ArticleCancer biomarkers : section A of Disease markers2020
Nomogram based on pre-treatment inflammatory biomarkers predicting survival in patients with head and neck soft tissue sarcoma.
Article in Cancer biomarkers : section A of Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Systemic Immun e-Inflammation Index as a Predictor for Head and Neck Cancer Prognosis: A Meta-Analysis.Frontiers in oncology · 2022Pooled it
- Development and validation of a machine learning-based model to predict postoperative overall survival in patients with soft tissue sarcoma: a retrospective cohort study.American journal of cancer research · 2024Article
- Combined low levels of H4K16ac and H4K20me3 predicts poor prognosis in breast cancer.International journal of clinical oncology · 2023Article
- Prognostic Utility of Nutritional Risk Index in Patients with Head and Neck Soft Tissue Sarcoma.Nutrients · 2023Article
- Identification of Novel Prognostic Risk Signatures of Soft Tissue Sarcoma Based on Ferroptosis-Related Genes.Frontiers in oncology · 2021Article
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5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSystemic inflammatory biomarkers reflect level of inflammatory response, which have been suggested as prognostic factors in cancer patients.
objectiveTo estimate the prognostic value of inflammatory biomarkers in 149 patients with head and neck soft tissue sarcoma (HNSTS).
methodsPre-treatment neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), neutrophil-platelet score (NPS) and Aarhus Composite Biomarker Score (ACBS) were analyzed for association with overall survival (OS) and progression-free survival (PFS). Nomograms were consisted of independent predictors for OS and PFS, and evaluated by calibration curve and concordance index (C-index).
resultsIn multivariate analysis, LMR (HR = 0.42, 95% CI: 0.19-0.94, P= 0.035), ACBS (HR = 2.05, 95% CI: 1.02-4.12, P= 0.045) and AJCC stage were independent prognostic markers of OS. Moreover, high NLR (HR = 1.78, 95% CI: 1.07-2.94, P= 0.024) and advanced AJCC stage were independently related with worse PFS. Calibration curves reflected good discriminative ability of prognosis. The nomograms showed better accuracy of predicting OS (C-index: 0.748 vs. 0.690, P= 0.009) and PFS (C-index: 0.644 vs. 0.612, P= 0.028) than stage.
conclusionsPre-treatment LMR, ACBS and AJCC stage were effective predictor of OS. The NLR and AJCC stage could independently predict PFS. The nomogram might act as a promising prognostic model for OS and PFS in HNSTS.
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