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Research Article
Xu Cai
Wenling Maternal and Child Health Care Hospital
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
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.
Keywords
neuroendocrine cervical carcinoma, competing risk analysis, nomogram, prognosis
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Figure 6
This is a list of supplementary files associated with this preprint. Click to download.
- Table1.pdf
- Table2.pdf
- Table3.pdf
- Table4.pdf
- Table5.pdf
- TableS1.xlsx
- FigureS1.tif
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.
- FigureS2.tif
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).
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CURRENT STATUS: Under Review
Version 1
Posted 23 Dec, 2020
No community comments so far
Editorial decision: Major revision
On 11 May, 2021
Reviews received
Received 10 May, 2021
Reviews received
Received 23 Apr, 2021
Reviewers agreed
On 20 Apr, 2021
Reviews received
Received 22 Feb, 2021
Reviewers agreed
On 15 Feb, 2021
Reviewers agreed
On 15 Feb, 2021
Reviewers invited
Invitations sent on 27 Dec, 2020
Editor assigned
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
First submitted
On 12 Dec, 2020
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This preprint is under consideration at BMC Cancer. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Xu Cai
Wenling Maternal and Child Health Care Hospital
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 23 Dec, 2020
No community comments so far
Editorial decision: Major revision
On 11 May, 2021
Reviews received
Received 10 May, 2021
Reviews received
Received 23 Apr, 2021
Reviewers agreed
On 20 Apr, 2021
Reviews received
Received 22 Feb, 2021
Reviewers agreed
On 15 Feb, 2021
Reviewers agreed
On 15 Feb, 2021
Reviewers invited
Invitations sent on 27 Dec, 2020
Editor assigned
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
First submitted
On 12 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
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
This is a list of supplementary files associated with this preprint. Click to download.
- Table1.pdf
- Table2.pdf
- Table3.pdf
- Table4.pdf
- Table5.pdf
- TableS1.xlsx
- FigureS1.tif
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.
- FigureS2.tif
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).
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