ArticleCancer management and research2022
Fibrinogen-Albumin Ratio Index Exhibits Predictive Value of Neoadjuvant Chemotherapy in Osteosarcoma.
Article in Cancer management and research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- BoneCoT: multicentre validation of a whole-body skeleton foundation model for bone metastases guided by clinician-derived chain of thought.Nature biomedical engineering · 2026Article
- Fibrinogen-to-Albumin Ratio in Neonatal Sepsis.International journal of general medicine · 2023Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
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Abstract
Purpose: Inflammatory response and nutritional status are associated with cancer development and progression. The present study aimed to evaluate the predictive ability of the fibrinogen-albumin ratio index (FARI) to the efficacy of neoadjuvant chemotherapy (NAC) for osteosarcoma. Patients and methods: A retrospective analysis involving 752 consecutive osteosarcoma patients between 2012 and 2020 was performed. Data on serum fibrinogen, albumin levels, white blood cell count, platelet count, and alkaline phosphatase (ALP) before and after NAC were collected. The predictive value of the NAC efficacy in osteosarcoma was assessed by constructing a receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Prognosis and its predictive factors were analyzed by Kaplan-Meier method and COX regression analysis. Nomogram was established according to selected variables. The predictive performance of the nomogram model was assessed using C-statistics. Results: A total of 203 patients were included. ROC analysis showed that both FARI before NAC (preFARI; AUC = 0.594, Conclusion: Our findings indicated that FARI exhibits the favorable predictive ability for the efficacy of NAC for osteosarcoma, which could support clinicians and patients in clinical decision-making and treatment optimization.
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