Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation
Abstract Aim To construct a predictive model based on the LODDS stage established for patients with late-onset colon adenocarcinoma to enhance survival stratification. Methods Late-onset colon adenocarcinoma data were obtained from the public database. After determining the optimal LODDS truncation...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-01849-0 |
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| author | Chen Chen Heng-Bo Xia Wei-Wei Yuan Meng-Ci Zhou Xue Zhang A.-Man Xu |
| author_facet | Chen Chen Heng-Bo Xia Wei-Wei Yuan Meng-Ci Zhou Xue Zhang A.-Man Xu |
| author_sort | Chen Chen |
| collection | DOAJ |
| description | Abstract Aim To construct a predictive model based on the LODDS stage established for patients with late-onset colon adenocarcinoma to enhance survival stratification. Methods Late-onset colon adenocarcinoma data were obtained from the public database. After determining the optimal LODDS truncation value for the training set via X-tile software, we created a new staging system by integrating the T stage and M stage. Nomograms of the prognostic model were created after Cox analyses identified independent risk factors for overall survival (OS) and cause-specific survival (CSS) and were validated internally and externally. The efficacy of the nomograms was assessed by calibration, time-dependent area under the curve (AUC) and decision curve analysis (DCA). Finally, the prognoses of the patients were compared by plotting survival curves on the basis of risk scores. Results A total of 103,291 and 100 patients with late-onset colon adenocarcinoma (50–80 years old) were screened from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. Cox regression analysis revealed independent risk factors for OS and CSS, including age, gender, race, size, LODDS stage, PLN stage, LNR stage, and TNM stage. A comparison of the four models constructed on the basis of different stages revealed that the model constructed with the LODDS stage had the minimum AIC (Akaike information criterion), maximum C-index (concordance index) and time-dependent AUC. Nomograms based on the LODDS stage were constructed and successfully validated for accuracy and clinical utility. Conclusion For patients with late-onset colon adenocarcinoma, LODDS may achieve optimal predictive performance. Furthermore, compared to the 8th edition of the AJCC classification system, the nomogram based on LODDS stage may demonstrate superior survival prediction capabilities. |
| format | Article |
| id | doaj-art-0c957b76bffa44dfa3809da8294b071b |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-0c957b76bffa44dfa3809da8294b071b2025-02-02T12:30:35ZengSpringerDiscover Oncology2730-60112025-01-0116111510.1007/s12672-025-01849-0Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validationChen Chen0Heng-Bo Xia1Wei-Wei Yuan2Meng-Ci Zhou3Xue Zhang4A.-Man Xu5Department of General Surgery, Anhui Public Health Clinical CenterDepartment of General Surgery, The First Affiliated Hospital of Anhui Medical UniversityDepartment of General Surgery, Anhui Public Health Clinical CenterDepartment of Interventional Radiology, Affiliated Hospital of Xuzhou Medical UniversityDepartment of General Surgery, The First Affiliated Hospital of Anhui Medical UniversityDepartment of General Surgery, The First Affiliated Hospital of Anhui Medical UniversityAbstract Aim To construct a predictive model based on the LODDS stage established for patients with late-onset colon adenocarcinoma to enhance survival stratification. Methods Late-onset colon adenocarcinoma data were obtained from the public database. After determining the optimal LODDS truncation value for the training set via X-tile software, we created a new staging system by integrating the T stage and M stage. Nomograms of the prognostic model were created after Cox analyses identified independent risk factors for overall survival (OS) and cause-specific survival (CSS) and were validated internally and externally. The efficacy of the nomograms was assessed by calibration, time-dependent area under the curve (AUC) and decision curve analysis (DCA). Finally, the prognoses of the patients were compared by plotting survival curves on the basis of risk scores. Results A total of 103,291 and 100 patients with late-onset colon adenocarcinoma (50–80 years old) were screened from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. Cox regression analysis revealed independent risk factors for OS and CSS, including age, gender, race, size, LODDS stage, PLN stage, LNR stage, and TNM stage. A comparison of the four models constructed on the basis of different stages revealed that the model constructed with the LODDS stage had the minimum AIC (Akaike information criterion), maximum C-index (concordance index) and time-dependent AUC. Nomograms based on the LODDS stage were constructed and successfully validated for accuracy and clinical utility. Conclusion For patients with late-onset colon adenocarcinoma, LODDS may achieve optimal predictive performance. Furthermore, compared to the 8th edition of the AJCC classification system, the nomogram based on LODDS stage may demonstrate superior survival prediction capabilities.https://doi.org/10.1007/s12672-025-01849-0LODDSLate-onset colon adenocarcinomaPrognostic modelOverall survivalCause-specific survival |
| spellingShingle | Chen Chen Heng-Bo Xia Wei-Wei Yuan Meng-Ci Zhou Xue Zhang A.-Man Xu Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation Discover Oncology LODDS Late-onset colon adenocarcinoma Prognostic model Overall survival Cause-specific survival |
| title | Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation |
| title_full | Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation |
| title_fullStr | Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation |
| title_full_unstemmed | Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation |
| title_short | Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation |
| title_sort | developing a novel model for predicting overall survival in late onset colon adenocarcinoma patients based on lodds a study based on the seer database and external validation |
| topic | LODDS Late-onset colon adenocarcinoma Prognostic model Overall survival Cause-specific survival |
| url | https://doi.org/10.1007/s12672-025-01849-0 |
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