ArticleInternational journal of colorectal disease2023
Prediction models for overall and cancer-specific survival in patients with metastatic early-onset colorectal cancer: a population-based study.
Article in International journal of colorectal disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Albumin and neutrophil combined prognostic grade for predicting overall survival in colorectal cancer: a retrospective cohort study.Frontiers in oncology · 2026Article
- Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology.BMC gastroenterology · 2025Article
- Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early-onset colorectal cancer.Frontiers in oncology · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
purposeMetastatic early-onset colorectal cancer (EO-CRC) is on the rise, yet there is a dearth of predictive models for this disease. Therefore, it is crucial to develop a nomogram to aid in the early detection and management of metastatic colorectal cancer in young patients.
methodsWe retrieved data from the SEER database on patients with metastatic colorectal cancer aged 50 or younger between 2010 and 2017. The data were randomly allocated in a 7:3 ratio to training and validation cohorts, and univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) at 1, 3, and 5 years. The nomograms were developed based on these factors, and their discriminatory and calibration capabilities were validated. Using the nomogram risk scores, patients were stratified into low-risk and high-risk groups.
resultsThe study included 2470 patients with metastatic EO-CRC. Univariate and multivariate Cox regression analysis identified 12 independent risk factors that were included in the nomogram. The training cohort had a consistency index (C-index) of 0.71, while the validation cohort had a C-index of 0.70, demonstrating good predictive accuracy. Calibration plots showed a high level of consistency between the observed and predicted values, with overlapping plots along the diagonal. The decision curve analysis (DCA) revealed that the nomogram had a high clinical application value.
conclusionsThe novel nomograms were created to predict the prognosis of patients with metastatic EO-CRC, which can aid clinicians in developing more effective treatment strategies and contribute to more accurate prognostic assessments.
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