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The impact of the lymph node density on overall survival in patients with Wilms’ tumor: a SEER analysis
OBJECTIVE: The objective of this study was to determine the impact of the lymph node density (LND) on overall survival of patients with Wilms’ tumor (WT) using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Data from the SEER database were extracted from patients with WT i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896671/ https://www.ncbi.nlm.nih.gov/pubmed/29670401 http://dx.doi.org/10.2147/CMAR.S163514 |
Sumario: | OBJECTIVE: The objective of this study was to determine the impact of the lymph node density (LND) on overall survival of patients with Wilms’ tumor (WT) using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Data from the SEER database were extracted from patients with WT in whom the LND could be obtained. Patients were divided into a low LND group and high LND group. Survival curves based on the LND stratification were plotted using the Kaplan–Meier method and compared with the log-rank test. The impact of prognostic factors on overall survival was analyzed using Cox regression models. RESULTS: A total of 1,924 patients were identified from the database. Overall survival for the low LND group at 5, 10, and 20 years was significantly better than the high LND group (5-year survival: 94.1% vs 81.4%; 10-year survival: 92.6% vs 80.8%; 20-year survival: 90.6% vs 79.1%; P<0.001). In multivariate analysis, LND was a significant predictor of overall survival, regardless of whether it was a categorical variable or a continuous variable. Other significant predictors included age, race, SEER stage, and tumor laterality. CONCLUSION: LND was a significant risk factor for overall survival of patients with WT. LND may provide a better prediction of the prognosis of WT patients and may be helpful for designing better treatments. |
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