ArticleFrontiers in medicine2025
Development and validation of a predictive score for chemoresistance in high-grade osteosarcoma at baseline.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Natural products mediate ferroptosis and immune microenvironment-linked sensitization in osteosarcoma: from chemotherapy resistance to combined therapeutic transformation.Molecular diversity · 2026Review
- Predicting resistance to neoadjuvant chemotherapy in osteosarcoma using machine learning with clinical data and T2-weighted MRI radiomics.European radiology experimental · 2026Article
- Non-invasive MRI biomarkers for assessment of neoadjuvant chemotherapy response in osteosarcoma: Current techniques and clinical perspectives.Journal of bone oncology · 2026Review
- Multi-omics integration and Mendelian randomization elucidate the PARP16-UPR axis driving chemoresistancein gastric cancer.Frontiers in oncology · 2026Article
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Authors and funding
7 authors.
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Abstract
Objective: Histological tumor necrosis is the current indicator for the response of osteosarcoma after neoadjuvant chemotherapy. Chemoresistant tumors require close monitoring and adjustment of treatment. We aimed to develop a prediction score for chemoresistance in newly diagnosed osteosarcoma patients underwent neoadjuvant chemotherapy. Materials and methods: Data from a registry-based cohort of high-grade osteosarcoma patients treated with neoadjuvant chemotherapy between January 2008 and October 2023 were used. Histological necrosis from surgical specimens was the reference standard. Clinical and MRI parameters at baseline were derived by risk regression analysis. Results: From 139 patients, 93 (66.91%) were classified as chemoresistant (histological necrosis <90%). The model included four predictors: age >40 years, initial metastasis, tumor volume (≤150 ml, > 150-400, or > 400 ml), and pre-chemotherapy tumor necrosis >50%. The AuROC of the model was 0.76 (95% CI 0.68-0.85) and well-calibrated. Internal validation using a bootstrap technique showed consistent AuROC results. The prediction score ranged from 0 to 8, with a score of 0-2 indicating low probability (positive LHR = 0.45) and a score of 3-8 indicating high probability (positive LHR = 2.56) of chemoresistance. Conclusion: High-grade osteosarcoma patients with a prediction score of 3-8 have a high probability of chemoresistance. This score could be used for risk communication and tailoring management at diagnosis.
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