Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients
Background This study aimed to construct a novel model and validate its predictive power in non-esophageal squamous cell carcinoma (NESCC) patients.Methods This retrospective study included 151 patients between October 2006 and September 2016. The LASSO Cox and Random Survival Forest (RSF) models we...
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Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2025.2483985 |
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| author | Ning Xue Xiaoyan Wen Qian Wang Yong Shen Yuanye Qu Qingxia Xu Shulin Chen Jing Chen |
| author_facet | Ning Xue Xiaoyan Wen Qian Wang Yong Shen Yuanye Qu Qingxia Xu Shulin Chen Jing Chen |
| author_sort | Ning Xue |
| collection | DOAJ |
| description | Background This study aimed to construct a novel model and validate its predictive power in non-esophageal squamous cell carcinoma (NESCC) patients.Methods This retrospective study included 151 patients between October 2006 and September 2016. The LASSO Cox and Random Survival Forest (RSF) models were developed with the help of hematological biomarkers and clinical characteristics. The concordance index (C-index) was used to assess the prognostic power of the LASSO Cox model, RSF model, and TNM staging. Based on the risk scores of the LASSO Cox and RSF models, we divided patients into low-risk and high-risk subgroups.Results We constructed two models in NESCC patients according to LASSO Cox regression and RSF models. The RSF model reached a C-index of 0.841 (95% CI: 0.792–0.889) in the primary cohort and 0.880 (95% CI: 0.830–0.930) in the validation cohort, which was higher than the C-index of the LASSO Cox model 0.656 (95% CI: 0.580–0.732) and 0.632 (95% CI: 0.542–0.720) in the two cohorts. The integrated C/D area under the ROC curve (AUC) values for the LASSO Cox and RSF models were 0.701 and 0.861, respectively. In both two models, Kaplan-Meier survival analysis and the estimated restricted mean survival time (RMST) values indicated that the low-risk subgroup had a better prognostic outcome than the high-risk subgroup (p < 0.05).Conclusions The RSF model has better prediction power than the LASSO Cox and the TNM staging models. It has a guiding value for the choice of individualized treatment in patients with NESCC. |
| format | Article |
| id | doaj-art-0459a9143f8e41c28a3d40c86b3aea3d |
| institution | OA Journals |
| issn | 0785-3890 1365-2060 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj-art-0459a9143f8e41c28a3d40c86b3aea3d2025-08-20T02:09:51ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602025-12-0157110.1080/07853890.2025.2483985Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patientsNing Xue0Xiaoyan Wen1Qian Wang2Yong Shen3Yuanye Qu4Qingxia Xu5Shulin Chen6Jing Chen7Department of Clinical Laboratory, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou Key Laboratory of Digestive System Tumor Marker Diagnosis, Zhengzhou, P. R. ChinaCentral Sterilization Supply Department, The Guanghua Stomatological College of Sun Yat-sen University, Hospital of Stomatology, SunYat-sen University, Guangzhou, P. R. ChinaDepartment of radiation oncology, China–Japan Union Hospital of Jilin University, Changchun, P.R. ChinaDepartment of Clinical Laboratory, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou Key Laboratory of Digestive System Tumor Marker Diagnosis, Zhengzhou, P. R. ChinaDepartment of Clinical Laboratory, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou Key Laboratory of Digestive System Tumor Marker Diagnosis, Zhengzhou, P. R. ChinaDepartment of Clinical Laboratory, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou Key Laboratory of Digestive System Tumor Marker Diagnosis, Zhengzhou, P. R. ChinaState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, ChinaDepartment of Clinical Laboratory, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou Key Laboratory of Digestive System Tumor Marker Diagnosis, Zhengzhou, P. R. ChinaBackground This study aimed to construct a novel model and validate its predictive power in non-esophageal squamous cell carcinoma (NESCC) patients.Methods This retrospective study included 151 patients between October 2006 and September 2016. The LASSO Cox and Random Survival Forest (RSF) models were developed with the help of hematological biomarkers and clinical characteristics. The concordance index (C-index) was used to assess the prognostic power of the LASSO Cox model, RSF model, and TNM staging. Based on the risk scores of the LASSO Cox and RSF models, we divided patients into low-risk and high-risk subgroups.Results We constructed two models in NESCC patients according to LASSO Cox regression and RSF models. The RSF model reached a C-index of 0.841 (95% CI: 0.792–0.889) in the primary cohort and 0.880 (95% CI: 0.830–0.930) in the validation cohort, which was higher than the C-index of the LASSO Cox model 0.656 (95% CI: 0.580–0.732) and 0.632 (95% CI: 0.542–0.720) in the two cohorts. The integrated C/D area under the ROC curve (AUC) values for the LASSO Cox and RSF models were 0.701 and 0.861, respectively. In both two models, Kaplan-Meier survival analysis and the estimated restricted mean survival time (RMST) values indicated that the low-risk subgroup had a better prognostic outcome than the high-risk subgroup (p < 0.05).Conclusions The RSF model has better prediction power than the LASSO Cox and the TNM staging models. It has a guiding value for the choice of individualized treatment in patients with NESCC.https://www.tandfonline.com/doi/10.1080/07853890.2025.2483985LASSO Cox modelnon-esophageal squamous cell carcinomaprognostic modelRSF model |
| spellingShingle | Ning Xue Xiaoyan Wen Qian Wang Yong Shen Yuanye Qu Qingxia Xu Shulin Chen Jing Chen Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients Annals of Medicine LASSO Cox model non-esophageal squamous cell carcinoma prognostic model RSF model |
| title | Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients |
| title_full | Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients |
| title_fullStr | Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients |
| title_full_unstemmed | Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients |
| title_short | Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients |
| title_sort | establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non esophageal squamous cell carcinoma patients |
| topic | LASSO Cox model non-esophageal squamous cell carcinoma prognostic model RSF model |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2025.2483985 |
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