From associations to clinical practice: translating inflammatory-nutritional indices into a machine learning-driven model for breast cancer risk stratification with cross-ethnic validation - Scorecard - MDSpire
Advertisement
From associations to clinical practice: translating inflammatory-nutritional indices into a machine learning-driven model for breast cancer risk stratification with cross-ethnic validation
Clinical Scorecard: Translating Inflammatory-Nutritional Indices into a Machine Learning Model for Breast Cancer Risk Assessment: A Cross-Ethnic Validation Approach
At a Glance
Category
Detail
Condition
Breast Cancer
Key Mechanisms
Inflammatory-nutritional indices and their association with breast cancer risk and mortality.
Target Population
Female patients with breast cancer and matched healthy controls.
Care Setting
Cancer risk assessment and prognostic stratification.
Key Highlights
Advanced Lung Cancer Inflammation Index (ALI) inversely associated with breast cancer risk and mortality.
Neutrophil percentage-to-albumin ratio (NPAR), systemic inflammation response index (SIRI), and neutrophil-to-lymphocyte ratio (NLR) positively associated with risk.
Machine learning model achieved an AUC of 0.832 for predicting breast cancer risk.
Cross-ethnic validation indicated the need for population-specific calibration.
Web-based dynamic nomogram developed for risk prediction.
Guideline-Based Recommendations
Diagnosis
Evaluate inflammatory-nutritional indices for breast cancer risk assessment.
Management
Consider inflammatory indices in prognostic stratification and clinical decision-making.
Monitoring & Follow-up
Monitor inflammatory status in breast cancer management.
Risks
Increased risk associated with high NPAR, SIRI, and NLR.
Patient & Prescribing Data
Female breast cancer patients and healthy controls.
Inflammatory indices may inform targeted interventions to mitigate inflammatory processes.
Clinical Best Practices
Utilize machine learning approaches for risk stratification.
Incorporate a comprehensive panel of inflammatory indices in assessments.
