## 3 Results
### Relapse-Free Survival Analysis  
The 2-year RFS was 41.0% for the study cohort, including those with tumor persistence as relapse cases. In the same way as in OS analysis (see Table 2), HPV and TLG turned out to be significant features in RFS Kaplan-Meier analysis (see Table 5). The most important clinical feature is the HPV status (\(p\) = 0.023), being a prognostic indicator of higher RFS in HPV-positive patients (SR: 45.5% in positive subgroup versus SR: 84.6% in negative subgroup). Additionally, four texture and two shape features were found to be statistically significant predictors of RFS, with ZLNU being the best indicator. For ZLNU (\(p\) = 0.001) the longer relapse-free survival is related to lower values (SR: 78.4%) rather than higher values (SR: 26.7%). For Surface (\(p\) = 0.004), the best prognosis is related to lower values (SR: 82.1%) rather than high values (SR: 38.1%), and for MTV (\(p\) = 0.006) a better prognosis is related to lower values (SR: 78.9%) rather than higher values (SR: 36.8%). While the results were statistically significant before multiple-testing correction, only ZLNU was significant afterwards. The RFS curves of relevant clinical features are shown in Figure 4. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Univariate**} \\ \hline  & **HR (95\% CI)** & **\(p\)-Value** \\ \hline Location & 1.446 (0.459–4.556) & 0.529 \\ Smoker & 157/042.285 (0.000–) & 0.986 \\ SUV\({}_{\rm max}\) & 1.038 (0.989–1.088) & 0.129 \\ Skewness & 0.141 (0.022–0.906) & 0.039 \\ TLG & 1.005 (1.002–1.009) & 0.002 \\ MTV & 1.068 (1.019–1.119) & 0.006 \\ Surface & 1.000 (1.000–1.001) & 0.005 \\ GLCM Entropy & 28.669 (1.726–476.315) & 0.019 \\ GLRLM\_RLNU & 1.002 (1.000–1.003) & 0.038 \\ GLZLM\_GLNU & 1.065 (1.003–1.130) & 0.039 \\ GLZLM\_ZLNU & 1.018 (1.006–1.030) & 0.004 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Cox regression analyses for overall 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. Tumor stage is not included due to non-convergence. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Univariate**} & \multicolumn{2}{c}{**Multivariate**} \\ \hline  & **HR (95\% CI)** & **\(p\)-Value** & **HR (95\% CI)** & **\(p\)-Value** \\ \hline HPV & 0.152 (0.020–1.182) & 0.072 & & \\ Tumor stage & 27.519 (0.049–1.559 \(\times\) 10\({}^{5}\)) & 0.305 & & \\ Location & 1.410 (0.447–4.442) & 0.558 & & \\ Smoker & 23.267 (0.004–1.348 \(\times\) 10\({}^{5}\)) & 0.477 & & \\ SUV\({}_{\rm max}\) & 1.037 (0.981–1.096) & 0.199 & & \\ TLG & 1.006 (1.003–1.009) & 0.001 * & 1.006 & 0.001 \\ MTV & 1.075 (1.025–1.126) & 0.003 & & \\ Surface & 1.000 (1.000–1.001) & 0.001 * & & \\ GLRLM RLNU & 1.002 (1.000–1.003) & 0.043 & & \\ GLZLM GLNU & 1.069 (1.005–1.137) & 0.033 & & \\ GLZLM ZLNU & 1.017 (1.005–1.030) & 0.007 & & \\ \hline \hline \end{tabular} For HPV status adjustment, two more variables were significant in predicting clinical outcome in OS (Skewness (HR = 0.141 (0.022–0.906), \(p\) = 0.039) and Entropy (28.669 (1.726–476.315), \(p\) = 0.019)), resulting in six variables with better results than those non-adjusted by HPV Cox regression (see Table 4). However, TLG (HR = 1.005 (1.002–1.009), \(p\) = 0.002), with worse results than those obtained in the previous analysis, was still the most significant variable. In addition, these results showed no significant variables after multiple-testing correction by means of the Benjamini-Hochberg procedure.  
\end{table} 
Table 3: Cox regression analyses for overall survival for 2-year follow-up of relevant clinical characteristics and significant image features. * Statistically significant \(p\)-value after multiple-testing correction by means of Benjamini–Hochberg procedure. RLNU: run-length non-uniformity; GLNU: gray-level non-uniformity; ZLNU: zone-length non-uniformity.