Adam Galazka

Dr. Adam Galazka


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 July 2025 in Cancers
Verified
Journal Article
Open access
PDF file
KSKatarzyna Stawarz
Katarzyna Stawarz
KBKarolina Bieńkowska-Pluta
Karolina Bieńkowska-Pluta
AGAdam Galazka
Adam Galazka
AGAnna Gorzelnik
Anna Gorzelnik
MDMonika Durzynska
Monika Durzynska
JZJakub Zwoliński
Jakub Zwoliński
Background: Despite advances in treatment, oral squamous cell carcinoma (OSCC) remains associated with high recurrence and mortality rates. Traditional TNM staging, while foundational, may not fully capture tumor aggressiveness. This study aimed to identify clinical and histopathological predictors of survival to enhance risk stratification and guide treatment planning in OSCC patients. Methods: A retrospective study of 100 patients with confirmed OSCC treated surgically with curative intent between January 2019 and January 2024 was analyzed. Clinicopathologic variables—including tumor volume, angioinvasion, perineural invasion, lymphatic invasion, and nodal status—were evaluated. Disease-specific survival (DSS) was assessed using Kaplan–Meier estimates, Cox regression, and logistic regression models. Results: The cohort had a mean age of 62.1 years, with a 46% OS rate and 43% DSS at study end. Perineural invasion (44%) and lymphatic invasion (42%) were the most common invasive features. Kaplan–Meier analysis revealed significantly reduced DSS in patients with angioinvasion, perineural invasion, and pN+ status. Multivariate logistic regression identified perineural invasion (OR = 3.93, p = 0.0023) and pN+ status (OR = 2.74, p = 0.0284) as independent predictors of cancer-specific mortality. Tumor volume was significantly associated with lymphatic invasion but not directly with DSS. Conclusions: Perineural invasion, angioinvasion, lymph node involvement, and tumor volume are important prognostic markers in OSCC, offering critical information beyond TNM staging. Incorporating these features into risk assessment models could improve prognostic accuracy and inform more individualized treatment strategies for high-risk OSCC patients.