Construction and validation of a nomogram based on the log odds of positive lymph nodes to predict the prognosis of T1 gastric cancer
Year: 2025
Type: article
Study design: Observational Study
Abstract: In patients with gastric cancer (GC), metastatic progression through the lymphatic, haematogenous, peritoneal, and ovarian routes is the ultimate cause of death. We developed a nomogram to estimate cancer-specific survival (CSS) in patients with T1 gastric cancer based on log odds of positive lymph nodes (LODDS). A total of 2,221 patients from the Surveillance, Epidemiology, and End Results (SEER) database were split into training and internal validation cohorts, while an external validation cohort included 165 patients from our hospital. Multivariate Cox regression analysis revealed that age, sex, tumour size, LODDS score, and M stage were independent prognostic factors for CSS. The LODDS outperformed the N stage and positive lymph node (PLN) count in terms of predictive ability and is recognised as an independent prognostic factor for nomogram construction. In the training and internal and external validation sets, the 1-year AUCs of the columniogram were 0.732, 0.672, and 0.719, respectively. The 3-year AUCs were 0.705, 0.692, and 0.638, respectively. The 5-year AUCs were 0.726, 0.698, and 0.713, respectively, indicating good predictive power. The calibration curve revealed that the predicted survival rate was consistent with the actual survival rate in the three groups. The ROC and DCA demonstrated that the nomogram has more potential in predicting prognosis than the existing AJCC staging system. We constructed and validated a novel nomogram leveraging LODDS, which effectively estimates the CSS at 1, 3, and 5 years for individuals with gastric cancer.
Source: Scientific Reports
Authors: Xiaqin Chen, Zhijie He, Caiqing Zhao, Kaini Wu, Qi Zhu, Yunfeng Fu, Yating Pan, Yuanping Fan, Sicheng Yang, Yonghua Zeng, Shicheng Luo, Lihua Liu, Fan Du, Xiaodong Zhou
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4408216078
