Background: Various molecular biomarkers, including epidermal growth factor receptor (EGFR), have gained importance as predictors of head and neck cancer disease progression.Aims: This study aimed to investigate the ability of EGFR expression as a prognostic marker for laryngeal squamous cell carcinoma (LSCC).Materials and methods: A total of 31 patients with LSCC with immunohistochemistry (IHC) staining for EGFR were examined. Digital image processing was applied to analyze EGFR staining intensity and percent distribution, which were calculated as the H-score. We used a receiver operating characteristic (ROC) curve to identify the best cut-off point of EGFR expression, with H-score separated into high- and low-grade for cancer recurrence prediction. Results: The cut-off point of EGFR expression for high- and low-grades was an H-score of 170 with a sensitivity of 75% and a specificity of 66.7%. Using this cut-off, 14 (45.16%) and 17 (54.84%) patients were categorized as having high- and low-grades EGFR, respectively. The analysis showed a significant reverse correlation between the EGFR grade and LSCC recurrence (RR, 0.4; 95% CI, 0.17-0.98; p = .02).Conclusions: Our study demonstrated that EGFR grading using H-score with the generated cut-off point by the ROC curve might be further applied as a potential marker for LSCC prognostic prediction.
Background: Various molecular biomarkers, including epidermal growth factor receptor (EGFR), have gained importance as predictors of head and neck cancer disease progression.Aims: This study aimed to investigate the ability of EGFR expression as a prognostic marker for laryngeal squamous cell carcinoma (LSCC).Materials and methods: A total of 31 patients with LSCC with immunohistochemistry (IHC) staining for EGFR were examined. Digital image processing was applied to analyze EGFR staining intensity and percent distribution, which were calculated as the H-score. We used a receiver operating characteristic (ROC) curve to identify the best cut-off point of EGFR expression, with H-score separated into high- and low-grade for cancer recurrence prediction. Results: The cut-off point of EGFR expression for high- and low-grades was an H-score of 170 with a sensitivity of 75% and a specificity of 66.7%. Using this cut-off, 14 (45.16%) and 17 (54.84%) patients were categorized as having high- and low-grades EGFR, respectively. The analysis showed a significant reverse correlation between the EGFR grade and LSCC recurrence (RR, 0.4; 95% CI, 0.17-0.98; p = .02).Conclusions: Our study demonstrated that EGFR grading using H-score with the generated cut-off point by the ROC curve might be further applied as a potential marker for LSCC prognostic prediction.