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A nomogram combining clinical factors and biomarkers for predicting the recurrence of high-risk cutaneous squamous cell carcinoma

BACKGROUND: Although determining the recurrence of cutaneous squamous cell carcinoma (cSCC) is important, currently suggested systems and single biomarkers have limited power for predicting recurrence. OBJECTIVE: In this study, combinations of clinical factors and biomarkers were adapted into a nomo...

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Detalles Bibliográficos
Autores principales: Oh, Yeongjoo, Zheng, Zhenlong, Kim, Ki-Yeol, Xu, Xiangshu, Pei, Meiling, Oh, Byungho, Kim, Sang Kyem, Chung, Kee Yang, Roh, Mi Ryung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632077/
https://www.ncbi.nlm.nih.gov/pubmed/36324094
http://dx.doi.org/10.1186/s12885-022-10213-2
Descripción
Sumario:BACKGROUND: Although determining the recurrence of cutaneous squamous cell carcinoma (cSCC) is important, currently suggested systems and single biomarkers have limited power for predicting recurrence. OBJECTIVE: In this study, combinations of clinical factors and biomarkers were adapted into a nomogram to construct a powerful risk prediction model. METHODS: The study included 145 cSCC patients treated with Mohs micrographic surgery. Clinical factors were reviewed, and immunohistochemistry was performed using tumor tissue samples. A nomogram was constructed by combining meaningful clinical factors and protein markers. RESULTS: Among the various factors, four clinical factors (tumor size, organ transplantation history, poor differentiation, and invasion into subcutaneous fat) and two biomarkers (Axin2 and p53) were selected and combined into a nomogram. The concordance index (C-index) of the nomogram for predicting recurrence was 0.809, which was higher than that for the American Joint Committee on Cancer (AJCC) 7th, AJCC 8th, Brigham and Women’s Hospital, and Breuninger staging systems in the patient data set. CONCLUSION: A nomogram model that included both clinical factors and biomarkers was much more powerful than previous systems for predicting cSCC recurrence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10213-2.