Prognostic Evaluation Using Nutrition-Inflammation Biomarkers from Routine Blood Tests in Metastatic Breast Cancer: A Boruta Algorithm-Optimized Feature Selection Study
By
Nong, Wen-xiong
Huang, Sheng-kai
Zhang, Wenhai
Tan, Yang
Wu, Zhi-dong
Liang, Wan-wang
Wu, Rui-zheng
May 13, 2026
Clinical Scorecard: Assessment of Prognostic Value of Nutrition and Inflammation Biomarkers from Standard Blood Tests in Metastatic Breast Cancer
At a Glance
Category Detail
Condition Metastatic Breast Cancer Key Mechanisms Nutrition and inflammation-related indices derived from routine blood tests Target Population Patients with newly diagnosed metastatic breast cancer Care Setting Oncology clinics and hospitals
Key Highlights
MLR, SIRI, ALI, AGR, and PA identified as independent predictors of overall survival Inflammation indices are stronger for short-term outcomes; nutrition indices for medium-to long-term survival ALI and MLR show consistent prognostic performance across all clinical subgroups Guideline-Based Recommendations
Diagnosis
Utilize routine blood tests to assess nutrition and inflammation indices in metastatic breast cancer patients Management
Incorporate MLR, SIRI, ALI, AGR, and PA into patient management strategies to optimize outcomes Monitoring & Follow-up
Regularly monitor nutrition and inflammation indices to evaluate patient prognosis and adjust treatment plans Risks
Patients with MLR ≥ 0.33 and SIRI ≥ 1.70 have significantly increased mortality risk Patient & Prescribing Data
163 newly diagnosed breast cancer patients with a single distant metastasis
Nutrition and inflammation indices can guide treatment decisions and improve survival rates
Clinical Best Practices
Apply the Boruta algorithm for feature selection in prognostic assessments Use Kaplan–Meier survival analysis and Cox regression models for evaluating survival associations Related Resources & Content
