Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression
Abstract Objective This study aimed to establish novel nomograms that could be used to predict the prognosis of gastric carcinoma patients who underwent D2 + total gastrectomy on overall survival (OS) and progression-free survival (PFS). Methods Lasso regression was employed to construct the nomogra...
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| Format: | Article |
| Language: | English |
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BMC
2023-07-01
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| Series: | World Journal of Surgical Oncology |
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| Online Access: | https://doi.org/10.1186/s12957-023-03097-4 |
| _version_ | 1797774190585053184 |
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| author | Yifan Li Min Bai Yuye Gao |
| author_facet | Yifan Li Min Bai Yuye Gao |
| author_sort | Yifan Li |
| collection | DOAJ |
| description | Abstract Objective This study aimed to establish novel nomograms that could be used to predict the prognosis of gastric carcinoma patients who underwent D2 + total gastrectomy on overall survival (OS) and progression-free survival (PFS). Methods Lasso regression was employed to construct the nomograms. The internal validation process included bootstrapping, which was used to test the accuracy of the predictions. The calibration curve was then used to demonstrate the accuracy and consistency of the predictions. In addition, the Harrell’s Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate the discriminative abilities of the new nomograms and to compare its performance with the 8th edition of AJCC-TNM staging. Furthermore, decision curve analysis (DCA) was performed to assess the clinical application of our model. Finally, the prognostic risk stratification of gastric cancer was conducted with X-tile software, and the nomograms were converted into a risk-stratifying prognosis model. Results LASSO regression analysis identified pT stage, the number of positive lymph nodes, vascular invasion, neural invasion, the maximum diameter of tumor, the Clavien–Dindo classification for complication, and Ki67 as independent risk factors for OS and pT stage, the number of positive lymph nodes, neural invasion, and the maximum diameter of tumor for PFS. The C-index of OS nomogram was 0.719 (95% CI: 0.690–0.748), which was superior to the 8th edition of AJCC-TNM staging (0.704, 95%CI: 0.623–0.783). The C-index of PFS nomogram was 0.694 (95% CI: 0.654–0.713), which was also better than that of the 8th edition of AJCC-TNM staging (0.685, 95% CI: 0.635–0.751). The calibration curves, t-ROC curves, and DCA of the two nomogram models showed that the prediction ability of the two nomogram models was outstanding. The statistical difference in the prognosis between the low- and high-risk groups further suggested that our model had an excellent risk stratification performance. Conclusion We reported the first risk stratification and nomogram for gastric carcinoma patients with total gastrectomy in Chinese population. Our model could potentially be used to guide treatment selections for the low- and high-risk patients to avoid delayed treatment or unnecessary overtreatment. |
| first_indexed | 2024-03-12T22:17:24Z |
| format | Article |
| id | doaj.art-f611ced38ccb40b0a05a326c6740d82e |
| institution | Directory Open Access Journal |
| issn | 1477-7819 |
| language | English |
| last_indexed | 2024-03-12T22:17:24Z |
| publishDate | 2023-07-01 |
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| series | World Journal of Surgical Oncology |
| spelling | doaj.art-f611ced38ccb40b0a05a326c6740d82e2023-07-23T11:16:17ZengBMCWorld Journal of Surgical Oncology1477-78192023-07-0121112710.1186/s12957-023-03097-4Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regressionYifan Li0Min Bai1Yuye Gao2Second Department of General Surgery, Shanxi Province Carcinoma Hospital, Shanxi Hospital Affiliated to Carcinoma Hospital, Chinese Academy of Medical Sciences, Carcinoma Hospital Affiliated to Shanxi Medical UniversityDepartment of Hematopathology, Shanxi Province Carcinoma Hospital, Shanxi Hospital Affiliated to Carcinoma Hospital, Chinese Academy of Medical Sciences, Carcinoma Hospital Affiliated to Shanxi Medical UniversityDepartment of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteAbstract Objective This study aimed to establish novel nomograms that could be used to predict the prognosis of gastric carcinoma patients who underwent D2 + total gastrectomy on overall survival (OS) and progression-free survival (PFS). Methods Lasso regression was employed to construct the nomograms. The internal validation process included bootstrapping, which was used to test the accuracy of the predictions. The calibration curve was then used to demonstrate the accuracy and consistency of the predictions. In addition, the Harrell’s Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate the discriminative abilities of the new nomograms and to compare its performance with the 8th edition of AJCC-TNM staging. Furthermore, decision curve analysis (DCA) was performed to assess the clinical application of our model. Finally, the prognostic risk stratification of gastric cancer was conducted with X-tile software, and the nomograms were converted into a risk-stratifying prognosis model. Results LASSO regression analysis identified pT stage, the number of positive lymph nodes, vascular invasion, neural invasion, the maximum diameter of tumor, the Clavien–Dindo classification for complication, and Ki67 as independent risk factors for OS and pT stage, the number of positive lymph nodes, neural invasion, and the maximum diameter of tumor for PFS. The C-index of OS nomogram was 0.719 (95% CI: 0.690–0.748), which was superior to the 8th edition of AJCC-TNM staging (0.704, 95%CI: 0.623–0.783). The C-index of PFS nomogram was 0.694 (95% CI: 0.654–0.713), which was also better than that of the 8th edition of AJCC-TNM staging (0.685, 95% CI: 0.635–0.751). The calibration curves, t-ROC curves, and DCA of the two nomogram models showed that the prediction ability of the two nomogram models was outstanding. The statistical difference in the prognosis between the low- and high-risk groups further suggested that our model had an excellent risk stratification performance. Conclusion We reported the first risk stratification and nomogram for gastric carcinoma patients with total gastrectomy in Chinese population. Our model could potentially be used to guide treatment selections for the low- and high-risk patients to avoid delayed treatment or unnecessary overtreatment.https://doi.org/10.1186/s12957-023-03097-4Gastric carcinomaTotal gastrectomyOverall survivalProgress-free survival |
| spellingShingle | Yifan Li Min Bai Yuye Gao Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression World Journal of Surgical Oncology Gastric carcinoma Total gastrectomy Overall survival Progress-free survival |
| title | Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression |
| title_full | Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression |
| title_fullStr | Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression |
| title_full_unstemmed | Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression |
| title_short | Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression |
| title_sort | prognostic nomograms for gastric carcinoma after d2 total gastrectomy to assist decision making for postoperative treatment based on lasso regression |
| topic | Gastric carcinoma Total gastrectomy Overall survival Progress-free survival |
| url | https://doi.org/10.1186/s12957-023-03097-4 |
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