Investigation of Multiple Biomarkers in Predicting the Disease Free Survival and Overall Survival among Head and Neck Cancer Patients Public

Zhao, Bokai (Spring 2019)

Permanent URL: https://etd.library.emory.edu/concern/etds/8k71nj31w?locale=fr
Published

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide. This paper investigated the clinical factors associated with tumor response by different treatments and identify the biomarkers associated with disease free survival and overall survival among head and neck cancer patients.

Methods: Descriptive analysis was used to describe the demographic and clinical variables. Logistic regression was fitted to determine the risk factor for whether patients went through recurrence. Survival analysis was performed to identify which biomarker(s) would be responsible for patients’ OS or DFS. After univariate analysis, hazard ratio and p-value for each potential risk factor was calculated. Forward model selection was applied to determine the final logistic regression model. Kaplan Meier Curves, Supremum test for proportional hazards assumption and the plots of the standardized score process were applied.

Results: The odds of a HNSCC reoccurrence within Age >= 60 PS group was approximately 2.7 times the odds for Age < 60 PS group; the odds of HNSCC reoccurrence for patients whose P16 status were negative was 0.14 times the odds for patients whose P16 status were positive. OS and DFS were also significantly associated with HNSCC recurrence. We didn’t find significance in the odds ratio among different levels of any biomarkers with recurrence. For OS, the chance of dying for patients in HER3 < 0.5 was nearly 4 times the chance of dying for patients in HER3 > 0.5. For DFS, the relative risk of PD-L1 in Peritumoral Stroma Level 1 vs Level 4 was approximately 8 with p-value equaling to 0.0291.

Conclusion: In order to improve HNSCC patients’ overall survival further, new and less toxic treatment as well as improving patients’ general well-being and daily activities were crucial, as P16, PD-L1 and HER3 accounted for a large amount of patients’ recurrence and OS. Further studies would be needed to find both new treatment strategies and ways to provide better patients care.

 

Table of Contents

1. Introduction ....................................................................1

2. Method ............................................................................3

2.1 Data Collection ...............................................................3

2.2 Statistical Analysis Method ..............................................4

2.2.1 Descriptive analysis ......................................................4

2.2.2 Logistic Regression ......................................................4

2.2.3 Log Rank Test ...............................................................5

2.2.4 Cox Proportional Hazard model formulation ...................6

2.2.5 Evaluate assumption .....................................................6

2.3 Statistical Analysis Plan ...................................................7

3. Results .............................................................................8

3.1 Descriptive analysis .........................................................8

3.2 Univariate and multivariable logistic regression ................8

3.3 Survival Analysis .............................................................9

4. Conclusion and Discussion ................................................13

5. Selected References ..........................................................16

6. Tables and Figures ............................................................17

7. Appendix .........................................................................29

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