Prognostic Impact of Proximal <i>Versus</i> Distal Localization in Extremity Long Bone Osteosarcomas

Berner, Kjetil; Bruland, Øyvind S.

doi:10.21873/anticanres.13365

Cited by 8 publications

(2 citation statements)

References 15 publications

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“…In previous studies, axial tumor locations and large tumor sizes were deemed as the worst prognostic factors for the survival outcomes of patients with osteosarcoma [52][53][54][55]. Our study suggested that patients with axial tumors or larger tumors had decreased survival time compared with patients with extremity tumors or smaller tumors.…”

Section: Discussionsupporting

confidence: 51%

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

Yang¹,

Lai²,

Wang³

et al. 2021

neo

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This study aimed to develop and validate nomograms predicting the survival of osteosarcoma patients from the SEER database and our hospital. Data of 1,066 osteosarcoma patients from the SEER database were randomly divided into a development cohort (n=800) and validation cohort one (n=266). Another cohort of 126 patients from our hospital was utilized as validation cohort two. Univariate and multivariate Cox analyses were performed to identify the independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS). Nomograms predicting the 3-and 5-year OS and CSS probability were constructed and validated. The predictive performances of the established nomograms were evaluated by the concordance index (C-index) and the calibration plot. Variables of age, surgical stage, surgery, grade, tumor site, and tumor size were identified as independent prognosticators for OS and CSS in Cox analyses. The C-indexes for OS and CSS in the development cohort were 0.818 and 0.829. Comparatively, the C-indexes for OS and CSS were 0.843 and 0.834, 0.736 and 0.782 for validation cohort one and two, respectively. Calibration plots showed excellent consistency between nomogram prediction and actual survival. Nomograms based on the SEER database are of high accuracy and can serve as a reliable tool for individualized consultation and survival prediction in osteosarcoma patients.

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Section: Discussionsupporting

confidence: 51%

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

Yang¹,

Lai²,

Wang³

et al. 2021

neo

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“…In addition, we found that the tumor's location near the central axis (spine, pelvis, thorax) has a significantly higher risk of death than the limbs. Like previous studies, axial tumor location predicts the worst prognosis (36,37). Wan et al (38) also found that the survival rate of EWS of the spine and pelvis was lower.…”

Section: Discussionmentioning

confidence: 53%

A Nomogram for Predicting Cancer-Specific Survival of Osteosarcoma and Ewing's Sarcoma in Children: A SEER Database Analysis

Wang

Zhanghuang

Tan

et al. 2022

Front. Public Health

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BackgroundOsteosarcoma (OSC) and Ewing's sarcoma (EWS) are children's most common primary bone tumors. The purpose of the study is to develop and validate a new nomogram to predict the cancer-specific survival (CSS) of childhood OSC and EWS.MethodsThe clinicopathological information of all children with OSC and EWS from 2004 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were used to screen children's independent risk factors for CSS. These risk factors were used to construct a nomogram to predict the CSS of children with OSC and EWS. A series of validation methods, including calibration plots, consistency index (C-index), and area under the receiver operating characteristic curve (AUC), were used to validate the accuracy and reliability of the prediction model. Decision curve analysis (DCA) was used to validate the clinical application efficacy of predictive models. All patients were divided into low- and high-risk groups based on the nomogram score. Kaplan-Meier curve and log-rank test were used to compare survival differences between the two groups.ResultsA total of 2059 children with OSC and EWS were included. All patients were randomly divided into training cohort 60% (N = 1215) and validation cohort 40% (N = 844). Univariate and multivariate analysis suggested that age, surgery, stage, primary site, tumor size, and histological type were independent risk factors. Nomograms were established based on these factors to predict 3-, 5-, and 8-years CSS of children with OSC and EWS. The calibration plots showed that the predicted value was highly consistent with the actual value. In the training cohort and validation cohort, the C-index was 0.729 (0.702–0.756) and 0.735 (0.702–0.768), respectively. The AUC of the training cohort and the validation cohort also showed similar results. The DCA showed that the nomogram had good clinical value.ConclusionWe constructed a new nomogram to predict the CSS of OSC and EWS in children. This predictive model has good accuracy and reliability and can help doctors and patients develop clinical strategies.

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Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing’s sarcoma: nomogram and webpage

Zhou,

Li,

Zeng

et al. 2024

Clin Transl Oncol

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Prognostic Impact of Proximal Versus Distal Localization in Extremity Long Bone Osteosarcomas

Cited by 8 publications

References 15 publications

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

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

A Nomogram for Predicting Cancer-Specific Survival of Osteosarcoma and Ewing's Sarcoma in Children: A SEER Database Analysis

Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing’s sarcoma: nomogram and webpage

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