This preprint is under consideration at BMC Pulmonary Medicine. 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.
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Research article
Lina Wang
Henan University
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
Background: Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis. Our aim was to determine the prognostic factors of patients with pulmonary LCNEC after surgery based on competing risk model.
Methods: Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. For single outcome events, Kaplan-Meier method and Cox proportional risk model were used for analysis. Competing risk model was used in the analysis of multiple outcome events to adjust potential confounding factors. Competing risk model was used to calculate the cumulative incidence function of LCNEC-specific death. The Fine-Gray model was used for multivariate analysis to determine independent prognostic factors.
Results: We finally screened 614 patients with pulmonary LCNEC who underwent surgery. The univariate analysis showed that T stage, N stage, M stage, regional nodes positive (RNP), and radiotherapy were significantly associated with the cumulative incidence of LCSD (P < 0.05). The Fine-Gray model showed that age, T stage, M stage, RNP, radiotherapy, and chemotherapy were independent prognostic factors for patients with pulmonary LCNEC after surgery (P < 0.05).
Conclusion: Based on the competing risk model, we estimated a more accurate cumulative incidence of LCNEC-specific death and prognostic factors for patients with pulmonary LCNEC after surgery.
Keywords
pulmonary large-cell neuroendocrine carcinoma, competing risk model, prognostic factors, Surveillance, Epidemiology and End Results program
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CURRENT STATUS: Under Review
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Posted 22 Jun, 2020
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Editor assigned
On 19 Jun, 2020
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On 18 Jun, 2020
Editor invited
On 18 Jun, 2020
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Editorial decision: Major revision
On 20 May, 2020
Review #2 received
Received 15 May, 2020
Review #1 received
Received 26 Apr, 2020
Review #3 received
Received 24 Apr, 2020
Reviewer #3 agreed
On 18 Apr, 2020
Reviewer #2 agreed
On 17 Apr, 2020
Reviewer #1 agreed
On 15 Apr, 2020
Reviewers invited
Invitations sent on 29 Mar, 2020
Editor assigned
On 23 Mar, 2020
Submission checks complete
On 12 Mar, 2020
Editor invited
On 11 Mar, 2020
First submitted
On 01 Mar, 2020
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Subject Areas
Pulmonology
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This preprint is under consideration at BMC Pulmonary Medicine. 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
Lina Wang
Henan University
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 2
Posted 22 Jun, 2020
No community comments so far
Editor assigned
On 19 Jun, 2020
Submission checks complete
On 18 Jun, 2020
Editor invited
On 18 Jun, 2020
No comments provided
Editorial decision: Major revision
On 20 May, 2020
Review #2 received
Received 15 May, 2020
Review #1 received
Received 26 Apr, 2020
Review #3 received
Received 24 Apr, 2020
Reviewer #3 agreed
On 18 Apr, 2020
Reviewer #2 agreed
On 17 Apr, 2020
Reviewer #1 agreed
On 15 Apr, 2020
Reviewers invited
Invitations sent on 29 Mar, 2020
Editor assigned
On 23 Mar, 2020
Submission checks complete
On 12 Mar, 2020
Editor invited
On 11 Mar, 2020
First submitted
On 01 Mar, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Pulmonology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis. Our aim was to determine the prognostic factors of patients with pulmonary LCNEC after surgery based on competing risk model.
Methods: Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. For single outcome events, Kaplan-Meier method and Cox proportional risk model were used for analysis. Competing risk model was used in the analysis of multiple outcome events to adjust potential confounding factors. Competing risk model was used to calculate the cumulative incidence function of LCNEC-specific death. The Fine-Gray model was used for multivariate analysis to determine independent prognostic factors.
Results: We finally screened 614 patients with pulmonary LCNEC who underwent surgery. The univariate analysis showed that T stage, N stage, M stage, regional nodes positive (RNP), and radiotherapy were significantly associated with the cumulative incidence of LCSD (P < 0.05). The Fine-Gray model showed that age, T stage, M stage, RNP, radiotherapy, and chemotherapy were independent prognostic factors for patients with pulmonary LCNEC after surgery (P < 0.05).
Conclusion: Based on the competing risk model, we estimated a more accurate cumulative incidence of LCNEC-specific death and prognostic factors for patients with pulmonary LCNEC after surgery.
Figure 1
Figure 2
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