Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study
Backgrounds: Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rarely high-grade neuroendocrine carcinoma of the lung with features of both small cell and non-small cell lung cancer. In this study, we aim to construct a prognostic nomogram that integrates the clinical features and treatment...
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MDPI AG
2023-06-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/12/12/4126 |
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| author | Xiaoli Mu Dan Pu Yajuan Zhu Yixin Zhou Qiang Wu Qing Liu Liyuan Yin Yan Li |
| author_facet | Xiaoli Mu Dan Pu Yajuan Zhu Yixin Zhou Qiang Wu Qing Liu Liyuan Yin Yan Li |
| author_sort | Xiaoli Mu |
| collection | DOAJ |
| description | Backgrounds: Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rarely high-grade neuroendocrine carcinoma of the lung with features of both small cell and non-small cell lung cancer. In this study, we aim to construct a prognostic nomogram that integrates the clinical features and treatment options to predict disease-specific survival (DSS). Methods: A total of 713 patients diagnosed with LCNEC were from the US National Cancer Institute’s Surveillance Epidemiology and End Results (SEER) registry between 2010–2016. Cox proportional hazards analysis was conducted to choose the significant predictors of DSS. External validation was performed using 77 patients with LCNEC in the West China Hospital Sichuan University between 2010–2018. The predictive accuracy and discriminative capability were estimated by the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve. The clinical applicability of the nomogram was verified through the decision curve analysis (DCA). Additionally, we conducted a subgroup analysis of data available in the external cohort that may impact prognosis but was not recorded in the SEER database. Results: Six independent risk factors for DSS were identified and integrated into the nomogram. The nomogram achieved good C- indexes of 0.803 and 0.767 in the training and validation group, respectively. Moreover, the calibration curves for the probability of survival showed good agreement between prediction by nomogram and actual observation in 1-, 3- and 5-year DSS. The ROC curves demonstrated the prediction accuracy of the established nomogram (all Area Under Curve (AUC) > 0.8). DCA exhibited the favorable clinical applicability of the nomogram in the prediction of LCNEC survival. A risk classification system was built which could perfectly classify LCNEC patients into high-, medium- and low-risk groups (<i>p</i> < 0.001). The survival analysis conducted on the West China Hospital cohort indicated that whole brain radiation therapy (WBRT), prophylactic cranial irradiation (PCI), surgical procedures, tumor grade, Ki-67, and PD-L1 expression were not significantly associated with DSS. Conclusion: This study has effectively developed a prognostic nomogram and a corresponding risk stratification system, which demonstrate promising potential for predicting the DSS of patients with LCNEC. |
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| language | English |
| last_indexed | 2024-03-11T02:18:01Z |
| publishDate | 2023-06-01 |
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| spelling | doaj.art-0e571c2fba64467aa2d8cdd8c6be41e62023-11-18T11:01:20ZengMDPI AGJournal of Clinical Medicine2077-03832023-06-011212412610.3390/jcm12124126Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort StudyXiaoli Mu0Dan Pu1Yajuan Zhu2Yixin Zhou3Qiang Wu4Qing Liu5Liyuan Yin6Yan Li7The Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaLung Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaThe Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaThe Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaLung Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaDepartment of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaLung Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaLung Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, ChinaBackgrounds: Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rarely high-grade neuroendocrine carcinoma of the lung with features of both small cell and non-small cell lung cancer. In this study, we aim to construct a prognostic nomogram that integrates the clinical features and treatment options to predict disease-specific survival (DSS). Methods: A total of 713 patients diagnosed with LCNEC were from the US National Cancer Institute’s Surveillance Epidemiology and End Results (SEER) registry between 2010–2016. Cox proportional hazards analysis was conducted to choose the significant predictors of DSS. External validation was performed using 77 patients with LCNEC in the West China Hospital Sichuan University between 2010–2018. The predictive accuracy and discriminative capability were estimated by the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve. The clinical applicability of the nomogram was verified through the decision curve analysis (DCA). Additionally, we conducted a subgroup analysis of data available in the external cohort that may impact prognosis but was not recorded in the SEER database. Results: Six independent risk factors for DSS were identified and integrated into the nomogram. The nomogram achieved good C- indexes of 0.803 and 0.767 in the training and validation group, respectively. Moreover, the calibration curves for the probability of survival showed good agreement between prediction by nomogram and actual observation in 1-, 3- and 5-year DSS. The ROC curves demonstrated the prediction accuracy of the established nomogram (all Area Under Curve (AUC) > 0.8). DCA exhibited the favorable clinical applicability of the nomogram in the prediction of LCNEC survival. A risk classification system was built which could perfectly classify LCNEC patients into high-, medium- and low-risk groups (<i>p</i> < 0.001). The survival analysis conducted on the West China Hospital cohort indicated that whole brain radiation therapy (WBRT), prophylactic cranial irradiation (PCI), surgical procedures, tumor grade, Ki-67, and PD-L1 expression were not significantly associated with DSS. Conclusion: This study has effectively developed a prognostic nomogram and a corresponding risk stratification system, which demonstrate promising potential for predicting the DSS of patients with LCNEC.https://www.mdpi.com/2077-0383/12/12/4126pulmonary large cell neuroendocrine carcinomadisease-specific survivalprophylactic cranial irradiationnomogram |
| spellingShingle | Xiaoli Mu Dan Pu Yajuan Zhu Yixin Zhou Qiang Wu Qing Liu Liyuan Yin Yan Li Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study Journal of Clinical Medicine pulmonary large cell neuroendocrine carcinoma disease-specific survival prophylactic cranial irradiation nomogram |
| title | Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study |
| title_full | Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study |
| title_fullStr | Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study |
| title_full_unstemmed | Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study |
| title_short | Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study |
| title_sort | lung large cell neuroendocrine carcinoma a population based retrospective cohort study |
| topic | pulmonary large cell neuroendocrine carcinoma disease-specific survival prophylactic cranial irradiation nomogram |
| url | https://www.mdpi.com/2077-0383/12/12/4126 |
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