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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06032767
Other study ID # B2022-420-Y01
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date August 14, 2023
Est. completion date December 30, 2024

Study information

Verified date January 2024
Source Sun Yat-sen University
Contact Fang-Yun Xie, M.D.
Phone +8613902205880
Email xiefy@sysucc.org.cn
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The goal of this observational study is to apply the CNN-based DL method to extract the three-dimensional spatial information of IMRT dose distribution to predict the occurrence probability of serious radiotherapy and chemotherapy induced oral mucositis(SRCOM), and compare with a model based on dosimetry, NTCP or doseomics to improve the prediction accuracy of SRCOM, thus guiding the clinical planning design, reducing the occurrence probability of OM, and may have the potential value of preventing serious complications and improving the quality of life in patients with nasopharyngeal carcinoma.


Recruitment information / eligibility

Status Recruiting
Enrollment 480
Est. completion date December 30, 2024
Est. primary completion date September 30, 2024
Accepts healthy volunteers No
Gender All
Age group N/A and older
Eligibility Inclusion Criteria: - Initial diagnosis, pathological histological diagnosis, the pathological type is non-keratotic carcinoma (according to the WHO pathological classification). - Initial intensity-modulated radiotherapy (Intensity modulated radiation therapy, IMRT). - No previous radiotherapy was received. Exclusion Criteria: - Patients with recurrent nasopharyngeal carcinoma. - Radiotherapy plan cannot be obtained. - Previous history of malignancy; previous radiotherapy. - The primary lesion and cervical metastatic lesions have received surgical treatment (except for diagnostic treatment).

Study Design


Intervention

Other:
observational group
patients initially diagnosed with nasopharyngeal carcinoma treated with IMRT

Locations

Country Name City State
China Sun Yat-sen University Cancer Center Guangzhou Guangdong

Sponsors (1)

Lead Sponsor Collaborator
Sun Yat-sen University

Country where clinical trial is conducted

China, 

References & Publications (8)

Elad S, Yarom N, Zadik Y, Kuten-Shorrer M, Sonis ST. The broadening scope of oral mucositis and oral ulcerative mucosal toxicities of anticancer therapies. CA Cancer J Clin. 2022 Jan;72(1):57-77. doi: 10.3322/caac.21704. Epub 2021 Oct 29. — View Citation

Gabrys HS, Buettner F, Sterzing F, Hauswald H, Bangert M. Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia. Front Oncol. 2018 Mar 5;8:35. doi: 10.3389/fonc.201 — View Citation

Ibragimov B, Toesca D, Chang D, Yuan Y, Koong A, Xing L. Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT. Med Phys. 2018 Oct;45(10):4763-4774. doi: 10.1002/mp.13122. Epub 2018 Sep 10. — View Citation

Li K, Yang L, Hu QY, Chen XZ, Chen M, Chen Y. Oral Mucosa Dose Parameters Predicting Grade >/=3 Acute Toxicity in Locally Advanced Nasopharyngeal Carcinoma Patients Treated With Concurrent Intensity-Modulated Radiation Therapy and Chemotherapy: An Indepen — View Citation

Li PJ, Li KX, Jin T, Lin HM, Fang JB, Yang SY, Shen W, Chen J, Zhang J, Chen XZ, Chen M, Chen YY. Predictive Model and Precaution for Oral Mucositis During Chemo-Radiotherapy in Nasopharyngeal Carcinoma Patients. Front Oncol. 2020 Nov 5;10:596822. doi: 10 — View Citation

Soutome S, Yanamoto S, Nishii M, Kojima Y, Hasegawa T, Funahara M, Akashi M, Saito T, Umeda M. Risk factors for severe radiation-induced oral mucositis in patients with oral cancer. J Dent Sci. 2021 Oct;16(4):1241-1246. doi: 10.1016/j.jds.2021.01.009. Epu — View Citation

Wolden SL, Chen WC, Pfister DG, Kraus DH, Berry SL, Zelefsky MJ. Intensity-modulated radiation therapy (IMRT) for nasopharynx cancer: update of the Memorial Sloan-Kettering experience. Int J Radiat Oncol Biol Phys. 2006 Jan 1;64(1):57-62. doi: 10.1016/j.i — View Citation

Zhen X, Chen J, Zhong Z, Hrycushko B, Zhou L, Jiang S, Albuquerque K, Gu X. Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study. Phys Med Biol. 2017 Oct 12;62(21):824 — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary RTOG/EROTC Acute Radiation Reaction Scoring Standard Toxicity records of oral mucosal Reaction in patients are conducted by professionally trained oncologists through radiation therapy, an average of 7 weeks
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