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Worst pattern of invasion in oral squamous cell carcinoma: An independent prognostic indicator

J Oral Biol Craniofac Res. 2025 May-Jun;15(3):638-644. doi: 10.1016/j.jobcr.2024.12.008. Epub 2025 Apr 10.

ABSTRACT

INTRODUCTION: Oral squamous cell carcinoma is a malignancy that is biologically aggressive.

OBJECTIVE: To investigate the correlation between various histopathological factors and the worst patterns of invasion at the tumor-host interface, which were classified as cohesive (1-3) and non-cohesive (4&5).

METHODS: Neck dissections were performed on 81 cases of oral squamous cell carcinoma those had been diagnosed. The selection was limited to paraffin-embedded blocks that contained sections from the tumor. Tumor staging, nodal staging and other factors such as lymphovascular invasion, perineural invasion, extra nodal extension, depth of invasion, margin status and tumor differentiation grades were documented.

RESULTS: The findings indicate a higher frequency of non-cohesive worst invasion patterns in numerous anatomical sites. A prediction accuracy of 69.1 % was obtained from the logistic regression analysis, suggesting that the predictive performance has also improved. The chi square test results demonstrated a statistically significant correlation between the variable of interest and extranodal extension showing a p value of 0.008 while lymph node status also showed significant with a p value of 0.000. Another factor that depicted a significance with worst pattern of invasion was tumor margin status having a p value of 0.046. Lymphovascular invasion and the worst pattern of invasion also exhibited a statistically significant correlation, with a p-value of 0.013.

CONCLUSION: The results of this investigation indicate that aggressive tumor biology is associated with non-cohesive worst pattern of invasion. Non-cohesive worst pattern of invasion is associated with moderate differentiation grade, lymphovascular invasion, perineural invasion, extranodal extension, closed or involved tumor margins and nodal metastases.

PMID:40265143 | PMC:PMC12013481 | DOI:10.1016/j.jobcr.2024.12.008

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