Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma
Abstract Objective This study aims to compare and analyze the effectiveness of different tumor regression grade (TRG) assessment systems in evaluating neoadjuvant therapy for esophageal cancer, with the goal of identifying an optimal assessment method to guide clinical practice. Methods A total of 4...
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2025-08-01
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| Online Access: | https://doi.org/10.1186/s12885-025-14726-4 |
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| author | Qiao Yang Xiaoqing Zhou Jiayu Li Jieyu Wang Jingcheng Luo Dan Luo Lin Shi Chengmin Zhou Yi Wang Xuefeng Leng Qifeng Wang Yang Liu Yehan Zhou |
| author_facet | Qiao Yang Xiaoqing Zhou Jiayu Li Jieyu Wang Jingcheng Luo Dan Luo Lin Shi Chengmin Zhou Yi Wang Xuefeng Leng Qifeng Wang Yang Liu Yehan Zhou |
| author_sort | Qiao Yang |
| collection | DOAJ |
| description | Abstract Objective This study aims to compare and analyze the effectiveness of different tumor regression grade (TRG) assessment systems in evaluating neoadjuvant therapy for esophageal cancer, with the goal of identifying an optimal assessment method to guide clinical practice. Methods A total of 467 patients with esophageal squamous cell carcinoma who underwent neoadjuvant therapy followed by surgical resection were included in this study. We comprehensively evaluated the effectiveness of five TRG assessment systems—Mandard, CAP, Becker, JSED, and Ryan—in predicting the prognosis of the primary tumor (PT) and lymph nodes (LN). The inter-observer consistency among these systems was also assessed to identify the most effective TRG evaluation method. Results The performance of the TRG assessment systems in predicting LN prognosis was generally superior to that for PT. Specifically, while the Ryan criteria demonstrated the highest inter-observer consistency coefficient (Mean Kappa = 0.848), its predictive efficacy was the lowest (Mean AUC = 0.502). In contrast, the Becker criteria exhibited the highest predictive efficacy (Mean AUC = 0.609) alongside a good consistency coefficient (Mean Kappa = 0.788). Notably, the modified Modified TRG system not only achieved a higher AUC value (0.624) but also showed excellent inter-observer consistency (Kappa = 0.904). Conclusion The modified Modified TRG system, with a focus on LN evaluation, demonstrates superior prognostic predictive ability and risk stratification effectiveness. These findings may assist clinicians in more accurately assessing patient prognosis and adjusting treatment strategies accordingly, ultimately optimizing patient treatment pathways. |
| format | Article |
| id | doaj-art-1ecd706e09b5467dbc3c9f9bfaec53e3 |
| institution | Kabale University |
| issn | 1471-2407 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj-art-1ecd706e09b5467dbc3c9f9bfaec53e32025-08-24T11:34:32ZengBMCBMC Cancer1471-24072025-08-0125111010.1186/s12885-025-14726-4Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinomaQiao Yang0Xiaoqing Zhou1Jiayu Li2Jieyu Wang3Jingcheng Luo4Dan Luo5Lin Shi6Chengmin Zhou7Yi Wang8Xuefeng Leng9Qifeng Wang10Yang Liu11Yehan Zhou12Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaDepartment of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of ChinaAbstract Objective This study aims to compare and analyze the effectiveness of different tumor regression grade (TRG) assessment systems in evaluating neoadjuvant therapy for esophageal cancer, with the goal of identifying an optimal assessment method to guide clinical practice. Methods A total of 467 patients with esophageal squamous cell carcinoma who underwent neoadjuvant therapy followed by surgical resection were included in this study. We comprehensively evaluated the effectiveness of five TRG assessment systems—Mandard, CAP, Becker, JSED, and Ryan—in predicting the prognosis of the primary tumor (PT) and lymph nodes (LN). The inter-observer consistency among these systems was also assessed to identify the most effective TRG evaluation method. Results The performance of the TRG assessment systems in predicting LN prognosis was generally superior to that for PT. Specifically, while the Ryan criteria demonstrated the highest inter-observer consistency coefficient (Mean Kappa = 0.848), its predictive efficacy was the lowest (Mean AUC = 0.502). In contrast, the Becker criteria exhibited the highest predictive efficacy (Mean AUC = 0.609) alongside a good consistency coefficient (Mean Kappa = 0.788). Notably, the modified Modified TRG system not only achieved a higher AUC value (0.624) but also showed excellent inter-observer consistency (Kappa = 0.904). Conclusion The modified Modified TRG system, with a focus on LN evaluation, demonstrates superior prognostic predictive ability and risk stratification effectiveness. These findings may assist clinicians in more accurately assessing patient prognosis and adjusting treatment strategies accordingly, ultimately optimizing patient treatment pathways.https://doi.org/10.1186/s12885-025-14726-4Tumor regression gradeEsophageal cancerPrognosisLymph nodes |
| spellingShingle | Qiao Yang Xiaoqing Zhou Jiayu Li Jieyu Wang Jingcheng Luo Dan Luo Lin Shi Chengmin Zhou Yi Wang Xuefeng Leng Qifeng Wang Yang Liu Yehan Zhou Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma BMC Cancer Tumor regression grade Esophageal cancer Prognosis Lymph nodes |
| title | Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma |
| title_full | Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma |
| title_fullStr | Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma |
| title_full_unstemmed | Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma |
| title_short | Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma |
| title_sort | comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma |
| topic | Tumor regression grade Esophageal cancer Prognosis Lymph nodes |
| url | https://doi.org/10.1186/s12885-025-14726-4 |
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