Construction and Validation of the Prognostic Model for Patients With Neuroendocrine Cervical Carcinoma: A Competing Risk Nomogram Analysis
Purpose: Neuroendocrine cervical carcinoma (NECC) is an uncommon malignancy of the female reproductive system. This study aimed to evaluate the cancer-specific mortality and to construct prognostic nomograms for predicting the survival of patients with NECC.
Methods: we assembled the patients with NECC diagnosed between 2004 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Meanwhile, we identified other patients with NECC from the Wenling Maternal and Child Health Care Hospital between 2002 to 2017. Fine and Gray’s test and Kaplan-Meier methods were used to evaluate cancer-specific mortality and overall survival (OS) rates, respectively. Nomograms were constructed for predicting cancer-specific survival (CSS) and OS for patients with NECC. The developed nomograms were validated both internally and externally.
Results: a total of 894 patients with NECC extracted from the SEER database, then classified them into the training cohort (n=628) and the internal validation cohort (n=266). Besides, 106 patients from the Wenling Maternal and Child Health Care Hospital served as an external validation cohort. Nomograms for predicting CSS and OS were constructed on clinical predictors. The validation of nomograms was calculated by calibration curves and concordance indexes (C-indexes). Furthermore, the developed nomograms presented higher areas under the receiver operating characteristic (ROC) curves when compared to the FIGO staging system.
Conclusions: we established the first competing risk nomograms to predict the survival of patients with NECC. Such a model with excellent performance could be a practical tool for clinicians.
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Figure 6
Due to technical limitations, tables 1,2,3,4,5 are only available as a download in the Supplemental Files section.
Table 6 not available with this version.
This is a list of supplementary files associated with this preprint. Click to download.
The graph shows the optimal cut-off points of age via the X-tile program. The black dot demonstrates the best cut-off of age (A); the histogram and survival curves were represented based on cut-off points (B, C). The best cut-off points of age were 44 and 67 years.
The calibration curves of external validation cohort show the nomograms-predicted rates (X-axis) are correspondent with the actual survival rates (Y-axis), including the 3-year CSS (A) and OS (B), and the 5-year CSS (C) and OS (D).
Posted 23 Dec, 2020
Invitations sent on 27 Dec, 2020
On 21 Dec, 2020
On 21 Dec, 2020
On 21 Dec, 2020
On 12 Dec, 2020
Construction and Validation of the Prognostic Model for Patients With Neuroendocrine Cervical Carcinoma: A Competing Risk Nomogram Analysis
Posted 23 Dec, 2020
Invitations sent on 27 Dec, 2020
On 21 Dec, 2020
On 21 Dec, 2020
On 21 Dec, 2020
On 12 Dec, 2020
Purpose: Neuroendocrine cervical carcinoma (NECC) is an uncommon malignancy of the female reproductive system. This study aimed to evaluate the cancer-specific mortality and to construct prognostic nomograms for predicting the survival of patients with NECC.
Methods: we assembled the patients with NECC diagnosed between 2004 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Meanwhile, we identified other patients with NECC from the Wenling Maternal and Child Health Care Hospital between 2002 to 2017. Fine and Gray’s test and Kaplan-Meier methods were used to evaluate cancer-specific mortality and overall survival (OS) rates, respectively. Nomograms were constructed for predicting cancer-specific survival (CSS) and OS for patients with NECC. The developed nomograms were validated both internally and externally.
Results: a total of 894 patients with NECC extracted from the SEER database, then classified them into the training cohort (n=628) and the internal validation cohort (n=266). Besides, 106 patients from the Wenling Maternal and Child Health Care Hospital served as an external validation cohort. Nomograms for predicting CSS and OS were constructed on clinical predictors. The validation of nomograms was calculated by calibration curves and concordance indexes (C-indexes). Furthermore, the developed nomograms presented higher areas under the receiver operating characteristic (ROC) curves when compared to the FIGO staging system.
Conclusions: we established the first competing risk nomograms to predict the survival of patients with NECC. Such a model with excellent performance could be a practical tool for clinicians.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Due to technical limitations, tables 1,2,3,4,5 are only available as a download in the Supplemental Files section.
Table 6 not available with this version.