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Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database

BACKGROUND: To determine the populations who suitable for surgical treatment in elderly patients (age ≥ 75 y) with IA stage. METHODS: The clinical data of NSCLC patients diagnosed from 2010 to 2015 were collected from the SEER database and divided into surgery group (SG) and no-surgery groups (NSG)....

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Autores principales: Zhang, Wenting, Liu, Yafeng, Wu, Jing, Wang, Wenyang, Zhou, Jiawei, Guo, Jianqiang, Wang, Qingsen, Zhang, Xin, Xie, Jun, Xing, Yingru, Hu, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720806/
https://www.ncbi.nlm.nih.gov/pubmed/36450593
http://dx.doi.org/10.1177/10732748221142750
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author Zhang, Wenting
Liu, Yafeng
Wu, Jing
Wang, Wenyang
Zhou, Jiawei
Guo, Jianqiang
Wang, Qingsen
Zhang, Xin
Xie, Jun
Xing, Yingru
Hu, Dong
author_facet Zhang, Wenting
Liu, Yafeng
Wu, Jing
Wang, Wenyang
Zhou, Jiawei
Guo, Jianqiang
Wang, Qingsen
Zhang, Xin
Xie, Jun
Xing, Yingru
Hu, Dong
author_sort Zhang, Wenting
collection PubMed
description BACKGROUND: To determine the populations who suitable for surgical treatment in elderly patients (age ≥ 75 y) with IA stage. METHODS: The clinical data of NSCLC patients diagnosed from 2010 to 2015 were collected from the SEER database and divided into surgery group (SG) and no-surgery groups (NSG). The confounders were balanced and differences in survival were compared between groups using PSM (Propensity score matching, PSM). Cox regression analysis was used to screen the independent factors that affect the Cancer-specific survival (CSS). The surgery group was defined as the patients who surgery-benefit and surgery-no benefit according to the median CSS of the no-surgery group, and then randomly divided into training and validation groups. A surgical benefit prediction model was constructed in the training and validation group. Finally, the model is evaluated using a variety of methods. RESULTS: A total of 7297 patients were included. Before PSM (SG: n = 3630; NSG: n = 3665) and after PSM (SG: n = 1725, NSG: n = 1725) confirmed that the CSS of the surgery group was longer than the no-surgery group (before PSM: 82 vs. 31 months, P < .0001; after PSM: 55 vs. 39 months, P < .0001). Independent prognostic factors included age, gender, race, marrital, tumor grade, histology, and surgery. In the surgery cohort after PSM, 1005 patients (58.27%) who survived for more than 39 months were defined as surgery beneficiaries, and the 720 patients (41.73%) were defined surgery-no beneficiaries. The surgery group was divided into training group 1207 (70%) and validation group 518 (30%). Independent prognostic factors were used to construct a prediction model. In training group (AUC = .678) and validation group (AUC = .622). Calibration curve and decision curve prove that the model has better performance. CONCLUSIONS: This predictive model can well identify elderly patients with stage IA NSCLC who would benefit from surgery, thus providing a basis for clinical treatment decisions.
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spelling pubmed-97208062022-12-06 Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database Zhang, Wenting Liu, Yafeng Wu, Jing Wang, Wenyang Zhou, Jiawei Guo, Jianqiang Wang, Qingsen Zhang, Xin Xie, Jun Xing, Yingru Hu, Dong Cancer Control How frail are surgical patients? The era of “Geriatric” or “Frailty” Surgical Oncology as a proof of concept-Original Article BACKGROUND: To determine the populations who suitable for surgical treatment in elderly patients (age ≥ 75 y) with IA stage. METHODS: The clinical data of NSCLC patients diagnosed from 2010 to 2015 were collected from the SEER database and divided into surgery group (SG) and no-surgery groups (NSG). The confounders were balanced and differences in survival were compared between groups using PSM (Propensity score matching, PSM). Cox regression analysis was used to screen the independent factors that affect the Cancer-specific survival (CSS). The surgery group was defined as the patients who surgery-benefit and surgery-no benefit according to the median CSS of the no-surgery group, and then randomly divided into training and validation groups. A surgical benefit prediction model was constructed in the training and validation group. Finally, the model is evaluated using a variety of methods. RESULTS: A total of 7297 patients were included. Before PSM (SG: n = 3630; NSG: n = 3665) and after PSM (SG: n = 1725, NSG: n = 1725) confirmed that the CSS of the surgery group was longer than the no-surgery group (before PSM: 82 vs. 31 months, P < .0001; after PSM: 55 vs. 39 months, P < .0001). Independent prognostic factors included age, gender, race, marrital, tumor grade, histology, and surgery. In the surgery cohort after PSM, 1005 patients (58.27%) who survived for more than 39 months were defined as surgery beneficiaries, and the 720 patients (41.73%) were defined surgery-no beneficiaries. The surgery group was divided into training group 1207 (70%) and validation group 518 (30%). Independent prognostic factors were used to construct a prediction model. In training group (AUC = .678) and validation group (AUC = .622). Calibration curve and decision curve prove that the model has better performance. CONCLUSIONS: This predictive model can well identify elderly patients with stage IA NSCLC who would benefit from surgery, thus providing a basis for clinical treatment decisions. SAGE Publications 2022-11-30 /pmc/articles/PMC9720806/ /pubmed/36450593 http://dx.doi.org/10.1177/10732748221142750 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle How frail are surgical patients? The era of “Geriatric” or “Frailty” Surgical Oncology as a proof of concept-Original Article
Zhang, Wenting
Liu, Yafeng
Wu, Jing
Wang, Wenyang
Zhou, Jiawei
Guo, Jianqiang
Wang, Qingsen
Zhang, Xin
Xie, Jun
Xing, Yingru
Hu, Dong
Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database
title Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database
title_full Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database
title_fullStr Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database
title_full_unstemmed Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database
title_short Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database
title_sort surgical treatment is still recommended for patients over 75 years with ia nsclc: a predictive model based on surveillance, epidemiology and end results database
topic How frail are surgical patients? The era of “Geriatric” or “Frailty” Surgical Oncology as a proof of concept-Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720806/
https://www.ncbi.nlm.nih.gov/pubmed/36450593
http://dx.doi.org/10.1177/10732748221142750
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