British Journal of Cancer · 2020 · 354 citations · 15 references
MedicineImmunologyOncologyCancer ImmunologyInflammationTumor ImmunologyBiomarker ValidationCancer BiomarkersCancer Survival AnalysisColorectal CancerImmuno-oncology BiomarkersInflammatory BiomarkersBiomarker-based Prognostic ModelsBiomarkers For Metastatic DiseaseColorectal Cancer BiomarkersColorectal Cancer PrognosisCox RegressionImmune Biomarker DevelopmentImmune Biomarkers In CancerKaplan-meier Confidence Intervals
BACKGROUND: Immune-inflammatory biomarkers (IIBs) showed a prognostic relevance in patients with metastatic CRC (mCRC). We aimed at evaluating the prognostic power of a new comprehensive biomarker, the Pan-Immune-Inflammation Value (PIV), in patients with mCRC receiving first-line therapy. METHODS: In the present pooled-analysis, we included patients enrolled in the Valentino and TRIBE trials. PIV was calculated as: (neutrophil count × platelet count × monocyte count)/lymphocyte count. A cut-off was determined using the maximally selected rank statistics method. Generalised boosted regression (GBR), the Kaplan-Meier method and Cox hazards regression models were used for survival analyses. RESULTS: A total of 438 patients were included. Overall, 208 patients (47%) had a low-baseline PIV and 230 (53%) had a high-baseline PIV. Patients with high PIV experienced a worse PFS (HR, 1.66; 95% CI, 1.36-2.03, P < 0.001) and worse OS (HR, 2.01; 95% CI, 1.57-2.57; P < 0.001) compared to patients with low PIV. PIV outperformed the other IIBs in the GBR model and in the multivariable models. CONCLUSION: PIV is a strong predictor of survival outcomes with better performance than other well-known IIBs in patients with mCRC treated with first-line therapy. PIV should be prospectively validated to better stratify mCRC patients undergoing first-line therapy.
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Greedy function approximation: A gradient boosting machine.
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The National Comprehensive Cancer Network
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Medicine, Oncology, Pharmacotherapy +12