ArticleInternational journal of colorectal disease2024
A novel log odds of positive lymph nodes-based nomogram for predicting overall survival in patients with colorectal signet ring cell carcinoma: a SEER population-based study.
Article in International journal of colorectal disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Development and validation of machine learning models for predicting cancer-specific survival in colorectal signet ring cell carcinoma.BMC gastroenterology · 2026Article
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3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeConsidering the poor prognosis and high lymph node (LN) involvement rate of colorectal signet ring cell carcinoma (SRCC), this study aimed to construct a prognostic nomogram to predict overall survival (OS) with satisfactory accuracy and utility, based on LN status indicators with superior predictability.
methodsUsing the Surveillance, Epidemiology, and End Results (SEER) database, we obtained cases of colorectal SRCC patients and employed univariate and multivariate Cox analyses to determine independent prognostic factors. Kaplan-Meier curves were utilized to visualize survival differences among these factors. Receiver operating characteristic curves were generated to assess predictive performances of models incorporating various LN status indicators. A novel nomogram, containing optimal LN status indicators and other prognostic factors, was developed to predict OS, whose discriminatory ability and accuracy were evaluated using calibration curves and decision curve analysis.
resultsA total of 1663 SRCC patients were screened from SEER database. Older patients and those with grades III-IV, tumor sizes > 39 mm, T3/T4 stage, N1/N2 stage, M1 stage, and higher log odds of positive lymph nodes (LODDS) values exhibited poorer prognoses. Age, grade, tumor size, TNM stage, and LODDS were independent prognostic factors. The model containing N stage and LODDS outperformed the one relying solely on N stage as LN status indicator, resulting in a validated nomogram for accurately predicting OS in SRCC patients.
conclusionThe integration of LODDS, N stage, and other risk factors into a nomogram offered precise OS predictions, enhancing therapeutic decision-making and tailored follow-up management for colorectal SRCC patients.
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