Establishment and validation of prognostic nomograms to predict overall survival and cancer-specific survival for patients with osteosarcoma

Yang, Qiankun; Lai, Qingyuan; Wang, Yi; Wang, Yang; Yao, Zhong-Xiang; Zhang, Xiaojing

doi:10.4149/neo_2020_200617n639

Cited by 14 publications

(13 citation statements)

References 53 publications

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“…feret (minimum diameter) significantly indicated higher chemoresistance. This was consistent with previous reports that increased tumour size prognosticated poor outcome for osteosarcoma [19]. Furthermore, higher tumour circularity indicated higher chemosensitivity in the current study.…”

Section: Discussionsupporting

confidence: 94%

Computational Analysis of Mris Predicts Osteosarcoma Chemoresponsiveness

et al. 2021

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Aim: This study aimed to improve osteosarcoma chemoresponsiveness prediction by optimization of computational analysis of MRIs. Patients & methods: Our retrospective predictive model involved osteosarcoma patients with MRI scans performed before OsteoSa MAP neoadjuvant cytotoxic chemotherapy. Results: We found that several monofractal and multifractal algorithms were able to classify tumors according to their chemoresponsiveness. The predictive clues were defined as morphological complexity, homogeneity and fractality. The monofractal feature CV for Λ′(G) provided the best predictive association (area under the ROC curve = 0.88; p <0.001), followed by Y-axis intersection of the regression line for box fractal dimension, r² for FDM and tumor circularity. Conclusion: This is the first full-scale study to indicate that computational analysis of pretreatment MRIs could provide imaging biomarkers for the classification of osteosarcoma according to their chemoresponsiveness.

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Section: Discussionsupporting

confidence: 94%

Computational Analysis of Mris Predicts Osteosarcoma Chemoresponsiveness

et al. 2021

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“…Moreover, it is generally believed that osteosarcoma patients with DM with higher age had a poorer OS prognosis than younger patients (44). Our study showed that patients as study objects (18,50), while we selected the patient with DM who lacked effective treatment and had a poor prognosis as a research object, which is more specific clinically and has not been studied. Second, our research included fewer clinical variables and had comparable or better AUC values.…”

Section: Discussionmentioning

confidence: 93%

Risk Factors, Prognostic Factors, and Nomograms for Distant Metastasis in Patients With Newly Diagnosed Osteosarcoma: A Population-Based Study

et al. 2021

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BackgroundOsteosarcoma is the most common bone cancer, mainly occurring in children and adolescents, among which distant metastasis (DM) still leads to a poor prognosis. Although nomogram has recently been used in tumor areas, there are no studies focused on diagnostic and prognostic evaluation of DM in primary osteosarcoma patients.MethodsThe data of osteosarcoma patients diagnosed between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for DM in osteosarcoma patients, and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors of osteosarcoma patients with DM. We then established two novel nomograms and the results were evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).ResultA total of 1,657 patients with osteosarcoma were included, and 267 patients (16.11%) had DM at the time of diagnosis. The independent risk factors for DM in patients with osteosarcoma include age, grade, T stage, and N stage. The independent prognostic factors for osteosarcoma patients with DM are age, chemotherapy and surgery. The results of ROC curves, calibration, DCA, and Kaplan–Meier (K-M) survival curves in the training, validation, and expanded testing sets, confirmed that two nomograms can precisely predict occurrence and prognosis of DM in osteosarcoma patients.ConclusionTwo nomograms are expected to be effective tools for predicting the risk of DM for osteosarcoma patients and personalized prognosis prediction for patients with DM, which may benefit clinical decision-making.

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“…As reported in previous studies, old age has been proven to be related with poor survival in patients with breast cancer (15), prostate cancer (16), and osteosarcoma (17). However, the precise cut-off value of age in PMCT remains controversial.…”

Section: Discussionmentioning

confidence: 92%