Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator
BackgroundConditional survival (CS) analysis can estimate further survival probabilities based on the time already survived, providing dynamic updates for prognostic information. This study aimed to develop a CS-nomogram to promote individualized disease management for stage III non-small cell lung...
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| Format: | Article |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2024.1491337/full |
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| author | Xiangdi Meng Xiangdi Meng Peihe Wang Jie Liu Daqing Sun Zhuojun Ju Yuanyuan Cai |
| author_facet | Xiangdi Meng Xiangdi Meng Peihe Wang Jie Liu Daqing Sun Zhuojun Ju Yuanyuan Cai |
| author_sort | Xiangdi Meng |
| collection | DOAJ |
| description | BackgroundConditional survival (CS) analysis can estimate further survival probabilities based on the time already survived, providing dynamic updates for prognostic information. This study aimed to develop a CS-nomogram to promote individualized disease management for stage III non-small cell lung cancer (NSCLC).MethodsThis study included patients diagnosed with stage III NSCLC in the Surveillance, Epidemiology, and End Results database from 2010 to 2017 (N = 3,512). The CS was calculated as CS(y|x) = OS(y + x)/OS(x), where OS(y + x) and OS(x) were the overall survival (OS) in the year (y + x) and year x, respectively, calculated by the Kaplan–Meier method. We used the least absolute shrinkage and selection operator (LASSO) regression to identify predictors and developed the CS-nomogram based on these predictors and the CS formula.ResultsThe CS analysis provided real-time updates on survival, with 5-year OS improving dynamically from 14.4 to 29.9%, 47.9, 66.0, and 80.8% (after 1–4 years of survival). Six independent predictors (age, tumor size, N status, surgery, radiotherapy and chemotherapy) were identified for the development of the CS-nomogram and its web version (https://dynapp.shinyapps.io/NSCLC/). The model performed with an excellent concordance index (C-index) of 0.71 (95% CI: 0.70–0.72), and a median time-dependent AUC of 0.71–0.73 from 200 iterations 5-fold cross-validation.ConclusionThe study demonstrated the improvement in real-time OS over time in stage III NSCLC survivors and developed the novel CS-nomogram to provide patients with updated survival data. It provided novel insights into clinical decisions in follow-up and treatment for survivors, offering a convenient tool for optimize resource allocation. |
| format | Article |
| id | doaj-art-fc4b8fea330d4acf9fcd5241110eb7b4 |
| institution | Kabale University |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Medicine |
| spelling | doaj-art-fc4b8fea330d4acf9fcd5241110eb7b42025-01-07T05:24:04ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-01-011110.3389/fmed.2024.14913371491337Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculatorXiangdi Meng0Xiangdi Meng1Peihe Wang2Jie Liu3Daqing Sun4Zhuojun Ju5Yuanyuan Cai6Department of Radiation Oncology, Weifang People’s Hospital, Weifang, ChinaDepartment of Radiation Oncology, Gunma University Graduate School of Medicine, Maebashi, JapanDepartment of Radiation Oncology, Weifang People’s Hospital, Weifang, ChinaDepartment of Radiation Oncology, Weifang People’s Hospital, Weifang, ChinaDepartment of Radiation Oncology, Weifang People’s Hospital, Weifang, ChinaDepartment of Radiation Oncology, Gunma University Graduate School of Medicine, Maebashi, JapanDepartment of Radiation Oncology, Weifang People’s Hospital, Weifang, ChinaBackgroundConditional survival (CS) analysis can estimate further survival probabilities based on the time already survived, providing dynamic updates for prognostic information. This study aimed to develop a CS-nomogram to promote individualized disease management for stage III non-small cell lung cancer (NSCLC).MethodsThis study included patients diagnosed with stage III NSCLC in the Surveillance, Epidemiology, and End Results database from 2010 to 2017 (N = 3,512). The CS was calculated as CS(y|x) = OS(y + x)/OS(x), where OS(y + x) and OS(x) were the overall survival (OS) in the year (y + x) and year x, respectively, calculated by the Kaplan–Meier method. We used the least absolute shrinkage and selection operator (LASSO) regression to identify predictors and developed the CS-nomogram based on these predictors and the CS formula.ResultsThe CS analysis provided real-time updates on survival, with 5-year OS improving dynamically from 14.4 to 29.9%, 47.9, 66.0, and 80.8% (after 1–4 years of survival). Six independent predictors (age, tumor size, N status, surgery, radiotherapy and chemotherapy) were identified for the development of the CS-nomogram and its web version (https://dynapp.shinyapps.io/NSCLC/). The model performed with an excellent concordance index (C-index) of 0.71 (95% CI: 0.70–0.72), and a median time-dependent AUC of 0.71–0.73 from 200 iterations 5-fold cross-validation.ConclusionThe study demonstrated the improvement in real-time OS over time in stage III NSCLC survivors and developed the novel CS-nomogram to provide patients with updated survival data. It provided novel insights into clinical decisions in follow-up and treatment for survivors, offering a convenient tool for optimize resource allocation.https://www.frontiersin.org/articles/10.3389/fmed.2024.1491337/fullconditional survivalnon-small cell lung cancernomogramoverall survivalprognostic factor |
| spellingShingle | Xiangdi Meng Xiangdi Meng Peihe Wang Jie Liu Daqing Sun Zhuojun Ju Yuanyuan Cai Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator Frontiers in Medicine conditional survival non-small cell lung cancer nomogram overall survival prognostic factor |
| title | Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator |
| title_full | Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator |
| title_fullStr | Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator |
| title_full_unstemmed | Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator |
| title_short | Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator |
| title_sort | dynamic assessment of long term survival in survivors with stage iii non small cell lung cancer a novel conditional survival model with a web based calculator |
| topic | conditional survival non-small cell lung cancer nomogram overall survival prognostic factor |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2024.1491337/full |
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