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已发表论文
用于预测胰腺癌患者生存的列线图
Authors Song W, Miao DL, Chen L
Received 19 October 2017
Accepted for publication 7 December 2017
Published 24 January 2018 Volume 2018:11 Pages 539—545
DOI https://doi.org/10.2147/OTT.S154599
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Manfred Beleut
Peer reviewer comments 2
Editor who approved publication: Dr William Cho
Background: The purpose of
this study was to develop a nomogram to predict cancer-specific survival (CSS)
in pancreatic cancer (PC).
Patients and methods: We used the Surveillance, Epidemiology, and End Results (SEER) database to analyze 53,028 patients diagnosed with PC from 2004 to 2014 and randomly divided them into the training (n=26,583) cohort and validation (n=26,445) cohort. Univariate and multivariate analyses were used to select independent prognostic factors. We used significant prognostic factors for constructing a nomogram based on Cox regression analyses. Validation of the nomogram was assessed by discrimination and calibration.
Results: According to the multivariate models of training cohort, a nomogram that combined age, race, tumor location, marital status, tumor size, TNM stage, tumor grade, and surgery was constructed for predicting CSS. The internally validated and externally validated C-indexes were 0.741 and 0.734, respectively. The calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year CSS accurately.
Conclusion: A nomogram effectively predicts survival in patients with PC. This prognostic model may be considered for use in clinical practice.
Keywords: pancreatic cancer, nomogram, SEER, cancer-specific survival, prognosis
Patients and methods: We used the Surveillance, Epidemiology, and End Results (SEER) database to analyze 53,028 patients diagnosed with PC from 2004 to 2014 and randomly divided them into the training (n=26,583) cohort and validation (n=26,445) cohort. Univariate and multivariate analyses were used to select independent prognostic factors. We used significant prognostic factors for constructing a nomogram based on Cox regression analyses. Validation of the nomogram was assessed by discrimination and calibration.
Results: According to the multivariate models of training cohort, a nomogram that combined age, race, tumor location, marital status, tumor size, TNM stage, tumor grade, and surgery was constructed for predicting CSS. The internally validated and externally validated C-indexes were 0.741 and 0.734, respectively. The calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year CSS accurately.
Conclusion: A nomogram effectively predicts survival in patients with PC. This prognostic model may be considered for use in clinical practice.
Keywords: pancreatic cancer, nomogram, SEER, cancer-specific survival, prognosis
