AUTHOR=Tu Irene Wen-Hui , Shannon Nicholas Brian , 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 , Subramaniam Narayana , Iyer N. Gopalakrishna 

TITLE=Risk Stratification in Oral Cancer: A Novel Approach

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.836803

DOI=10.3389/fonc.2022.836803

ISSN=2234-943X

ABSTRACT=Background: Oral cavity squamous cell carcinoma (OSCC) is a common head and neck cancer with high morbidity and mortality. Currently, treatment decisions are guided by TNM staging, which omits important negative prognosticators such as lympho-vascular invasion, perineural invasion and histologic differentiation. We proposed nomogram models based on adverse pathological features to identify candidates suitable for treatment escalation within each risk group according to National Comprehensive Cancer Network (NCCN) guidelines.
Methods: Anonymized clinicopathologic data of OSCC patients from 5 tertiary healthcare institutions in Asia were divided into 3 risk groups according to NCCN guidelines. Within each risk group, nomograms were built to predict overall survival based on histologic differentiation, histological margin involvement, depth of invasion (DOI), extranodal extension, perineural (PNI), lymphovascular and bone invasion. Nomograms were internally validated with Precision Recall Analysis and Kaplan Meier Survival Analysis. 
Results: Low risk patients with positive pathological nodal involvement and/or positive PNI should be considered for adjuvant radiotherapy. Intermediate risk patients with gross bone invasion may benefit from concurrent chemotherapy. High-risk patients with positive margins, high DOI and high composite score of histologic differentiation, PNI and AJCC 8 T-staging should be considered for treatment escalation to experimental therapies in clinical trials.  
Conclusion: Nomograms built based on prognostic adverse pathological features can be used within each NCCN risk group to fine tune treatment decisions for OSCC patients.