Acute radiation skin injury in stage III-IV head and neck cancer: scale correlates and predictive model.


Journal

World journal of surgical oncology
ISSN: 1477-7819
Titre abrégé: World J Surg Oncol
Pays: England
ID NLM: 101170544

Informations de publication

Date de publication:
25 Jul 2024
Historique:
received: 19 05 2024
accepted: 17 07 2024
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 25 7 2024
Statut: epublish

Résumé

Active radiation skin injury (ARSI) has the highest incidence of acute adverse reactions caused by radiotherapy (RT) in patients with head and neck cancer (HNC). This study aimed to screen risk factors that can facilitate the identification of HNC patients at high risk of ARSI. Data from 255 stage III-IV HNC patients who underwent intensity-modulated radiation therapy (IMRT) were collected. The data from our medical records, including clinical characteristics and hematological indices before RT, were retrospectively collected and arranged. The Common Terminology Criteria for Adverse Events Criteria (CTCAE), Radiation Therapy Oncology Group Criteria (RTOG), World Health Organization Criteria (WHO), Oncology Nursing Society (ONS), Acute Radiation Dermatitis Graduation Scale, Douglas & Fowler and Radiation Dermatitis Severity Scale (RDSS) were used to assess ARSI. Of these, CTCAE was used for further analysis. Binary logistic regression analyses were used to identity risk factors. To establish the correction between each risk factor and the ARSI score, the odds ratio (OR) and 95% confidence interval (CI) were computed. The assessment results of the CTCAE with RTOG, WHO, ONS, Graduation Scale, Douglas & Fowler and RDSS have good consistency. After radiotherapy, 18.4% of patients had at least 3 (3 +) grade ARSI. Multivariate logistic regression analysis revealed that the KPS score, blood glucose level, white blood cell count, and plasma free thyroxine (FT4) concentration were independent risk factors for 3 + grade ARSI. A nomogram was constructed on the basis of these risk factors, which demonstrated good predictive power according to the area under the ROC curve (AUC). The satisfactory consistency and clinical efficacy of the nomogram were confirmed by calibration curves and decision curve analysis (DCA). A low KPS score, high blood glucose level, high white blood cell count, and high thyroid hormone prior to radiotherapy for stage III-IV HNC are independent risk factors for grade 3 + RSI.

Identifiants

pubmed: 39054478
doi: 10.1186/s12957-024-03490-7
pii: 10.1186/s12957-024-03490-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

195

Subventions

Organisme : National Natural Science Foundation of China
ID : 82202958
Organisme : Science Technology Program of Jinan
ID : 202225013
Organisme : China Postdoctoral Science Foundation
ID : 2023M734299

Informations de copyright

© 2024. The Author(s).

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Auteurs

Zihan Zhou (Z)

Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China.

Junjian Lin (J)

Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China.

Ying Wang (Y)

Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China.

Yunhao Chen (Y)

Department of Radiation Oncology, Jiangsu Cancer Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.

Yang Zhang (Y)

Department of Radiation Oncology, Shandong University Cancer Center, Jinan, Shandong, China.

Xingchen Ding (X)

Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China. SDdingxingchen@126.com.

Benhua Xu (B)

Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China. benhuaxu@sina.com.
Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors (Fujian Medical University), Fuzhou, Fujian, China. benhuaxu@sina.com.
Clinical Research Center for Radiology and Radiotherapy of Fujian Province (Digestive, Hematological and Breast Malignancies), Fuzhou, Fujian, China. benhuaxu@sina.com.

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