Comparison of tumor volume, thickness, and T classification as predictors of outcomes in surgically treated squamous cell carcinoma of the oral tongue. Issue 8 (7th May 2018)

• Record Type: Journal Article
• Authors: Mair, Manish; Nair, Deepa; Nair, Sudhir; Malik, Akshat; Mishra, Aseem; Kannan, Sadhana; Bobdey, Saurabh; Singhvi, Hitesh; Chaturvedi, Pankaj
• Is Part Of: Head & neck. Volume 40:Issue 8(2018)
• Page Start: 1667
• Page End: 1675
• Publication Date: 2018-05-07
• Subjects: nodal metastasis -- survival -- T classification -- thickness -- tumor volume; Head -- Diseases -- Periodicals; Neck -- Diseases -- Periodicals; Head -- Periodicals; Neck -- Periodicals; Face -- Periodicals; 617.51059
• DOI: 10.1002/hed.25161
• Languages: English
• ISSNs: 1043-3074

Abstract

Abstract: Background: As per TNM classification, superficial tumors with a favorable prognosis are fallaciously clubbed together with unfavorable, deeply infiltrating lesions in the same classification. Methods: This is a retrospective study of 588 patients with treatment‐naive oral tongue cancers. Binary logistic regression was used to identify predictors of nodal metastasis and extracapsular spread (ECS) using tumor volume and thickness as separate models. The C‐index was generated to quantify predictive accuracy of T classification, thickness, and tumor volume for survival. Results: Compared to T classification, tumor volume and thickness were better predictors of nodal metastasis and ECS. Predictive accuracy for disease‐free survival (DFS) and overall survival (OS) given by C‐index was equal and better for thickness (0.60 and 0.69) and tumor volume (0.61 and 0.69) as compared to T classification (0.59 and 0.64, respectively). For early‐stage T1 to T2 oral tongue cancer, thickness is a better predictor of nodal metastasis as compared to tumor volume and T classification. Conclusion: Concordance between the tumor thickness and volume proves that tumor thickness can be taken as a surrogate and reliable predictor of outcomes instead of calculating the tumor volume.