Construction and Validation of Nomograms for Predicting the Prognosis of Juvenile Osteosarcoma: A Real-World Analysis in the SEER Database

Jiang, Yao; Wang, Tianyu; Wei, Zizheng

doi:10.1177/1533033820947718

Cited by 14 publications

(23 citation statements)

References 28 publications

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“… 31 However, a recent study of 736 adolescents with juvenile osteosarcoma from the SEER database demonstrated that the treatment of chemotherapy did not associate with improved OS as well as CSS. 32 In our study, we found that the elderly osteosarcoma patients without chemotherapy had an unfavorable prognosis, which was in accordance with previous studies for older patients. 33 , 34 Surgical resection of primary site plays a pivotal role in the management of patients with osteosarcoma.…”

Section: Discussionsupporting

confidence: 92%

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Liu¹,

He²,

Yao³

et al. 2021

IJGM

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Background The aim of the current study was to construct prognostic nomograms for individual risk prediction in elderly patients with osteosarcoma. Methods Data for 816 elderly patients (≥40 years old) with osteosarcoma between 2004 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were randomly assigned to training (N=573) and internal validation (N=243) sets. The essential clinical predictors were identified based on least absolute shrinkage and selection operator (Lasso) Cox regression. Nomograms were constructed to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS). Results Our LASSO regression analyses of the training set yielded five clinicopathological features (age, chemotherapy, surgery, AJCC stage, and summary stage) in the training cohort for the prognosis of elderly patients with osteosarcoma, while grade was only associated with OS and M stage was only associated with CSS. Construction of nomograms based on these predictors was performed to evaluate the prognosis of elderly patients with osteosarcoma. The C-index, calibration and decision curve analysis also showed the satisfactory performance of these nomograms for prognosis prediction. Conclusion The constructed nomograms are helpful tools for exactly predicting the prognosis of elderly patients with osteosarcoma, which could enable patients to be more accurately managed in clinical practice.

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Section: Discussionsupporting

confidence: 92%

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Liu¹,

He²,

Yao³

et al. 2021

IJGM

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“…This has some enlightenment for doctors and patients in choosing surgical methods for patients with different risks. On chemotherapy, our study found that chemotherapy does not affect patient survival, similar to previous studies (38). highly consistent with the observed value, which indicates the accuracy of the prediction model.…”

Section: Discussionsupporting

confidence: 92%

A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study

Tang

Wang

Pan

2022

Front. Public Health

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Background: Malignant bone tumors (MBT) are one of the causes of death in elderly patients. The purpose of our study is to establish a nomogram to predict the overall survival (OS) of elderly patients with MBT.Methods: The clinicopathological data of all elderly patients with MBT from 2004 to 2018 were downloaded from the SEER database. They were randomly assigned to the training set (70%) and validation set (30%). Univariate and multivariate Cox regression analysis was used to identify independent risk factors for elderly patients with MBT. A nomogram was built based on these risk factors to predict the 1-, 3-, and 5-year OS of elderly patients with MBT. Then, used the consistency index (C-index), calibration curve, and the area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model was. Decision curve analysis (DCA) was used to assess the clinical potential application value of the nomogram. Based on the scores on the nomogram, patients were divided into high- and low-risk groups. The Kaplan-Meier (K-M) curve was used to test the difference in survival between the two patients.Results: A total of 1,641 patients were included, and they were randomly assigned to the training set (N = 1,156) and the validation set (N = 485). The univariate and multivariate analysis of the training set suggested that age, sex, race, primary site, histologic type, grade, stage, M stage, surgery, and tumor size were independent risk factors for elderly patients with MBT. The C-index of the training set and the validation set were 0.779 [0.759–0.799] and 0.801 [0.772–0.830], respectively. The AUC of the training and validation sets also showed similar results. The calibration curves of the training and validation sets indicated that the observed and predicted values were highly consistent. DCA suggested that the nomogram had potential clinical value compared with traditional TNM staging.Conclusion: We had established a new nomogram to predict the 1-, 3-, 5-year OS of elderly patients with MBT. This predictive model can help doctors and patients develop treatment plans and follow-up strategies.

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“…Considering that AJCC-Stage is composed of grade and AJCC-T/N/M, these variables form a high degree of collinearity ( Table S1 ) ( 26 , 27 ); thus the AJCC-Stage will not be included in univariate and multivariate analysis. Univariate analysis suggested that age, sex, pathological subtype (ICD-O-3 Hist/behave), primary site, grade, AJCC-T, AJCC-N, AJCC-M, tumor size, tumor extension, surgery type, radiation, and chemotherapy were significantly associated with CSS (all P≤0.05), whereas race, marital status, and laterality failed to reach statistical significance (P>0.05) ( Table 2 ).…”

Section: Resultsmentioning

confidence: 99%

“…Based on surgery codes (https://seer. cancer.gov/manuals/2021/AppendixC/Surgery_Codes_ Bones_2021.pdf), the types of surgery were classified into local or partial resection (codes 15,19,25,26), radical resection with limb salvage (code 30), amputation (codes 40, 41, 42, 50), forequarter/hindquarter/hemipelvectomy (codes 51, 52, 53, 54), and surgery, NOS (code 90) (22,23).…”

Section: Data Extraction and Endpoint Definitionmentioning

confidence: 99%

Development and validation of an online prognostic nomogram for osteosarcoma after surgery: a retrospective study based on the SEER database and external validation with single-center data

Feng¹,

Chen²,

Ye³

et al. 2022

Transl Cancer Res TCR

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Background: Osteosarcoma is a severe malignancy with relatively low morbidity and significant variation in patient outcomes. Thus the development of predictive models could help clinicians make betterindividualized decisions. The present study established a nomogram to predict postoperative survival of osteosarcoma patients using the large population-based Surveillance, Epidemiology, and End Results (SEER) database and validated it with single-center data from an Asian/Chinese population. Methods: Data from osteosarcoma patients who underwent surgery from 2000 to 2016 in the SEER database were obtained and were randomly divided into a training set (n=1,057) and an internal validation set (n=1,057). Data from osteosarcoma patients who underwent surgery in our hospital from 2013 to 2016 were collected as an external validation set (n=65). Univariate and multivariate Cox proportional hazard models were used in the training set to screen for prognostic factors and a nomogram was established to individually predict 1-, 3-and 5-year cancer-specific survival (CSS) and overall survival (OS). The discrimination and calibration ability of the nomogram were evaluated using the Harrell concordance index (C-index), calibration curves and area under the curve (AUC). The clinical utility was evaluated using decision curve analysis (DCA).Results: Predictive nomograms were generated using characteristics including age, pathological subtype, the American Joint Committee on Cancer (AJCC) group-N, AJCC-M, tumor size, and tumor extension for CSS and OS. The C-indexes for the CSS training set, the internal validation set, and the external validation set were 0.731, 0.713, and 0.721, respectively. The C-indexes of OS C-indices were 0.734, 0.706, and 0.719, respectively. The calibration curve suggested that the nomograms were accurate in their predictions and that DCA showed broad clinical benefits. Moreover, the present nomograms exhibited high accuracy (for

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Construction and Validation of Nomograms for Predicting the Prognosis of Juvenile Osteosarcoma: A Real-World Analysis in the SEER Database

Cited by 14 publications

References 28 publications

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study

Development and validation of an online prognostic nomogram for osteosarcoma after surgery: a retrospective study based on the SEER database and external validation with single-center data

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