ArticleJournal of cancer research and clinical oncology2023
A competing risk nomogram to predict cancer-specific mortality of patients with late-onset colorectal cancer.
Article 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 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Nomogram for predicting the development of pneumonia after colorectal cancer surgery.Scientific reports · 2025Article
- Survival prediction in sigmoid colon cancer patients with liver metastasis: a prospective cohort study.JNCI cancer spectrum · 2024Article
- Conditional survival analysis and real-time prognosis prediction in stage III T3-T4 colon cancer patients after surgical resection: a SEER database analysis.International journal of colorectal disease · 2024Article
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Authors and funding
5 authors at 4 institutions in 1 country.
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Abstract
objectiveThis study aimed to compare the clinical characteristics and survival differences between early-onset colorectal cancer (EOCRC) patients and late-onset colorectal cancer (LOCRC) patients, identify the risk factors for cancer-specific mortality (CSM) in LOCRC patients and construct a mortality risk assessment nomogram.
methodsCRC patients diagnosed pathologically between 2010 and 2019 in the SEER database were included and divided into the early-onset group and the late-onset group, and the late-onset group was divided into the training and validation sets. The Fine-Gray competing risk model was applied to analyze the prognostic factors of LOCRC patients and establish a competing risk nomogram for CSM.
resultsThere are differences in the distribution of multiple clinical features between the early-onset group and the late-onset group. Age, tumor size, histological type, pathological grading, T stage, N stage, M stage, SEER stage, primary tumor surgery, metastatic lesion surgery, radiotherapy, chemotherapy, neural invasion, and carcinoembryonic antigen (CEA) were independent influencing factors of the CSM rate in LOCRC patients. The C-index of the prognosis model outweighed 0.8, and the calibration curves fitted the reference line well.
conclusionThe CSM competing risk nomogram for LOCRC patients in this study had acceptable predictive performance that could be applied to the clinic.
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