Assessment of Antioxidant Enzyme Superoxide Dismutase (SOD) in Oral Cancer: Systematic Review and Meta-Analysis

Abstract

Objective. The present article aims to comprehensively review the existing literature on superoxide dismutase (SOD) levels, an antioxidant enzyme, in oral cancer. Method. An extensive literature search was conducted across various databases, including PubMed, Wiley Online Library, Science Direct, and Cross Reference, spanning 1998–2023. At the outset, 1,177 articles were initially identified, and 907 studies were excluded due to irrelevance or duplication of the research question. Subsequently, 270 articles underwent screening evaluation, resulting in the selection of 85 articles meeting the inclusion criteria. Following this, 68 articles underwent a full-text comprehensive assessment, and ultimately, 39 were chosen for data extraction. The risk of bias in the designated articles was assessed using the Newcastle–Ottawa Scale. Finally, 13 studies were meticulously selected, offering consistent data for the ensuing meta-analysis. Meta-analysis was executed using comprehensive meta-analysis (CMA) version 3 software (Bio Stat Inc., Englewood, NJ, USA). The meta-analysis findings revealed a statistically significant decrease in SOD levels in both erythrocyte samples ($P<0.001$) and tissue samples ($P<0.05$) among individuals with oral cancer (OSCC) compared to the normal control group. Conversely, the analysis of three studies on salivary samples demonstrated a significant increase ($P<0.05$) in SOD levels in the oral cancer group compared to the healthy controls. Conclusion. This systematic review underscores a statistically significant decline in SOD levels observed across diverse bio-samples in individuals with oral cancer, indicating an excess of oxidative stress (OS). Additional research is needed to delve into the relationship between SOD levels and clinic–pathological prognostic markers within the oral cancer cohort. Such investigations have the potential to significantly contribute to the development of prognostic tools grounded in OS, thereby guiding strategies for treatment planning.