, the progress achieved so far is still unsatisfactory, characterized by low sensitivity, complex operation, or high cost. Therefore, there is an urgent need to identify new biomarkers or strategies with high sensitivity and positive predictive value for nasopharyngeal carcinoma screening.
In 《The New England Journal of Medicine》 in 2023, Professor Xia Ningshao's team reported on the identification and validation of anti BNLF2 total antibody (P85Ab) as a new serological biomarker for nasopharyngeal cancer screening.The sensitivity of P85-Ab nasopharyngeal carcinoma is 97.9%, with a positive predictive value of 10.0%. Furthermore, on the basis of P85-Ab positivity, if further detection of EB double antibodies (EBV nuclear antigen 1 [EBNA1]-IgA and EBV-specific viral capsid antigen [VCA]-IgA) is carried out, intermediate or medium high risk individuals with EB double antibodies can undergo nasopharyngoscopy examination, which can increase the positive predictive value of nasopharyngeal carcinoma screening to 29.6% -44.6%, that is, for every 2-3 nasopharyngoscopes performed, one case of nasopharyngeal carcinoma can be diagnosed. The sensitivity of this study is very high, but the positive predictive value is only 10%. Even when combined with traditional EB dual antibody monitoring and nasal endoscopy, one-third to one-half of non nasopharyngeal carcinoma patients still undergo unnecessary and time-consuming clinical examinations. Therefore, it is still necessary to explore simple and cost-effective methods to improve the strategy of 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.
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Training group | – | Other: Tongue imageExperimental group: population of initially diagnosed nasopharyngeal carcinoma [600 people]; Control group: 2400 healthy individuals+nasopharyngeal disease patients+other tumors. |
| Validation group | – | Other: Tongue imageValidation group: Experimental group: Nasopharyngeal cancer population [400 people]; Control group: 1600 healthy individuals+patients with nasopharyngeal diseases+other tumors. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- This study plans to include a training group consisting of 600 newly diagnosed nasopharyngeal carcinoma patients and 800 healthy individuals, as well as 800 individuals with common nasopharyngeal diseases and other tumors. According to the training group: validation group=6:4, configure the number of validation group members. There are approximately 5000 people in total.
Key inclusion criteria (3 listed)
- Cancer patients confirmed by histology/cytology
- Patients with nasopharyngeal carcinoma in the training group are initially diagnosed
- Subjects voluntarily participate in the study
Key exclusion criteria (2 listed)
- Subjects taking medication or diet may affect their tongue image (such as aluminum magnesium carbonate, traditional Chinese medicine rhubarb, etc.)
- The researchers determined that the subjects had other factors that could force them to terminate the study.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Tongue imageUsing intelligent imaging devices to collect subject tongue images | Other | Training group, Validation group |
Primary outcome
Area Under Curve (AUC) of Diagnostic Model
Time frame: 12 months
Determine the screening effectiveness of the nasopharyngeal carcinoma tongue image model
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Nov 2023.
- Background: PubMed 25651787Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015 Mar;65(2):87-108. doi: 10.3322/caac.21262. Epub 2015 Feb 4.
- Background: PubMed 31178151Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J. Nasopharyngeal carcinoma. Lancet. 2019 Jul 6;394(10192):64-80. doi: 10.1016/S0140-6736(19)30956-0. Epub 2019 Jun 6.
- Background: PubMed 4055129Zeng Y, Zhang LG, Wu YC, Huang YS, Huang NQ, Li JY, Wang YB, Jiang MK, Fang Z, Meng NN. Prospective studies on nasopharyngeal carcinoma in Epstein-Barr virus IgA/VCA antibody-positive persons in Wuzhou City, China. Int J Cancer. 1985 Nov 15;36(5):545-7. doi: 10.1002/ijc.2910360505.
- Background: PubMed 23255783Liu Z, Ji MF, Huang QH, Fang F, Liu Q, Jia WH, Guo X, Xie SH, Chen F, Liu Y, Mo HY, Liu WL, Yu YL, Cheng WM, Yang YY, Wu BH, Wei KR, Ling W, Lin X, Lin EH, Ye W, Hong MH, Zeng YX, Cao SM. Two Epstein-Barr virus-related serologic antibody tests in nasopharyngeal carcinoma screening: results from the initial phase of a cluster randomized controlled trial in Southern China. Am J Epidemiol. 2013 Feb 1;177(3):242-50. doi: 10.1093/aje/kws404. Epub 2012 Dec 19.
- Background: PubMed 31373615Ji MF, Sheng W, Cheng WM, Ng MH, Wu BH, Yu X, Wei KR, Li FG, Lian SF, Wang PP, Quan W, Deng L, Li XH, Liu XD, Xie YL, Huang SJ, Ge SX, Huang SL, Liang XJ, He SM, Huang HW, Xia SL, Ng PS, Chen HL, Xie SH, Liu Q, Hong MH, Ma J, Yuan Y, Xia NS, Zhang J, Cao SM. Incidence and mortality of nasopharyngeal carcinoma: interim analysis of a cluster randomized controlled screening trial (PRO-NPC-001) in southern China. Ann Oncol. 2019 Oct 1;30(10):1630-1637. doi: 10.1093/annonc/mdz231.
- Background: PubMed 28792880Chan KCA, Woo JKS, King A, Zee BCY, Lam WKJ, Chan SL, Chu SWI, Mak C, Tse IOL, Leung SYM, Chan G, Hui EP, Ma BBY, Chiu RWK, Leung SF, van Hasselt AC, Chan ATC, Lo YMD. Analysis of Plasma Epstein-Barr Virus DNA to Screen for Nasopharyngeal Cancer. N Engl J Med. 2017 Aug 10;377(6):513-522. doi: 10.1056/NEJMoa1701717.
- Background: PubMed 33351145Miller JA, Le QT, Pinsky BA, Wang H. Cost-Effectiveness of Nasopharyngeal Carcinoma Screening With Epstein-Barr Virus Polymerase Chain Reaction or Serology in High-Incidence Populations Worldwide. J Natl Cancer Inst. 2021 Jul 1;113(7):852-862. doi: 10.1093/jnci/djaa198.
- Background: PubMed 32102852Simon J, Liu Z, Brenner N, Yu KJ, Hsu WL, Wang CP, Chien YC, Coghill AE, Chen CJ, Butt J, Proietti C, Doolan DL, Hildesheim A, Waterboer T. Validation of an Epstein-Barr Virus Antibody Risk Stratification Signature for Nasopharyngeal Carcinoma by Use of Multiplex Serology. J Clin Microbiol. 2020 Apr 23;58(5):e00077-20. doi: 10.1128/JCM.00077-20. Print 2020 Apr 23.
- Background: PubMed 29301829Coghill AE, Pfeiffer RM, Proietti C, Hsu WL, Chien YC, Lekieffre L, Krause L, Teng A, Pablo J, Yu KJ, Lou PJ, Wang CP, Liu Z, Chen CJ, Middeldorp J, Mulvenna J, Bethony J, Hildesheim A, Doolan DL. Identification of a Novel, EBV-Based Antibody Risk Stratification Signature for Early Detection of Nasopharyngeal Carcinoma in Taiwan. Clin Cancer Res. 2018 Mar 15;24(6):1305-1314. doi: 10.1158/1078-0432.CCR-17-1929. Epub 2018 Jan 4.
- Background: PubMed 35414057He YQ, Wang TM, Ji M, Mai ZM, Tang M, Wang R, Zhou Y, Zheng Y, Xiao R, Yang D, Wu Z, Deng C, Zhang J, Xue W, Dong S, Zhan J, Cai Y, Li F, Wu B, Liao Y, Zhou T, Zheng M, Jia Y, Li D, Cao L, Yuan L, Zhang W, Luo L, Tong X, Wu Y, Li X, Zhang P, Zheng X, Zhang S, Hu Y, Qin W, Deng B, Liang X, Fan P, Feng Y, Song J, Xie SH, Chang ET, Zhang Z, Huang G, Xu M, Feng L, Jin G, Bei J, Cao S, Liu Q, Kozlakidis Z, Mai H, Sun Y, Ma J, Hu Z, Liu J, Lung ML, Adami HO, Shen H, Ye W, Lam TH, Zeng YX, Jia WH. A polygenic risk score for nasopharyngeal carcinoma shows potential for risk stratification and personalized screening. Nat Commun. 2022 Apr 12;13(1):1966. doi: 10.1038/s41467-022-29570-4.
- Background: PubMed 34465768Zhou X, Cao SM, Cai YL, Zhang X, Zhang S, Feng GF, Chen Y, Feng QS, Chen Y, Chang ET, Liu Z, Adami HO, Liu J, Ye W, Zhang Z, Zeng YX, Xu M. A comprehensive risk score for effective risk stratification and screening of nasopharyngeal carcinoma. Nat Commun. 2021 Aug 31;12(1):5189. doi: 10.1038/s41467-021-25402-z.
- Background: PubMed 29760067Lam WKJ, Jiang P, Chan KCA, Cheng SH, Zhang H, Peng W, Tse OYO, Tong YK, Gai W, Zee BCY, Ma BBY, Hui EP, Chan ATC, Woo JKS, Chiu RWK, Lo YMD. Sequencing-based counting and size profiling of plasma Epstein-Barr virus DNA enhance population screening of nasopharyngeal carcinoma. Proc Natl Acad Sci U S A. 2018 May 29;115(22):E5115-E5124. doi: 10.1073/pnas.1804184115. Epub 2018 May 14.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Qi Zeng, Doctor principal investigator
Fifth Affiliated Hospital, Sun Yat-Sen University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Nasopharyngeal Carcinoma, run by Fifth Affiliated Hospital, Sun Yat-Sen University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 13 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Yulong Zhang, Doctor (18810550602, zhongxiyi1101@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Area Under Curve (AUC) of Diagnostic Model (time frame: 12 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06129201, which also lists 16 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Nov 2023.