Incorporation of adverse features in advanced oral cancer improves precision in staging and patient prognostication. Issue 4 (31st January 2022)

• Record Type: Journal Article
• Authors: Singh, Manraj; Thankappan, Krishnakumar; Balasubramanian, Deepak; Pillai, Vijay; Shetty, Vivek; Rangappa, Vidyabhushan; Chandrasekhar, Naveen Hedne; Kekatpure, Vikram; Kuriakose, Moni Abraham; Krishnamurthy, Arvind; Mitra, Arun; Pattatheyil, Arun; Jain, Prateek; Iyer, Subramania; Iyer, Narayanan Gopalakrishna; Subramaniam, Narayana
• Is Part Of: Head & neck. Volume 44:Issue 4(2022)
• Page Start: 964
• Page End: 974
• Publication Date: 2022-01-31
• Subjects: head and neck cancer -- oral cancer; Head -- Diseases -- Periodicals; Neck -- Diseases -- Periodicals; Head -- Periodicals; Neck -- Periodicals; Face -- Periodicals; 617.51059
• DOI: 10.1002/hed.26990
• Languages: English
• ISSNs: 1043-3074

Abstract

Abstract: Background: Despite revised staging criteria, stratification of patients with advanced oral squamous cell carcinoma (OSCC) remains difficult. Well‐established features like perineural invasion (PNI), differentiation, and lymphovascular‐invasion (LVI) are controversial, and hence omitted from staging. We endeavor to better stratify this cohort by identifying predictors of survival in advanced OSCC (T3‐4). Methods: Seven hundred and forty‐two patients with T3‐4 OSCC underwent surgery from 2006 to 2013. Cox regression was performed to determine predictors of overall survival (OS). Results: OS was adversely impacted by PNI ( p = 0.046), LVI ( p = 0.038), moderate/poor differentiation ( p = 0.001), close/involved surgical margins ( p = 0.002), pT ( p = 0.034), and pN ( p < 0.001). The cumulative number of adverse histopathological features predicted poorer OS; HR 2.64 (CI 1.42–4.90) for one adverse feature and HR 4.23 (CI 2.34–7.67) for ≥2. Conclusion: In advanced OSCC, stratification with histopathologic risk factors can predict survival even in maximally treated patients; adjuvant therapies are unable to entirely mitigate this risk. Incorporation of adverse features into future editions of TNM can improve precision in staging and identify candidates for treatment escalation.