Analysis of inflammatory, metabolic and nutritional parameters as prognostic factors in locally advanced cervical cancer

Multiple predictors have been studied and included in predictive models for locally advanced cervical cancer (LACC) treated with chemoradiation (CRT). Among published predictive models there is often heterogeneity for clinical setting, analyzed outcomes and included predictors, which makes it sometimes difficult to apply the model in the real daily practice. Therefore, there is growing interest in investigating emerging prognostic factors that can provide additional valuable information. To improve the accuracy of outcome predictions and enable treatment customization based on prognostic profiles, we analyzed a large population of patients treated with CRT for LACC in our institution exploring the impact of several parameters on clinical oncological outcomes. We retrospectively analyzed pre-treatment systemic inflammatory indices, nutritional parameters (focusing on sarcopenic obesity), and metabolic parameters such as maximum standardized uptake value (SUVmax). This analysis reported conflicting outcomes that currently do not support the routine use of the valuated parameters. However, sarcopenic obesity emerged as a novel and significant predictor of adverse outcomes and we confirmed the importance of pre-treatment hemoglobin assessment and anemia correction. Advanced statistical methodologies and collaborative efforts are needed to enhance the accuracy of prognostic models. Constructing large databases through cooperative initiatives may provide a robust foundation for the development of reliable predictive models in the future.