Evidence map›Paper›PMID 42703478›Full record

ArticleJournal of gastrointestinal oncology2026

A predictive nomogram model for overall survival in obstructive colorectal cancer based on clinical and laboratory indicators.

Pingxia Lu, Wanyun Su, Dingman Huang, Xinyu Huang, Cuifeng Zheng, Baowei Xu, Xianqiang Chen, Junrong Zhang, Zhengyuan Huang

Abstract read
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Article in Journal of gastrointestinal oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Pingxia Lu *Department of Laboratory Medicine, Fujian Medical University Union Hospital, Fuzhou, China.
Wanyun Su *Department of Laboratory Medicine, Fujian Medical University Union Hospital, Fuzhou, China.
Dingman Huang *Clinical Medicine, Fujian Medical University, Fuzhou, China.
Xinyu HuangDepartment of Laboratory Medicine, Fujian Medical University Union Hospital, Fuzhou, China.
Cuifeng ZhengDepartment of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Baowei XuDepartment of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Xianqiang ChenDepartment of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Junrong ZhangDepartment of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Zhengyuan HuangDepartment of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obstructive colorectal cancer (oCRC) correlates with advanced disease and poor outcomes. This study aimed to identify independent prognostic factors using clinical and laboratory data and construct a predictive nomogram for oCRC patients' individualized survival estimation and clinical decision-making. Methods: A retrospective cohort of 167 patients with histologically confirmed oCRC admitted to hospital between February 2019 and February 2021 was analyzed. Patients were randomly divided into a training cohort (n=116) and a validation cohort (n=51) in a 7:3 ratio. Prognostic variables were identified using univariate and multivariate Cox proportional hazards regression analyses. A nomogram was developed based on independent prognostic factors. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA) to evaluate its discrimination, calibration, and clinical utility, respectively. Results: Multivariate Cox regression analysis identified five independent prognostic factors: M stage [hazard ratio (HR) =1.917, 95% confidence interval (CI): 1.005-3.657, P=0.048], tumor grade (HR =0.229, 95% CI: 0.096-0.543, P<0.001), carbohydrate antigen 19-9 (CA19-9; HR =3.919, 95% CI: 2.038-7.538, P<0.001), albumin-to-globulin ratio (AGR; HR =2.103, 95% CI: 1.158-3.817, P=0.02), and platelet-to-lymphocyte ratio (PLR; HR =1.873, 95% CI: 1.013-3.464, P=0.045). These variables were incorporated into a prognostic nomogram. The model demonstrated good discriminatory ability, with area under the curve (AUC) values of 0.721 in the training cohort and 0.776 in the validation cohort. Additionally, the model exhibited satisfactory calibration and clinical utility, as evidenced by DCA. Conclusions: The nomogram (incorporating M stage, tumor grade, CA19-9, AGR, PLR) provides individualized prognosis for oCRC patients, and may aid clinical risk stratification and therapeutic decision-making.

Indexed as

Intestinal obstruction of colorectal cancernomogramprognostic

Identifiers

PMID42703478
PMCPMC13546597

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.