ArticleBMJ open2022
Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Predictors of one-year adverse outcomes after laparoscopic resection for hepatocellular carcinoma: Development and validation of an early-warning model.World journal of gastroenterology · 2026Article
- Effect of stratified management and stepwise training on pulmonary rehabilitation in older patients with liver cancer.World journal of gastrointestinal surgery · 2025Article
- Analysis of influencing factors of concurrent primary liver cancer in hepatitis B patients and construction of column chart prediction model.Epidemiology and infection · 2025Article
- Investigation of Risk Factors and Development and Validation of a Nomogram for Predicting Overall Survival in Breast-Invasive Lobular Carcinoma.Breast care (Basel, Switzerland) · 2025Article
- Development and evaluation of a nomogram prediction model for invasion and metastasis in primary liver cancer based on serum CD147 and IL-6.Frontiers in oncology · 2025Article
- Prognostic Index for Liver Radiation (PILiR).Current oncology (Toronto, Ont.) · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the risk factors and construct a nomogram model for the prognosis of primary liver cancer in the elderly based on the data from the US SEER database.
methodsThe latest data of patients with primary liver cancer were extracted from the SEER database using SEER*STAT software, and the required variables were included. The data were screened and then divided into a training cohort and a validation cohort. A nomogram model was constructed by screening the variables through univariate and multivariate Cox analysis. The C-Index, ROC and calibration curves were used for model evaluation.
resultsA total of 10 824 eligible cases from 2004 to 2017 were extracted, among which, 7757 cases were included in the training cohort and 3247 in the validation cohort. The C-Index of the model was 0.747 (in the training cohort) and 0.773 (in the validation cohort). The 3-year area under the curve (AUCs) of the training and the validation cohorts were 0.760 and 0.750, and the 5-year AUCs of the two cohorts were 0.761 and 0.748. The calibration curves showed an ideal calibration of the constructed model.
conclusionsThe nomogram model constructed followed by Cox regression analysis showed moderate calibration and discrimination property, and can provide reference to a certain extent for furture clinical application of primary liver cancer in the elderly.
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