Trial reportScientific reports2023
Nomogram for predicting the likelihood of liver metastases at initial diagnosis in patients with Siewert type II gastroesophageal junction adenocarcinoma.
Trial report in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The liver is one of the most ordinary metastatic sites of gastroesophageal junction adenocarcinoma and significantly affects its prognosis. Therefore, this study tried to construct a nomogram that can be applied to predict the likelihood of liver metastases from gastroesophageal junction adenocarcinoma. 3001 eligible patients diagnosed with gastroesophageal junction adenocarcinoma between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were involved in the analysis. Patients were randomly divided into a training cohort and an internal validation cohort using R software, with an allocation ratio of 7:3. According to the consequences of univariate and multivariate logistic regression, we constructed a nomogram for predicting the risk of liver metastases. The discrimination and calibration ability of the nomogram was appraised by the C-index, ROC curve, calibration plots, and decision curve analysis (DCA). We also used Kaplan-Meier survival curves to compare differences in overall survival in patients with gastroesophageal junction adenocarcinoma with and without liver metastases. Liver metastases developed in 281 of 3001 eligible patients. The overall survival of patients with gastroesophageal junction adenocarcinoma with liver metastases before and after propensity score matching (PSM) was obviously lower than that of patients without liver metastases. Six risk factors were finally recognized by multivariate logistic regression, and a nomogram was constructed. The C-index was 0.816 in the training cohort and 0.771 in the validation cohort, demonstrating the good predictive capacity of the nomogram. The ROC curve, calibration curve, and decision curve analysis further demonstrated the good performance of the predictive model. The nomogram can accurately predict the likelihood of liver metastases in gastroesophageal junction adenocarcinoma patients.
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