Prognostic Evaluation Using Nutrition-Inflammation Biomarkers from Routine Blood Tests in Metastatic Breast Cancer: A Boruta Algorithm-Optimized Feature Selection Study - Summary - MDSpire
Advertisement
Prognostic Evaluation Using Nutrition-Inflammation Biomarkers from Routine Blood Tests in Metastatic Breast Cancer: A Boruta Algorithm-Optimized Feature Selection Study
To evaluate and compare the prognostic value of nutrition-and inflammation-related indices derived from routine blood tests in patients with metastatic breast cancer, and to identify the most clinically applicable indicators.
Key Findings:
MLR, SIRI, ALI, AGR, and PA were identified as independent predictors of overall survival.
Patients with MLR ≥ 0.33 had a 3.94-fold increased risk of death.
Patients with SIRI ≥1.70 had a 3.32-fold increased risk of death.
Patients with ALI ≥53.99, AGR ≥1.11, and PA ≥181 had reductions in mortality risk of 73%, 76%, and 77%, respectively.
Inflammation-related indices were stronger predictors for short-term outcomes, while nutrition-related indices were better for medium-to long-term survival.
Interpretation:
Nutrition-and inflammation-related indices from routine blood tests are effective prognostic tools in metastatic breast cancer, with ALI and MLR showing consistent performance across patient subgroups.
Limitations:
Retrospective design may introduce bias.
Single-center study limits generalizability.
Potential confounding factors not fully accounted for.
Conclusion:
Nutrition-and inflammation-related indices, particularly MLR, SIRI, ALI, AGR, and PA, are valuable for prognostic assessment in metastatic breast cancer, aiding in patient management and improving survival and quality of life.
