## 4 Discussion  
New cancer treatment techniques are currently being studied to improve patient survival [34; 35; 36]. However, the same technique may have different results in patients diagnosed with the same cancer. For this reason, studying the possible therapeutic strategies based on the clinical and image characteristics of the patient at the time of diagnosis is a matter of great importance. In this study, cancer lesions from [18F]FDG PET/CT images of patients with oropharyngeal cancer are analyzed to assess the predictive value of clinical, quantitative, and textural features, assessing OS and RFS over a 2-year follow-up period. Concretely, 48 parameters are extracted, including 13 conventional parameters, 4 shape and size features, and 31 textural features. Kaplan-Meier curves and Cox proportional hazards regression analyses are computed. This study evidences the importance of HPV status for the prognosis of oropharyngeal cancer for OS and RFS. In this study, Kaplan-Meier curves for OS and RFS showed that HPV-negative diagnosis is related to poorer outcomes. However, future clinical trials should include a greater variety of patients in order to further study the implications of HPV status. This fact suggests that within the group of patients who respond satisfactorily, the vast majority achieve a sustained response, with low rates of relapse. As shown in Kaplan-Meier curves, several retrospective studies have demonstrated that patients \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Univariate**} \\ \hline  & **HR (95\% CI)** & \(p\)**-Value** \\ \hline HPV & 0.243 (0.055–1.077) & 0.063 \\ Tumor stage & 2.934 (0.387–22.200) & 0.298 \\ Location & 0.930 (0.349–2.480) & 0.884 \\ Smoker & 23.320 (0.011–4.73 \(\times\) 10\({}^{4}\)) & 0.418 \\ SUV\({}_{\text{max}}\) & 1.017 (0.962–1.074) & 0.560 \\ TLG & 1.003 (1.000–1.006) & 0.026 \\ Sphericity & 0.002 (0.000–6.065) & 0.033 \\ Surface & 1.000 (1.000–1.000) & 0.028 \\ GLZLM ZLNU & 1.011 (1.001–1.022) & 0.031 \\ \hline \hline \end{tabular} After the adjustment for the HPV status variable, none of the characteristic proved to be significant in predicting clinical outcome in RFS (see Table 7). However, both tumor stage (HR = 3.624 (0.484–27.127), \(p\) = 0.210) and SUV\({}_{\text{max}}\) (HR = 1.019 (0.974–1.067), \(p\) = 0.407) resulted in better \(p\)-values.  
\end{table} 
Table 6: Cox regression analysis for relapse-free survival for 2-year follow-up of relevant clinical characteristics and statistically significant image features. No \(p\)-value was significant after multiple-testing correction. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Univariate**} \\ \hline  & **HR (95\% CI)** & \(p\)**-Value** \\ \hline Tumor stage & 3.624 (0.484–27.127) & 0.210 \\ Location & 0.973 (0.412–2.295) & 0.949 \\ Smoker & 6.883 \(\times\) 10\({}^{5}\) (0.000–) & 0.987 \\ SUV\({}_{\text{max}}\) & 1.019 (0.974–1.067) & 0.407 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Cox regression analyses for relapse-free survival for 2-year follow-up of relevant clinical characteristics and significant image features adjusted for the HPV status variable before multiple-testing correction by means of the Benjamini–Hochberg procedure. No \(p\)-value was significant after multiple-testing correction. with HPV-positive status have a better prognosis than patients with HPV-negative status, especially those patients with oropharyngeal carcinoma. This is due to the fact that HPV-positive cases are identified as a tumor entities with different biological, pathological, and clinical features [37; 38]. Consequently, a better OS and RFS is expected in these patients. The fact that most of our cohort are stage IV (84.64%) may explain the low rates of OS and RFS, along with the inclusion of tumor persistence as relapse cases.