Brain Metastasis From Renal Cell Carcinoma

Masuda, Fujio; Arai, Yoshikazu; Ohnishi, Tetsuro; Nakada, J; Suzuki, Masayasu; Machida, Toyohei

doi:10.5980/jpnjurol1928.75.2_278

Cited by 3 publications

(6 citation statements)

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“…Chemotherapy and immunotherapy generally are not effective in the palliative management of intracranial metastases from RCC 5. The role of chemotherapy and immunotherapy for brain lesions is limited because of blood‐brain barrier integrity.…”

Section: Discussionmentioning

confidence: 99%

“…Renal cell carcinoma (RCC) accounts for approximately 90% of primary kidney tumors and 1% of all cancers 1. The percentage of patients who develop brain metastases during the course of RCC is not high (4‐13%) 2‐7. However, in > 50% of patients with cerebral metastases from RCC, multiple tumors are present 3‐8.…”

mentioning

confidence: 99%

“…The percentage of patients who develop brain metastases during the course of RCC is not high (4‐13%) 2‐7. However, in > 50% of patients with cerebral metastases from RCC, multiple tumors are present 3‐8. The majority of these patients have metastases at other sites, most often in the lung 3, 5, 7, 9.…”

mentioning

confidence: 99%

“…However, in > 50% of patients with cerebral metastases from RCC, multiple tumors are present 3‐8. The majority of these patients have metastases at other sites, most often in the lung 3, 5, 7, 9. Various protocols of fractionated whole brain radiation therapy (WBRT) have been used alone or after surgical resection.…”

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confidence: 99%

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Stereotactic radiosurgery for brain metastasis from renal cell carcinoma

Mori

Kondziolka

Flickinger

et al. 1998

Cancer

182

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Stereotactic radiosurgery for brain metastasis from renal cell carcinoma

Mori

Kondziolka

Flickinger

et al. 1998

Cancer

182

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“…Brain metastasis is an unfavorable prognostic factor in renal cell carcinoma (RCC) and occurs in 4-13% of patients (Masuda et al, 1984;Fujime et al, 1986;Gay et al, 1987;Marshall et al, 1990;Shibui et al, 1990;Yonese et al, 1995). The median time interval between the diagnosis of RCC and the discovery of brain metastasis ranges from 11 to 19 months (Gay et al, 1987;Yonese et al, 1995;Harada et al, 1999).…”

Section: Genitourinary Cancersmentioning

confidence: 99%

Neurological complications of solid tumors

Aregawi

Sherman

Schiff

2012

Handbook of Clinical Neurology

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A clinical prediction model for predicting the risk of liver metastasis from renal cell carcinoma based on machine learning

Wang

Liu

et al. 2023

Front. Endocrinol.

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BackgroundRenal cell carcinoma (RCC) is a highly metastatic urological cancer. RCC with liver metastasis (LM) carries a dismal prognosis. The objective of this study is to develop a machine learning (ML) model that predicts the risk of RCC with LM, which is used to assist clinical treatment.MethodsThe retrospective study data of 42,547 patients with RCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. ML includes algorithmic methods and is a fast-rising field that has been widely used in the biomedical field. Logistic regression (LR), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), random forest (RF), decision tree (DT), and naive Bayesian model [Naive Bayes Classifier (NBC)] were applied to develop prediction models to predict the risk of RCC with LM. The six models were 10-fold cross-validated, and the best-performing model was selected based on the area under the curve (AUC) value. A web online calculator was constructed based on the best ML model.ResultsBone metastasis, lung metastasis, grade, T stage, N stage, and tumor size were independent risk factors for the development of RCC with LM by multivariate regression analysis. In addition, the correlation of the relative proportions of the six clinical variables was shown by a heat map. In the prediction models of RCC with LM, the mean AUC of the XGB model among the six ML algorithms was 0.947. Based on the XGB model, the web calculator (https://share.streamlit.io/liuwencai4/renal_liver/main/renal_liver.py) was developed to evaluate the risk of RCC with LM.ConclusionsThis XGB model has the best predictive effect on RCC with LM. The web calculator constructed based on the XGB model has great potential for clinicians to make clinical decisions and improve the prognosis of RCC patients with LM.

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Brain Metastasis From Renal Cell Carcinoma

Cited by 3 publications

References 0 publications

Stereotactic radiosurgery for brain metastasis from renal cell carcinoma

Stereotactic radiosurgery for brain metastasis from renal cell carcinoma

Neurological complications of solid tumors

A clinical prediction model for predicting the risk of liver metastasis from renal cell carcinoma based on machine learning

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