Clinical trial · Interventional
Health Outcomes of Nasopharyngeal Carcinoma Patients Three Years After Treatment by the AI-assisted Home Enteral Nutrition Management
NCT06603909CI-TRIAL-00080784completedN/AClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Artificial Intelligence (AI) | — | UNRESOLVED | — |
| Cancer, Carcinoma | Malignant Neoplasm | ALIAS | 0.85 |
| Nutrition | — | UNRESOLVED | — |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| group 1: Use AI to assist nutrition management | Other | — | UNRESOLVED |
| group 2：Traditional nutrition management（through the hospital dietitian） | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- type
- EXPERIMENTAL
- label
- group 1: Use AI to assist nutrition management
- description
- 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.
- interventionNames
- Other: group 1: Use AI to assist nutrition management
- type
- EXPERIMENTAL
- label
- group 2: Contact the nutritionist team of the hospital for nutrition management
- description
- Contact the nutritionist team of the hospital for nutrition management according to patients' own situation
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Malignant tumor patient Exclusion Criteria: * no
References
Publications (5)
- RESULTKulkarni 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. PMID 31636002
- RESULTMundi 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. PMID 36912121
- RESULTBischoff 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. PMID 35007816
- RESULTMuscaritoli 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. PMID 33946039
- DERIVEDLiu 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. PMID 39839291