Trial reportCancer medicine2023
Establishment and validation of a prognostic nomogram for postoperative patients with gastric cardia adenocarcinoma: A study based on the Surveillance, Epidemiology, and End Results database and a Chinese cohort.
Trial report in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Trial
- Conversion to laparotomy due to intra-abdominal adhesions during laparoscopic hernia repair: a predictive model based on computed tomography manifestations and clinical indicators.Quantitative imaging in medicine and surgery · 2026Article
- Survival Prediction in Stomach Cancer with Deep Learning: Unveiling Model Decisions with LIME and SHAP.Asian Pacific journal of cancer prevention : APJCP · 2025Article
- Construction and validation of a novel nomogram based on the log odds of positive lymph nodes to predict cancer-specific survival in elderly patients with gastric adenocarcinoma after radical surgery.BMC gastroenterology · 2025Article
- Article
- Deep learning model for predicting postoperative survival of patients with gastric cancer.Frontiers in oncology · 2024Article
- Construction of a novel nomogram for predicting overall survival in patients with Siewert type II AEG based on LODDS: a study based on the seer database and external validation.Frontiers in oncology · 2024Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric cardia adenocarcinoma (GCA) is a highly fatal form of cancer in humans. The aim of this study was to extract clinicopathological data of postoperative patients with GCA from the Surveillance, Epidemiology, and End Results database, analyze prognostic risk factors, and build a nomogram.
methodsIn this study, the clinical information of 1448 patients with GCA who underwent radical surgery and were diagnosed between 2010 and 2015 was extracted from the SEER database. The patients were then randomly divided into training (n = 1013) and internal validation (n = 435) cohorts at a 7:3 ratio. The study also included an external validation cohort (n = 218) from a Chinese hospital. The study used the Cox and LASSO models to pinpoint the independent risk factors linked to GCA. The prognostic model was constructed according to the results of the multivariate regression analysis. To assess the predictive accuracy of the nomogram, four methods were used: C-index, calibration curve, time-dependent ROC curve, and DCA curve. Kaplan-Meier survival curves were also generated to illustrate the differences in cancer-specific survival (CSS) between the groups.
resultsThe results of the multivariate Cox regression analysis showed that age, grade, race, marital status, T stage, and log odds of positive lymph nodes (LODDS) were independently associated with cancer-specific survival in the training cohort. Both the C-index and AUC values depicted in the nomogram were greater than 0.71. The calibration curve revealed that the nomogram's CSS prediction was consistent with the actual outcomes. The decision curve analysis suggested moderately positive net benefits. Based on the nomogram risk score, significant differences in survival between the high- and low-risk groups were observed.
conclusionsRace, age, marital status, differentiation grade, T stage, and LODDS are independent predictors of CSS in patients with GCA after radical surgery. Our predictive nomogram constructed based on these variables demonstrated good predictive ability.
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