ArticleBMC cancer2020
A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Development and verification of risk prediction nomograms for overall and specific mortality in primary small bowel cancer: a population-based study.Translational cancer research · 2025Article
- Prognostic nomogram for overall survival in rectal cancer with synchronous lung metastases using Surveillance, Epidemiology, and End Results data and a single-center external validation cohort.Journal of gastrointestinal oncology · 2025Article
- Development and validation of a nomogram for predicting cancer-specific survival in small-bowel adenocarcinoma patients using the SEER database.World journal of surgical oncology · 2024Article
- Prediction of distant metastasis and specific survival prediction of small intestine cancer patients with metastasis: A population-based study.Cancer medicine · 2023Article
- Clinicopathological characteristics and prognostic factors of elderly small intestine adenocarcinoma using propensity score matching analysis: a study based on SEER database.International journal of colorectal disease · 2022Article
- Development of a Deep Learning Model for Malignant Small Bowel Tumors Survival: A SEER-Based Study.Diagnostics (Basel, Switzerland) · 2022Article
- Development and validation of prognostic nomograms for patients with metastatic small bowel adenocarcinoma: a retrospective cohort study.Scientific reports · 2022Article
- Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery.Frontiers in oncology · 2022Article
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9 authors.
Funding
Abstract
backgroundThe objective of this study was to develop a practical nomogram for predicting the cancer-specific survival (CSS) of patients with small-intestine adenocarcinoma.
methodsPatients diagnosed with small-intestine adenocarcinoma between 2010 and 2015 were selected for inclusion in this study from the Surveillance, Epidemiology, and End Results (SEER) database. The selected patients were randomly divided into the training and validation cohorts at a ratio of 7:3. The predictors of CSS were identified by applying both forward and backward stepwise selection methods in a Cox regression model. The performance of the nomogram was measured by the concordance index (C-index), the area under receiver operating characteristic curve (AUC), calibration plots, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and decision-curve analysis (DCA).
resultsMultivariate Cox regression indicated that factors including age at diagnosis, sex, marital status, insurance status, histology grade, SEER stage, surgery status, T stage, and N stage were independent covariates associated with CSS. These factors were used to construct a predictive model, which was built and virtualized by a nomogram. The C-index of the constructed nomogram was 0.850. The AUC values indicated that the established nomogram displayed better discrimination performance than did the seventh edition of the American Joint Committee on Cancer TNM staging system in predicting CSS. The IDI and NRI also showed that the nomogram exhibited superior performance in both the training and validation cohorts. Furthermore, the calibrated nomogram predicted survival rates that closely corresponded to actual survival rates, while the DCA demonstrated the considerable clinical usefulness of the nomogram.
conclusionWe have constructed a nomogram for predicting the CSS of small-intestine adenocarcinoma patients. This prognostic model may improve the ability of clinicians to predict survival in individual patients and provide them with treatment recommendations.
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