Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis
Abstract Background Estimation of incidence and prognosis of melanomas with brain metastases (MBM) at initial diagnosis based on a large cohort is lacking in current research. This study aims to construct an effective prognostic nomogram for newly diagnosed MBM. Materials and Methods Patients diagno...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-12-01
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| Series: | Cancer Medicine |
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| Online Access: | https://doi.org/10.1002/cam4.2644 |
| _version_ | 1828886163683803136 |
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| author | Hong Liu Yan‐Bo Xu Cheng‐Cheng Guo Ming‐Xin Li Jia‐Li Ji Rong‐Rong Dong Ling‐Ling Zhang Xue‐Xin He |
| author_facet | Hong Liu Yan‐Bo Xu Cheng‐Cheng Guo Ming‐Xin Li Jia‐Li Ji Rong‐Rong Dong Ling‐Ling Zhang Xue‐Xin He |
| author_sort | Hong Liu |
| collection | DOAJ |
| description | Abstract Background Estimation of incidence and prognosis of melanomas with brain metastases (MBM) at initial diagnosis based on a large cohort is lacking in current research. This study aims to construct an effective prognostic nomogram for newly diagnosed MBM. Materials and Methods Patients diagnosed with melanomas from Surveillance, Epidemiology, and End Results program between 2010 and 2014 were enrolled in our study. Risk factors predicting brain metastases (BM) were identified using logistic regression analysis. Cox regression analysis was performed to identify prognostic factors of overall survival (OS). Nomogram for estimating 6‐, 9‐, and 12‐month OS was established based on Cox regression analysis. The discriminative ability and calibration of the nomogram were tested using C statistics, calibration plots, and Kaplan‐Meier curves. Results Sixty‐two thousand three hundred and sixty‐nine melanoma patients were enrolled, including 928 with BM. Sex, marital status, insurance status, subsite, surgery of primary sites, radiation, chemotherapy, bone metastases, liver metastases, and lung metastases were associated with MBM at initial diagnosis. On multivariable Cox regression, the following eight variables were incorporated in the prediction of OS: age, unmarried status, absence of surgery to primary sites or unknown, absence of radiation or unknown, absence of chemotherapy or unknown, with bone metastases, with liver metastases, and with lung metastases. The nomogram showed good predictive ability as indicated by discriminative ability and calibration, with the C statistics of 0.716 (95% CI, 0.695‐0.737). Conclusions The incidence and prognosis of MBM patients were well estimated in this study based on a large cohort. The nomogram performed well and could be a useful tool to predict prognosis. |
| first_indexed | 2024-12-13T11:40:39Z |
| format | Article |
| id | doaj.art-f6de3388a8a949f19412d348be050487 |
| institution | Directory Open Access Journal |
| issn | 2045-7634 |
| language | English |
| last_indexed | 2024-12-13T11:40:39Z |
| publishDate | 2019-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Cancer Medicine |
| spelling | doaj.art-f6de3388a8a949f19412d348be0504872022-12-21T23:47:40ZengWileyCancer Medicine2045-76342019-12-018187577758510.1002/cam4.2644Predictive value of a nomogram for melanomas with brain metastases at initial diagnosisHong Liu0Yan‐Bo Xu1Cheng‐Cheng Guo2Ming‐Xin Li3Jia‐Li Ji4Rong‐Rong Dong5Ling‐Ling Zhang6Xue‐Xin He7Department of Medical Oncology The Second Affiliated Hospital of Zhejiang University Hangzhou Zhejiang ChinaDepartment of Surgical Oncology The Second Affiliated Hospital of Zhejiang University Hangzhou Zhejiang ChinaState Key Laboratory of Oncology in South China Department of Neurosurgical Oncology Sun Yat‐Sen University Cancer Center Guangzhou Guangdong ChinaCollege of Medicine Upstate Medical University New York NY USADepartment of Oncology Affiliated Cancer Hospital of Nantong University Nantong Jiangsu ChinaDepartment of Internal Medicine The Children's Hospital of Zhejiang University Hangzhou Zhejiang ChinaDepartment of Oncology International Hospital of Peking University Beijing ChinaDepartment of Medical Oncology The Second Affiliated Hospital of Zhejiang University Hangzhou Zhejiang ChinaAbstract Background Estimation of incidence and prognosis of melanomas with brain metastases (MBM) at initial diagnosis based on a large cohort is lacking in current research. This study aims to construct an effective prognostic nomogram for newly diagnosed MBM. Materials and Methods Patients diagnosed with melanomas from Surveillance, Epidemiology, and End Results program between 2010 and 2014 were enrolled in our study. Risk factors predicting brain metastases (BM) were identified using logistic regression analysis. Cox regression analysis was performed to identify prognostic factors of overall survival (OS). Nomogram for estimating 6‐, 9‐, and 12‐month OS was established based on Cox regression analysis. The discriminative ability and calibration of the nomogram were tested using C statistics, calibration plots, and Kaplan‐Meier curves. Results Sixty‐two thousand three hundred and sixty‐nine melanoma patients were enrolled, including 928 with BM. Sex, marital status, insurance status, subsite, surgery of primary sites, radiation, chemotherapy, bone metastases, liver metastases, and lung metastases were associated with MBM at initial diagnosis. On multivariable Cox regression, the following eight variables were incorporated in the prediction of OS: age, unmarried status, absence of surgery to primary sites or unknown, absence of radiation or unknown, absence of chemotherapy or unknown, with bone metastases, with liver metastases, and with lung metastases. The nomogram showed good predictive ability as indicated by discriminative ability and calibration, with the C statistics of 0.716 (95% CI, 0.695‐0.737). Conclusions The incidence and prognosis of MBM patients were well estimated in this study based on a large cohort. The nomogram performed well and could be a useful tool to predict prognosis.https://doi.org/10.1002/cam4.2644melanomamelanoma brain metastasesnomogramprognosis |
| spellingShingle | Hong Liu Yan‐Bo Xu Cheng‐Cheng Guo Ming‐Xin Li Jia‐Li Ji Rong‐Rong Dong Ling‐Ling Zhang Xue‐Xin He Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis Cancer Medicine melanoma melanoma brain metastases nomogram prognosis |
| title | Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis |
| title_full | Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis |
| title_fullStr | Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis |
| title_full_unstemmed | Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis |
| title_short | Predictive value of a nomogram for melanomas with brain metastases at initial diagnosis |
| title_sort | predictive value of a nomogram for melanomas with brain metastases at initial diagnosis |
| topic | melanoma melanoma brain metastases nomogram prognosis |
| url | https://doi.org/10.1002/cam4.2644 |
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