Perinerural, lymphovascular and depths of invasion in extrapolating nodal metastasis in oral cancer
- PMID: 31139977
- DOI: 10.1007/s00784-019-02921-0
Perinerural, lymphovascular and depths of invasion in extrapolating nodal metastasis in oral cancer
Abstract
Objective: The role of tumour thickness (TT), depth of invasion (DOI) from two different reference points (TT2 and TT3), perineural invasion (PNI) and lymphovascular invasion (LVI) were evaluated to predict lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC). Reference points for measuring the DOI were suggested.
Material and methods: Paraffin-embedded tissues of excisional biopsy cases diagnosed as OSCC were sectioned and stained in haematoxylin and eosin to study variables like TT1, TT2, TT3, PNI and LVI. Out of total 150 cases collected for the study, 136, 123 and 149 cases were qualified for analysis of TT1, TT2 and TT3 respectively. The association with LNM was studied using chi square test of independence. A binary logistic regression model (BLC) was developed to indicate high-risk cases.
Results: Receiver operating curve analysis suggested an optimum cut-off value. A significant correlation of TT1 (> 8.64, RR = 1.642, p = 0.018) and TT2 (> 7.64, RR = 2.041, p = 0.016), PNI (p = 0.028) and LVI (p = 0.000) were found with LNM. A mathematical model was suggested as Z = - 1.866 + 0.101TT2 + 2.106VI + e, where Z = log [(p/(1 - p)] p = probability of the case experiencing the event of interest.
Conclusion: With the suggestion of a standardised reference point to measure DOI for the first time, this study has shown an association of TT1, TT2, PNI and LVI with LNM in Indian Population. The mathematical model can help in identifying high-risk cases in OSCC.
Clinical relevance: Such studies would offer avenues for the pre-surgery assessment of depth of invasion and tumour thickness before performing neck dissection, thereby decreasing morbidity.
Keywords: Lymph node metastasis; Lymphovascular invasion; Oral squamous cell carcinoma; Perineural invasion; ROC curve; Reference point; Tumour thickness.
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