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Prognostic factors in oral squamous cell Carcinoma patients treated with curative intent: a retrospective cohort study

Grant number: 21/09805-8
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): April 01, 2022
Effective date (End): March 31, 2023
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Gilberto de Castro Junior
Grantee:Lucas Luiz Constantino
Host Institution: Instituto do Câncer do Estado de São Paulo Octavio Frias de Oliveira (ICESP). Coordenadoria de Serviços de Saúde (CSS). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil

Abstract

The prognosis of patients with oral squamous cell Carcinoma (OSCC) is dependent on several factors. The TNM classification (AJCC) in its eighth edition improved its prognostic accuracy by incorporating new variables. More recently, the detrimental impact of inflammation and the presence of sarcopenia on the clinical outcome of OSCC patients treated with curative intent have been well recognized. In addition, the worst pattern of invasion, the presence of budding, and the higher tumor grades are pathological variables associated with worse outcomes in terms of overall survival and disease-free survival in patients treated with surgery with curative intent, followed or not by adjuvant therapies. The treatment of OSCC has a negative cosmetic impact and it is also associated with other dysfunctions (dysphagia, for example), and high costs. Here we hypothesize that the TNM classification used to estimate an individual prognosis can be refined in order to better estimate the prognosis of OSCC patients and to individualize the treatment of patients with CECCO. We aim to investigate, in a retrospective cohort study, the following prognostic markers: TNM staging (AJCC 8th ed.), tumor differentiation grade, the worst pattern of invasion, presence of budding, inflammation, and sarcopenia, and to study their impact on overall survival and disease-free survival. A more precise prognostic characterization may be helpful in treatment selection and to optimize the use of human and material resources.(AU)

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