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You have completed the current stage of cancer treatment, after which you need to check regularly and pay attention to nutrition. So we started this study to see if AI could help with nutrition management. Main options: Option 1: Use AI to assist nutrition management; Option 2: Contact the nutritionist team of the hospital for nutrition management according to your own situation. Option 3: Do not adopt the first two management methods. Special Statement: Please choose; Cancer screening data is used for statistical analysis, but does not reveal any personal privacy.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| group 1: Use AI to assist nutrition management | Experimental | The first step: Preliminary clinical nutrition screening and evaluation. Information of patients' age, stage of nasopharyngeal cancer, treatment stage (radiotherapy, chemotherapy stage) and other information were collected, and the management plan was determined. The second step: AI-assisted HEN management mode. Regular nutritional monitoring and follow-up of patients were conducted by means of intelligent computer, intelligent App body fat device and mobile communication network collection, and basic signs, nutritional status, nutritional risks and implementation of support programs of patients were managed. Nutritional analysis model and index model are used to start the intelligent daily monitoring management and acute attack early warning mechanism. The third step: Monitor and alert. The AI system popularized the basic knowledge of nutrition to patients through the App platform. |
|
| group 2: Contact the nutritionist team of the hospital for nutrition management | Experimental | Contact the nutritionist team of the hospital for nutrition management according to patients' own situation |
|
| group 3: Do not adopt the two management methods. | No Intervention | blank control group |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| group 1: Use AI to assist nutrition management | Other | group1：AI-assisted nutrition management. group 2：Traditional nutrition management（through the hospital dietitian）.group 3:control. |
| Measure | Description | Time Frame |
|---|---|---|
| Survival Rate | Survival Rate | three years after treatment |
| Local Recurrence Rate | Local Recurrence Rate | three years after treatment |
| Measure | Description | Time Frame |
|---|---|---|
| DNA positive rate of Epstein-Barr(EB) virus | DNA positive rate of Epstein-Barr(EB) virus | three years after treatment |
| Body mass index | Data was obtained through the intelligent body fat device |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| First Affiliated Hospital of Zhengzhou University | Zhengzhou | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31636002 | Result | Kulkarni S, Seneviratne N, Baig MS, Khan AHA. Artificial Intelligence in Medicine: Where Are We Now? Acad Radiol. 2020 Jan;27(1):62-70. doi: 10.1016/j.acra.2019.10.001. Epub 2019 Oct 19. | |
| 36912121 | Result | Mundi MS, Mohamed Elfadil O, Olson DA, Pattinson AK, Epp LM, Miller LD, Seegmiller SL, Schneckloth JM, Baker MR, Abdelmagid MG, Patel A, Wescott BA, Elder LS, Hagenbrock MC, Sefried LE, Hurt RT. Home enteral nutrition: A descriptive study. JPEN J Parenter Enteral Nutr. 2023 May;47(4):550-562. doi: 10.1002/jpen.2498. Epub 2023 Apr 12. |
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Publish the paper publicly so that more people can learn about the results of the study
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| group 2：Traditional nutrition management（through the hospital dietitian） | Other | group 2：Traditional nutrition management（through the hospital dietitian） |
|
| three years after treatment |
| 35007816 | Result | Bischoff SC, Austin P, Boeykens K, Chourdakis M, Cuerda C, Jonkers-Schuitema C, Lichota M, Nyulasi I, Schneider SM, Stanga Z, Pironi L. ESPEN practical guideline: Home enteral nutrition. Clin Nutr. 2022 Feb;41(2):468-488. doi: 10.1016/j.clnu.2021.10.018. Epub 2021 Nov 24. |
| 33946039 | Result | Muscaritoli M, Arends J, Bachmann P, Baracos V, Barthelemy N, Bertz H, Bozzetti F, Hutterer E, Isenring E, Kaasa S, Krznaric Z, Laird B, Larsson M, Laviano A, Muhlebach S, Oldervoll L, Ravasco P, Solheim TS, Strasser F, de van der Schueren M, Preiser JC, Bischoff SC. ESPEN practical guideline: Clinical Nutrition in cancer. Clin Nutr. 2021 May;40(5):2898-2913. doi: 10.1016/j.clnu.2021.02.005. Epub 2021 Mar 15. |
| 39839291 | Derived | Liu J, Wang X, Ye X, Chen D. Improved health outcomes of nasopharyngeal carcinoma patients 3 years after treatment by the AI-assisted home enteral nutrition management. Front Nutr. 2025 Jan 7;11:1481073. doi: 10.3389/fnut.2024.1481073. eCollection 2024. |
| ID | Term |
|---|---|
| D009369 | Neoplasms |
| D002277 | Carcinoma |
| ID | Term |
|---|---|
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |
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