Laryngoscope Investigative Otolaryngology (Oct 2022)

Demographic and pathologic factor regression to a growth rate model of p16‐negative oral cavity squamous cell carcinoma

  • Jacob G. J. Wihlidal,
  • Keng Yeow Tay,
  • S. Danielle MacNeil,
  • Anthony C. Nichols,
  • Kevin Fung,
  • John H. J. Yoo,
  • Adrian I. Mendez

DOI
https://doi.org/10.1002/lio2.831
Journal volume & issue
Vol. 7, no. 5
pp. 1384 – 1390

Abstract

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Abstract Objectives The current study aims to quantify the growth rate of p16‐negative oral cavity squamous cell carcinoma, characterize causative relationships between demographic risk factors and tumor growth, and examine pathologic findings associated with the tumor growth rate at a tertiary care institution. It is hypothesized that causative relationships will be drawn between the individual sociodemographic and pathologic factors and oral cavity p16‐negative squamous cell carcinoma growth rate. Methods Prospectively recruited participants, receiving surgical intervention only, were followed from initial staging CT scan to surgical resection. Interval growth was calculated in cm3/week. Demographic information including age, sex, smoking history, alcohol consumption history, previous all‐type malignancy, previous chemotherapy treatment, previous head or neck radiation exposure, and time interval elapsed between diagnosis and surgery was collected from each participant, and regression analysis was applied to determine causality. Results Summary statistics revealed a mean growth rate for the study sample of 1.385cm3/week. Statistically significant regression correlations were detected between tumor growth and alcohol consumption, origination at the retromolar trigone, and clinical nodal stage. Conclusions Through a small prospective cohort sample, the current study suggests clinical associations between alcohol consumption, origination at the retromolar trigone, and clinical nodal stage with rate of tumor growth. Future work will validate these relationships in a larger patient cohort, and against stronger modeling techniques. Level of Evidence Prospective non‐random cohort design.

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