Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study
ObjectiveNeoadjuvant chemoradiotherapy (nCRT) plays an important role in patients with locally advanced esophageal cancer (EC). We aim to determine the prognostic risk factors and establish a reliable nomogram to predict overall survival (OS) based on SEER population.MethodsPatients with EC coded by...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Surgery |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsurg.2022.927457/full |
| _version_ | 1818551512547196928 |
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| author | Mingduan Chen Mingduan Chen Mingduan Chen Mingduan Chen Zhinuan Hong Zhinuan Hong Zhinuan Hong Zhinuan Hong Zhimin Shen Zhimin Shen Zhimin Shen Zhimin Shen Lei Gao Lei Gao Lei Gao Lei Gao Mingqiang Kang Mingqiang Kang Mingqiang Kang Mingqiang Kang |
| author_facet | Mingduan Chen Mingduan Chen Mingduan Chen Mingduan Chen Zhinuan Hong Zhinuan Hong Zhinuan Hong Zhinuan Hong Zhimin Shen Zhimin Shen Zhimin Shen Zhimin Shen Lei Gao Lei Gao Lei Gao Lei Gao Mingqiang Kang Mingqiang Kang Mingqiang Kang Mingqiang Kang |
| author_sort | Mingduan Chen |
| collection | DOAJ |
| description | ObjectiveNeoadjuvant chemoradiotherapy (nCRT) plays an important role in patients with locally advanced esophageal cancer (EC). We aim to determine the prognostic risk factors and establish a reliable nomogram to predict overall survival (OS) based on SEER population.MethodsPatients with EC coded by 04–15 in the SEER database were included. The data were divided into training group and verification group (7:3). The Cox proportional-risk model was evaluated by using the working characteristic curve (receiver operating characteristic curve, ROC) and the area under the curve (AUC), and a nomogram was constructed. The calibration curve was used to measure the consistency between the predicted and the actual results. Decision curve analysis (DCA) was used to evaluate its clinical value. The best cut-off value of nomogram score in OS was determined by using X-tile software, and the patients were divided into low-risk, medium-risk, and high-risk groups.ResultsA total of 2,209 EC patients who underwent nCRT were included in further analysis, including 1,549 in the training cohort and 660 in the validation group. By Cox analysis, sex, marital status, T stage, N stage, M stage, and pathological grade were identified as risk factors. A nomogram survival prediction model was established to predict the 36-, 60-, and 84-month survival. The ROC curve and AUC showed that the model had good discrimination ability. The correction curve was in good agreement with the prediction results. DCA further proved the effective clinical value of the nomogram model. The results of X-tile analysis showed that the long-term prognosis of patients in the low-risk subgroup was better in the training cohort and the validation cohort (p < 0.001).ConclusionThis study established an easy-to-use nomogram risk prediction model consisting of independent prognostic factors in EC patients receiving nCRT, helping to stratify risk, identify high-risk patients, and provide personalized treatment options. |
| first_indexed | 2024-12-12T09:00:53Z |
| format | Article |
| id | doaj.art-62a6f2028d334cfa83e283361c3af9ac |
| institution | Directory Open Access Journal |
| issn | 2296-875X |
| language | English |
| last_indexed | 2024-12-12T09:00:53Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Surgery |
| spelling | doaj.art-62a6f2028d334cfa83e283361c3af9ac2022-12-22T00:29:50ZengFrontiers Media S.A.Frontiers in Surgery2296-875X2022-05-01910.3389/fsurg.2022.927457927457Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based StudyMingduan Chen0Mingduan Chen1Mingduan Chen2Mingduan Chen3Zhinuan Hong4Zhinuan Hong5Zhinuan Hong6Zhinuan Hong7Zhimin Shen8Zhimin Shen9Zhimin Shen10Zhimin Shen11Lei Gao12Lei Gao13Lei Gao14Lei Gao15Mingqiang Kang16Mingqiang Kang17Mingqiang Kang18Mingqiang Kang19Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, ChinaKey Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, ChinaKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, ChinaDepartment of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, ChinaKey Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, ChinaKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, ChinaDepartment of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, ChinaKey Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, ChinaKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, ChinaDepartment of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, ChinaKey Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, ChinaKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, ChinaDepartment of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, ChinaKey Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, ChinaKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, ChinaObjectiveNeoadjuvant chemoradiotherapy (nCRT) plays an important role in patients with locally advanced esophageal cancer (EC). We aim to determine the prognostic risk factors and establish a reliable nomogram to predict overall survival (OS) based on SEER population.MethodsPatients with EC coded by 04–15 in the SEER database were included. The data were divided into training group and verification group (7:3). The Cox proportional-risk model was evaluated by using the working characteristic curve (receiver operating characteristic curve, ROC) and the area under the curve (AUC), and a nomogram was constructed. The calibration curve was used to measure the consistency between the predicted and the actual results. Decision curve analysis (DCA) was used to evaluate its clinical value. The best cut-off value of nomogram score in OS was determined by using X-tile software, and the patients were divided into low-risk, medium-risk, and high-risk groups.ResultsA total of 2,209 EC patients who underwent nCRT were included in further analysis, including 1,549 in the training cohort and 660 in the validation group. By Cox analysis, sex, marital status, T stage, N stage, M stage, and pathological grade were identified as risk factors. A nomogram survival prediction model was established to predict the 36-, 60-, and 84-month survival. The ROC curve and AUC showed that the model had good discrimination ability. The correction curve was in good agreement with the prediction results. DCA further proved the effective clinical value of the nomogram model. The results of X-tile analysis showed that the long-term prognosis of patients in the low-risk subgroup was better in the training cohort and the validation cohort (p < 0.001).ConclusionThis study established an easy-to-use nomogram risk prediction model consisting of independent prognostic factors in EC patients receiving nCRT, helping to stratify risk, identify high-risk patients, and provide personalized treatment options.https://www.frontiersin.org/articles/10.3389/fsurg.2022.927457/fullesophageal cancerneoadjuvant chemoradiotherapylong-term survivalpopulation-based studySEERfollow-up plan |
| spellingShingle | Mingduan Chen Mingduan Chen Mingduan Chen Mingduan Chen Zhinuan Hong Zhinuan Hong Zhinuan Hong Zhinuan Hong Zhimin Shen Zhimin Shen Zhimin Shen Zhimin Shen Lei Gao Lei Gao Lei Gao Lei Gao Mingqiang Kang Mingqiang Kang Mingqiang Kang Mingqiang Kang Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study Frontiers in Surgery esophageal cancer neoadjuvant chemoradiotherapy long-term survival population-based study SEER follow-up plan |
| title | Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study |
| title_full | Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study |
| title_fullStr | Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study |
| title_full_unstemmed | Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study |
| title_short | Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study |
| title_sort | prognostic nomogram for predicting long term overall survival of esophageal cancer patients receiving neoadjuvant chemoradiotherapy plus surgery a population based study |
| topic | esophageal cancer neoadjuvant chemoradiotherapy long-term survival population-based study SEER follow-up plan |
| url | https://www.frontiersin.org/articles/10.3389/fsurg.2022.927457/full |
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