Nomograms for predicting overall survival and cancer‐specific survival of chondroblastic osteosarcoma patients

Gao, Zhongyang; Zhou, Songlin; Song, Hui; Wang, Yudong; He, Xijing

doi:10.1002/jso.26185

Cited by 13 publications

(18 citation statements)

References 37 publications

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“…All subjects ( n = 1749) were randomly divided into two groups using the R package caret: the development cohort (67%, n = 1165) and the validation cohort (33%, n = 584). It has been proven suitable to include 2/3–4/5 patients as the development cohort ( 17 , 18 ). The baseline values of the total cohort and the development cohort are displayed in Table 1 , according to whether CAA was present.…”

Section: Resultsmentioning

confidence: 99%

The Significance of Symptoms in Predicting Coronary Artery Aneurysms of Kawasaki Disease, Especially in Female Patients

Sun

et al. 2022

Front. Cardiovasc. Med.

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BackgroundKawasaki disease (KD) is an acute febrile systemic vasculitis of unknown etiology that occurs during early childhood, commonly involving the coronary artery, and can lead to coronary artery aneurysms (CAAs).MethodsThe demographic, clinical, and laboratory data of KD patients without coronary artery lesions (N-CAL) and with CAA were collected during 2005–2020 at the Second Affiliated Hospital of Wenzhou Medical University. The patients were divided into the development cohort and the validation cohort. First, we compared the general information, symptoms, and laboratory data of N-CAL and CAA patients in the development cohort and the total cohort and screened out the different indices by logistic regression analysis. Then, we established three models and compared the area under the curve (AUC) values of the receiver operating characteristic (ROC) curves to identify meaningful models for CAA, which were further verified by decision curve analysis (DCA). Second, taking into account previous reports on the importance of gender to CAA, gender stratification was conducted.ResultsThe analysis of clinical and blood indices revealed the following novel features: (i) Many factors were found to be related to CAA, including IVIG resistance and the symptoms of rash, oral changes, and cervical lymphadenopathy. (ii) The development cohort was analyzed by logistic regression, and three models were established. The ROC curves showed that Model 2, composed of IVIG resistance, rash, oral changes, and cervical lymphadenopathy, had a better AUC value and easily to evaluate in the prediction of CAA. (iii) The selected model for predicting CAA in the development cohort was further confirmed in the validation cohort through DCAs. (iv)We further compared the items enrolled in the three models above between the N-CAL and CAA groups by sex, and the results indicated that female KD patients without rash, oral changes, and cervical lymphadenopathy were more likely to develop CAA.ConclusionThe absence of rash, oral changes, and cervical lymphadenopathy are risk factors for CAA, especially in female KD patients. Accurately recognizing symptoms, early diagnosis, and standard treatment for KD are key to reducing the incidence of CAA.

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Section: Resultsmentioning

confidence: 99%

The Significance of Symptoms in Predicting Coronary Artery Aneurysms of Kawasaki Disease, Especially in Female Patients

Sun

et al. 2022

Front. Cardiovasc. Med.

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“…Nomogram, an easy-to-use comprehensive tool, which could incorporate the conducive factors together, is of great significance for clinicians to accurately clarify diagnosis and predict survival of individual patient. [17][18][19][20] As for patients with osteosarcoma, several predictive models have been constructed in previous studies, 6,11,13 however, limited data is available for this special age group. Besides, independent predictors for OS and CSS in elderly patients with osteosarcoma are still controversial until now.…”

Section: Discussionmentioning

confidence: 99%

“…[1][2][3] Due to their different gene expression, therapeutic response, and their heterogeneous histological subtypes, osteosarcoma can be diagnostically and prognostically challenging. [4][5][6] Moreover, patients with osteosarcoma older than 40 years old exhibit a lower survival rate than those of adolescents even though multidisciplinary treatment including surgery and chemotherapy. [7][8][9] Thus, identification of older patients with osteosarcoma who are at high risk of mortality can ensure the implementation of appropriate treatment and have a substantial impact on prognosis.…”

Section: Introductionmentioning

confidence: 99%

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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“…After the inclusion and exclusion criteria, there were 152 non-LAA stroke patients were admitted to the study. In previous studies, it is common and suitable to include 2/3-4/5 patients as the development group (Gao et al 2020;Du 2020;Wang 2020;Guan 2019). In our study, we used R (packge caret) to randomly select 2/3 of the patients as the development group, and the remaining patients as the validation group.…”

Section: Methodsmentioning

confidence: 99%

Cardiac parameters affect prognosis in patients with non-large atherosclerotic infarction

Zeng

Zhang

Cheng

et al. 2021

Mol Med

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Background Although large artery atherosclerosis (LAA) is the most common type of cerebral infarction, non-LAA is not uncommon. The purpose of this paper is to investigate the prognosis of patients with non-LAA and to establish a corresponding nomogram. Patients and methods Between June 2016 and June 2017, we had 1101 admissions for acute ischemic stroke (AIS). Of these, 848 were LAA and 253 were non-LAA. Patients were followed up every 3 months with a minimum of 1 year of follow-up. After excluding patients who were lost follow-up and patients who did not meet the inclusion criteria, a total of 152 non-LAA patients were included in this cohort study. After single-factor analysis and multifactor logistic regression analysis, the risk factors associated with prognosis were derived and different nomograms were developed based on these risk factors. After comparison, the best model is derived. Results Logistics regression found that the patient’s National Institutes of Health Stroke Scale (NIHSS) score, ejection fraction (EF), creatine kinase-MB (CK-MB), age, neutrophil-to-lymphocyte ratio (NLR), aspartate aminotransferase (AST), and serum albumin were independently related to the patient’s prognosis. We thus developed three models: model 1: single NIHSS score, AUC = 0.8534; model 2, NIHSS + cardiac parameters (CK-MB, EF), AUC = 0.9325; model 3, NIHSS + CK−MB + EF + age + AST + NLR + albumin, AUC = 0.9598. We compare the three models: model 1 vs model 2, z = − 2.85, p = 0.004; model 2 vs model 3, z = − 1.58, p = 0.122. Therefore, model 2 is considered to be the accurate and convenient model. Conclusions Predicting the prognosis of patients with non-LAA is important, and our nomogram, built on the NIHSS and cardiac parameters, can predict the prognosis accurately and provide a powerful reference for clinical decision making.

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Nomograms for predicting overall survival and cancer‐specific survival of chondroblastic osteosarcoma patients

Cited by 13 publications

References 37 publications

The Significance of Symptoms in Predicting Coronary Artery Aneurysms of Kawasaki Disease, Especially in Female Patients

The Significance of Symptoms in Predicting Coronary Artery Aneurysms of Kawasaki Disease, Especially in Female Patients

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Cardiac parameters affect prognosis in patients with non-large atherosclerotic infarction

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