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Circulating tumor cells as a new predictive and prognostic factor in patients with small cell lung cancer
Background: Small cell lung cancer (SCLC) is the most malignant type of lung cancer characterized by rapid progression, early metastasis and recurrence. In recent years, circulating tumor cells (CTCs) were found to play an important role in tumor invasion, metastasis, recurrence and prognosis. Metho...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052935/ https://www.ncbi.nlm.nih.gov/pubmed/32127938 http://dx.doi.org/10.7150/jca.35308 |
Sumario: | Background: Small cell lung cancer (SCLC) is the most malignant type of lung cancer characterized by rapid progression, early metastasis and recurrence. In recent years, circulating tumor cells (CTCs) were found to play an important role in tumor invasion, metastasis, recurrence and prognosis. Methods: CTCs were detected in 138 patients with newly diagnosed SCLC from January 2012 to December 2018. Nomogram prediction models were constructed based on prognostic factors screened by multivariate Cox regression analysis and the risk stratification of SCLC patients were performed on basis of nomogram points. A total of 108 patients from January 2012 to December 2016 were assigned to a training group, and 30 patients from January 2017 to December 2018 were included into the validation group for nomogram analysis. This study was approved by ethics committee of Guangzhou First People's Hospital and all subjects provided informed consent. Results: The number of CTCs was associated with age, lymph node metastasis (N), distant metastasis (M), TNM staging, and NSE. The high number of CTC predicted adverse prognosis, and the AUC of time-dependent ROC curve was all high than 0.5. In the training group, after multivariate COX regression screening, the factors in the median survival time (MST) and overall survival (OS) nomogram prediction models were age, TNM, CTC, NSE and treatment mode. The C-index of the nomograms in internal validation for MST and OS was 0.813 and in external validation for MST and OS were 0.885. The AUC of ROC curves for nomogram were high than 0.5. Finally, risk stratification could be effectively performed on the basis of nomogram points. Conclusions: CTC can be served as a predictive and prognostic factor for SCLC, and the nomogram models constructed by CTC and multiple clinical parameters can comprehensively predict the prognosis of SCLC patients and perform risk stratification. |
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