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Peripheral blood values as predictors of autoimmune status in oral cavity squamous cell carcinoma

BACKGROUND: Recent literature has highlighted the role of the host in prognosis in oral squamous cell carcinoma (OSCC). Autoimmune (AI) disease represents a macroscopic depiction of host status. The goal of this study was to predict an AI “status” and to analyze the utility of this “status” as a pro...

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Detalles Bibliográficos
Autores principales: Pillai, Anjali, Valero, Cristina, Navas, Kathleen, Morris, Quaid, Patel, Snehal G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441075/
https://www.ncbi.nlm.nih.gov/pubmed/34521033
http://dx.doi.org/10.1016/j.tranon.2021.101220
Descripción
Sumario:BACKGROUND: Recent literature has highlighted the role of the host in prognosis in oral squamous cell carcinoma (OSCC). Autoimmune (AI) disease represents a macroscopic depiction of host status. The goal of this study was to predict an AI “status” and to analyze the utility of this “status” as a prognostic indicator in OSCC. METHODS: From a departmental database of OSCC patients (n = 1377), 125 patients with an AI disorder were identified. PBL values were obtained and standardized for analysis. A LASSO regression model was used to determine the best predictors of AI status and an AI score was developed. The score was then analyzed across various survival endpoints. RESULTS: When AI score was divided into a binary variable, patients in the highest quartile had a significantly worse overall survival (OS), local recurrence-free (LRFP) and distant recurrence-free probability (DRFP). Survival curves showed significant differences for OS, DSS, LRFP, and DRFP. CONCLUSIONS: AI diseases are immune dysregulations that could play a role in prognosis. Therefore, development of an AI score is necessary to depict host status in a ubiquitous manner. AI score as a binary variable may be more utilitarian in a clinical setting, compared to the continuous score. This novel tool needs validation and integration into more tumor and host characteristics. This investigation showed utility of such a score, similar to PBL data in OSCC prognosis. Future studies should incorporate other relevant variables known to affect outcome and implement a more comprehensive predictive model.