Authors’ reply to Kansal et al.

We thank Kansal et al.[1] for the insightful comments on our article titled “Predictors of extranodal extension (ENE) in oral squamous cell carcinoma: A retrospective analysis.”[2] Depth of invasion (DOI) is a significant factor affecting disease outcomes in oral cancer. An increase in DOI is well correlated with the presence of nodal metastasis and poor prognosis[3]; a logical explanation would be that the deeper the tumor’s invasion, the greater the breach of anatomical barriers, which could lead to an unpredictable distant tumor spread along the neurovascular bundles. While our study did not find a significant correlation between DOI and ENE, we agree that including a substantial proportion of clinically node-negative (N0) patients in the cohort could have influenced this outcome.[2] The association between positive surgical margins and ENE is an important point.[1] Positive margins are known to reflect aggressive tumor biology and may indeed be associated with a higher risk of ENE, though the adequacy of the surgical margins is still debatable in the literature.[4] We chose to omit surgical margins from the correlation analysis because they are primarily a surgeon-controlled factor. There is a growing evidence regarding the significance of the number of positive lymph nodes and its effect on the prognosis of oral cancer. In our posthoc analysis, we identified >5 positive lymph nodes as a potential predictor of ENE. We concur that the optimal cutoff remains debatable, and as this is a subset analysis, no definitive conclusions can be drawn. This finding needs to be validated in large datasets. A Taiwanese study involving a large population (n = 4287) showed that a lymph node ratio ≥0.078 and the presence of at least three pathologically positive nodes were significantly associated with poor disease-specific survival and overall survival.[5] Tumor budding, desmoplastic reaction, and tumor-infiltrating lymphocytes are not yet standardized in the routine histopathological reporting of oral cancer specimens and, therefore, were not included in the current study.[2] However, with the growing evidence in the literature regarding the significance of these emerging histological factors in head-and-neck cancers and their prognosis, future studies should validate their role in the prognosis of oral cancer.[6] We acknowledge the high specificity and low sensitivity of clinical ENE (cENE) in predicting pathological ENE in our study. We agree that incorporating advanced imaging techniques, as outlined by the 2024 Head and Neck Cancer International Group, may help improve the diagnostic accuracy of cENE. However, predicting occult nodal metastasis in the preoperative setting remains crucial for optimizing treatment planning and enhancing prognostication. In the contemporary era of artificial intelligence (AI)-based radiomics, integrating AI-driven predictive models presents a promising advancement for identifying occult metastasis and improving the diagnostic accuracy of cENE.[7] In conclusion, combining imaging data with clinical and histopathological parameters could enhance the predictive capabilities of ENE models in oral squamous cell carcinoma (OSCC), and exploring the development of better predictive models is warranted. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.