From Normal to Optimal: Investigating Metabolic and Inflammatory Parameters as Predictors of Survival in Locally Advanced Cervical Cancer

Cervical cancer is the third most common cancer in women, and recent studies have highlighted the importance of body composition markers in predicting patient outcomes. We build upon the data of 83 patients from the Uterus-11 study, to explore the relation of pairwise feature combinations to long-term progression-free survival. We propose a framework to identify the parameter combinations with pre-defined thresholds of "normal range" which provide good separation of the survival group. Further, we optimize the pair-wise thresholds to further improve the separation measured by F1 scores. This approach allowed us to improve the statistical significance of hazard ratios in comparison to the previous studies. The optimization results suggest that the normal ranges of well-established biomarkers such as body mass index could be shifted in the context of specific diseases to achieve optimal outcome.