A Predictive Nomogram for Early Death of Metastatic Gastric Cancer: A Retrospective Study in the SEER Database and China

Zhu, Ying; Fang, Xiongfeng; Wang, Lanqing; Zhang, Tao; Yu, Dandan

doi:10.7150/jca.46563

Cited by 40 publications

(36 citation statements)

References 29 publications

(28 reference statements)

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“…Thus, precise forecasts of the survival rates of LMS patients with lung metastasis is essential if clinicians are to make effective medical decisions. The nomogram is a visualization tool for oncology-related prediction that can help clinicians to make individualized survival predictions and offer personalized treatments (21,22). However, previously, no nomogram for predicting OS and CSS in LMS patients with lung metastasis existed.…”

Section: Discussionmentioning

confidence: 99%

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis

Li¹,

Wei²,

Gan³

et al. 2021

J Thorac Dis

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Background: This study sought to assess the prognostic factors for leiomyosarcoma (LMS) patients with lung metastasis and construct web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS). Method: Patients diagnosed with LMS combined with lung metastasis between 2010 and 2016 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into a training set and a testing set. The X-tile analysis provides the best age and tumor size cut-off point, and changes continuous variables into categorical variables. The independent prognostic factors were determined by Cox regression analysis, and 2 nomograms were established. Receiver operating characteristic curves and calibration curves were used to evaluate the nomograms. Based on the nomograms, 2 web-based nomograms were established. Results: Two hundred and twenty-eight cases were included in the OS nomogram construction, and were randomly divided into a training set (n=160) and a validation set (n=68). Age, T stage, bone metastasis, surgery, chemotherapy, marital status, tumor size, and tumor site were found to be correlated with OS. One hundred and eighty-three cases were enrolled in the CSS nomogram construction, and randomly divided into a training set (n=129) and a validation set (n=54). Age, bone metastasis, surgery, chemotherapy, tumor size, and tumor site were found to be correlated with CSS. Two nomograms were established to predict OS and CSS. In the training set, the areas under the curve of the nomogram for predicting 1-, 2-, and 3-year OS were 0.783, 0.830, and 0.832, respectively, and those for predicting 1-, 2-, and 3-year CSS were 0.889, 0.777, and 0.884, respectively. Two web-based nomograms were established to predict OS (https://wenn23. shinyapps.io/lmslmosapp/), and CSS (https://wenn23.shinyapps.io/lmslmcssapp/). Conclusion:The developed web-based nomogram is a useful tool for accurately analyzing the prognosis of LMS patients with lung metastasis, and could help clinical doctors to make personalized clinical decisions.

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Section: Discussionmentioning

confidence: 99%

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis

Li¹,

Wei²,

Gan³

et al. 2021

J Thorac Dis

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show abstract

“… 25 , 26 For malignant and advanced tumors, only a few studies have investigated early death. 9 – 11 Based on different diseases and risk factors, many studies have defined early death. 27 – 29 Using a definition of early death that is too long or short is not conducive for clinicians to provide effective treatment.…”

Section: Discussionmentioning

confidence: 99%

“…Studies on high-risk factors have been conducted in gastrointestinal tumors and endometrial cancers, but few have been reported in LUAD. 9 – 11 Furthermore, risk factors for early death in patients with bone metastasis of LUAD have not been well documented. Therefore, analyzing risk factors of early death (survival time ≤7 months) in patients with LUAD and bone metastasis is clinically significant.…”

Section: Introductionmentioning

confidence: 99%

A predictive web-based nomogram for the early death of patients with lung adenocarcinoma and bone metastasis: a population-based study

Wei

Cao

et al. 2021

J Int Med Res

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Objective To identify risk factors and develop predictive web-based nomograms for the early death of patients with bone metastasis of lung adenocarcinoma (LUAD). Methods Patients in the Surveillance, Epidemiology, and End Results database diagnosed with bone metastasis of LUAD between 2010 and 2016 were included and randomly divided into training and validation sets. Early death-related risk factors (survival time ≤7 months) were evaluated by logistic regression. Two predictive nomograms were established and validated by calibration curves, receiver operating characteristic curves, and decision curve analysis. Results A total of 9189 patients (56.59%) died from all causes within 7 months of being diagnosed, including 8585 patients (56.67%) who died from cancer-specific causes. Age >65 years, sex (men), T stage (T3 and T4), N stage (N2 and N3), brain metastasis, and liver metastasis were risk factors for all-cause and cancer-specific early death. The area under the curves of the nomograms for all-cause and cancer-specific early death prediction were 0.754 and 0.753 (training set) and 0.747 and 0.754 (validation set), respectively. Further analysis showed that the two nomograms performed well. Conclusions Our two web-based nomograms for all-cause and cancer-specific early death provide valuable tools for predicting early death in these patients.

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“…Figure 1 shows the flow diagram of the patient selection criteria. Considering the malignancy of pancreatic cancer and definition of previous studies, early death was defined as death within 3 months after first diagnosis ( 12 , 13 ).…”

Section: Methodsmentioning

confidence: 99%

Development and Validation of a Simple-to-Use Nomogram to Predict Early Death in Metastatic Pancreatic Adenocarcinoma

Zhang

2021

Front. Oncol.

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BackgroundPancreatic adenocarcinoma (PCa) is a highly aggressive malignancy with high risk of early death (survival time ≤3 months). The present study aimed to identify associated risk factors and develop a simple-to-use nomogram to predict early death in metastatic PCa patients.MethodsPatients diagnosed with metastatic PCa between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were collected for model construction and internal validation. An independent data set was obtained from China for external validation. Independent risk variables contributed to early death were identified by logistic regression models, which were then used to construct a nomogram. Internal and external validation was performed to evaluate the nomogram using calibration curves and the receiver operating characteristic curves.ResultsA total of 19,464 patients in the SEER cohort and 67 patients in the Chinese cohort were included. Patients from the SEER database were randomly divided into the training cohort (n = 13,040) and internal validation cohort (n = 6,424). Patients in the Chinese cohort were selected for the external validation cohort. Overall, 10,484 patients experienced early death in the SEER cohort and 35 in the Chinese cohort. A reliable nomogram was constructed on the basis of 11 significant risk factors. Internal validation and external validation of the nomogram showed high accuracy in predicting early death. Decision curve analysis demonstrated that this predictive nomogram had excellent and potential clinical applicability.ConclusionThe nomogram provided a simple-to-use tool to distinguish early death in patients with metastatic PCa, assisting clinicians in implementing individualized treatment regimens.

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A Predictive Nomogram for Early Death of Metastatic Gastric Cancer: A Retrospective Study in the SEER Database and China

Cited by 40 publications

References 29 publications

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis

A predictive web-based nomogram for the early death of patients with lung adenocarcinoma and bone metastasis: a population-based study

Development and Validation of a Simple-to-Use Nomogram to Predict Early Death in Metastatic Pancreatic Adenocarcinoma

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