Dynamic Nomogram for Predicting Long-Term Survival in Terms of Preoperative and Postoperative Radiotherapy Benefits for Advanced Gastric Cancer

Xinghui Li, Yang Yu, Cheng Zheng, Yue Zhang, Chuandao Shi, Lei Zhang () and Hui Qiao ()
Additional contact information
Xinghui Li: Cancer Institute of the General Hospital, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China
Yang Yu: Department of Neurosurgery, Huazhong University of Science and Technology Union Shenzhen Hospital, The 6th Affiliated Hospital of Shenzhen University, Shenzhen 518052, China
Cheng Zheng: Cancer Institute of the General Hospital, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China
Yue Zhang: Cancer Institute of the General Hospital, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China
Chuandao Shi: Department of Epidemiology and Biostatistics, College of Public Health, Shaanxi University of Chinese Medicine, Xi’an 712046, China
Lei Zhang: China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
Hui Qiao: Cancer Institute of the General Hospital, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China

IJERPH, 2023, vol. 20, issue 3, 1-12

Abstract: Studies on the prognostic significance of preoperative radiotherapy (PERT) and postoperative radiotherapy (PORT) in patients with advanced gastric cancer (GC) remain elusive. The aim of the study was to evaluate the survival advantage of preoperative and postoperative radiotherapy and construct a dynamic nomogram model to provide customized prediction of the probability of prognostic events for advanced GC patients. We collected clinical records from 2010 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database with a specific target for stage II-IV GC patients treated with PERT or PORT. We used the least absolute shrinkage and selection operator (LASSO) regression model to identify factors that contribute to the overall survival (OS) of GC patients. The dynamic nomogram infographic was constructed based on the prognostic factors of tumor-specific survival. Out of the 3215 total patients (2271 [70.6%] male; median age, 61 [SD = 12] years), 1204 were in the PERT group and 2011 in the PORT group. Receiving PORT was associated with a survival advantage over PERT for stage II GC patients (HR = 0.791, 95% CI= 0.712–0.879, p < 0.001). The 1-, 3-, and 5-year OS rates were 89.9%, 63.8%, and 53.8% in the PORT group, whereas the corresponding rates were significantly lower in the PERT group (86.4%, 57.1%, and 44.3%, respectively, all p < 0.05). The survival prediction model demonstrated that patients aged > 65 years, with an advanced cancer development stage and tumor size >3 were independent risk factors for poor prognosis (all HR > 1, p < 0.05). In this study, a dynamic nomogram was established based on the LASSO model to provide a statistical basis for the clinical characteristics and predictive factors of advanced GC in a large population. PORT demonstrated significantly better treatment advantages than PERT for stage II GC patients.

Keywords: advance gastric cancer; preoperative radiotherapy; postoperative radiotherapy; dynamic nomogram; LASSO; prognosis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/20/3/2747/pdf (application/pdf)
https://www.mdpi.com/1660-4601/20/3/2747/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:20:y:2023:i:3:p:2747-:d:1057072

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().