Evidence map›Paper›PMID 38698697›Full record

ArticleCancer medicine2024

A nomogram to predict the risk of venous thromboembolism in patients with colon cancer in China.

Yuanyuan Yang, Jiayi Zhan, Xiaosheng Li, Jun Hua, Haike Lei, Xiaoliang Chen

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Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yuanyuan YangDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, Chongqing, China.
Jiayi ZhanDepartment of Traditional Chinese Medicine, Chongqing University Cancer Hospital, Chongqing, China.
Xiaosheng LiChongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China.
Jun HuaDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, Chongqing, China.
Haike LeiChongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China.ORCID 0000-0003-0284-2052
Xiaoliang ChenDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, Chongqing, China.ORCID 0000-0002-3505-5314

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo create a nomogram for predicting the likelihood of venous thromboembolism (VTE) in colon cancer patients from China.

methodsThe data of colon cancer patients from Chongqing University Cancer Hospital between 2019 and 2022 were analyzed. Patients were divided into training set and internal validation set by random split-sample method in a split ratio of 7:3. The univariable and multivariable logistic analysis gradually identified the independent risk factors for VTE. A nomogram was created using all the variables that had a significance level of p < 0.05 in the multivariable logistic analysis and those with clinical significance. Calibration curves and clinical decision curve analysis (DCA) were used to assess model's fitting performance and clinical value. Harrell's C-index (concordance statistic) and the area under the receiver operating characteristic curves (AUC) were used to evaluate the predictive effectiveness of models.

resultsA total of 1996 patients were ultimately included. There were 1398 patients in the training set and 598 patients in the internal validation set. The nomogram included age, chemotherapy, targeted therapy, hypertension, activated partial thromboplastin time, prothrombin time, platelet, absolute lymphocyte count, and D-dimer. The C-index of nomogram and Khorana score were 0.754 (95% CI 0.711-0.798), 0.520 (95% CI 0.477-0.563) in the training cohort and 0.713 (95% CI 0.643-0.784), 0.542 (95% CI 0.473-0.612) in the internal validation cohort.

conclusionsWe have established and validated a nomogram to predict the VTE risk of colon cancer patients in China, which encompasses a diverse age range, a significant population size, and various clinical factors. It facilitates the identification of high-risk groups and may enable the implementation of targeted preventive measures.

Indexed as

Colonic NeoplasmsNomogramsVenous ThromboembolismAdultAgedChinaFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsROC Curvecolon cancernomogrampredictive modelvenous thromboembolism

Identifiers

PMID38698697
PMCPMC11066491

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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.