Trial reportJournal of cancer research and clinical oncology2023
Prognostic nomogram for colorectal cancer patients with multi-organ metastases: a Surveillance, Epidemiology, and End Results program database analysis.
Trial report in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 3 citations in OpenAlex.
- Training and validation of a nomogram for predicting synchronous distant organ metastasis in patients with very-early-onset colorectal cancer.Journal of gastrointestinal oncology · 2026Article
- Prognostic nomogram for T3-T4 primary colorectal cancer patients with perineural invasion after surgery: a Surveillance, Epidemiology, and End Results program database analysis.Journal of gastrointestinal oncology · 2025Article
- Albumin-bilirubin score: a promising predictor of postoperative distant metastasis in patients with colorectal cancer.Biomarkers in medicine · 2025Article
- Analysis of cancer-specific survival in patients with metastatic colorectal cancer: A evidence-based medicine study.World journal of gastrointestinal surgery · 2024Article
- Exosomal non-coding RNAs: Blueprint in colorectal cancer metastasis and therapeutic targets.Non-coding RNA research · 2023Review
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA nomogram that integrates risk models and clinical characteristics can accurately predict the prognosis of individual patients. We aimed to identify the prognostic factors and establish nomograms for predicting overall survival (OS) and cause-specific survival (CSS) in patients with multi-organ metastatic colorectal cancer (CRC).
methodsDemographic and clinical information on multi-organ metastases from 2010 to 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) Program. Univariate and multivariate Cox analyses were used to identify independent prognostic factors that were used to develop nomograms to predict CSS and OS, and to assess the concordance index (C-index), area under the curve (AUC), and calibration curve.
resultsThe patients were randomly assigned to the training and validation groups at a 7:3 ratio. A Cox proportional hazards model was conducted for CRC patients to identify independent prognostic factors, including age, sex, tumor size, metastases, degree of differentiation, stage T, stage N, primary and metastasis surgery. The competing risk models employed by Fine and Gray were used to identify the risk factors for CRC. Death from other causes was treated as a competing event, and Cox models were used to identify the factors for death to identify the independent factors of CSS. By incorporating the corresponding independent prognostic factors, we established prognostic nomograms for OS and CSS. Finally, we used the C-index, ROC curve, and calibration plots to assess the utility of the nomogram.
conclusionsUsing the SEER database, we constructed a predictive model for CRC patients with multi-organ metastases. Nomograms provide clinicians with 1-, 3-, and 5-year OS and CSS predictions for CRC, allowing them to formulate appropriate treatment plans.
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