A Nomogram for Predicting Cancer-Associated Venous Thromboembolism in Hospitalized Patients Receiving Chemoradiotherapy for Cancer.

IF 2.5 4区医学 Q3 ONCOLOGY

Cancer Control Pub Date : 2024-01-01 DOI:10.1177/10732748241290767

Yan Sisi, Li Genpeng, Chen Yao, Song Suting, Tang Rongying, Du Jiayi, Zhang Zhaoli, Wang Chunyu

{"title":"A Nomogram for Predicting Cancer-Associated Venous Thromboembolism in Hospitalized Patients Receiving Chemoradiotherapy for Cancer.","authors":"Yan Sisi, Li Genpeng, Chen Yao, Song Suting, Tang Rongying, Du Jiayi, Zhang Zhaoli, Wang Chunyu","doi":"10.1177/10732748241290767","DOIUrl":null,"url":null,"abstract":"Purpose: The aim of this study was to develop a novel nomogram to predict cancer-associated venous thromboembolism (CAT) in hospitalized patients with cancer who receive chemoradiotherapy.Methods: This was a retrospective cohort study of hospitalized patients with cancer who received chemoradiotherapy between January 2010 and December 2022. Predictive factors for CAT were determined using univariate and multivariate logistic regression analyses, and a risk prediction model based on the nomogram was constructed and validated internally. Nomogram performance was assessed using receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA).Results: A total of 778 patients were eligible for inclusion in this study. The nomogram incorporated 5 independent risk factors: age, cancer stage, use of nonsteroidal anti-inflammatory drugs, D-dimer levels, and history of diabetes mellitus. The area under the curve (AUC) of the nomogram for the training and validation cohorts was 0.816 and 0.781, respectively, with 95% confidence intervals (CIs) of 0.770-0.861 and 0.703-0.860, respectively. The calibration and DCA curves also displayed good agreement and clinical applicability of the nomogram model.Conclusions: The incidence of CAT was relatively high among patients with cancer receiving chemoradiotherapy. The nomogram risk model developed in this study has good prediction efficiency and can provide a reference for the clinical evaluation of the risk of adverse outcomes in patients with cancer receiving chemoradiotherapy.","PeriodicalId":49093,"journal":{"name":"Cancer Control","volume":"31 ","pages":"10732748241290767"},"PeriodicalIF":2.5000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11497502/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Control","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/10732748241290767","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Purpose: The aim of this study was to develop a novel nomogram to predict cancer-associated venous thromboembolism (CAT) in hospitalized patients with cancer who receive chemoradiotherapy.

Methods: This was a retrospective cohort study of hospitalized patients with cancer who received chemoradiotherapy between January 2010 and December 2022. Predictive factors for CAT were determined using univariate and multivariate logistic regression analyses, and a risk prediction model based on the nomogram was constructed and validated internally. Nomogram performance was assessed using receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA).

Results: A total of 778 patients were eligible for inclusion in this study. The nomogram incorporated 5 independent risk factors: age, cancer stage, use of nonsteroidal anti-inflammatory drugs, D-dimer levels, and history of diabetes mellitus. The area under the curve (AUC) of the nomogram for the training and validation cohorts was 0.816 and 0.781, respectively, with 95% confidence intervals (CIs) of 0.770-0.861 and 0.703-0.860, respectively. The calibration and DCA curves also displayed good agreement and clinical applicability of the nomogram model.

Conclusions: The incidence of CAT was relatively high among patients with cancer receiving chemoradiotherapy. The nomogram risk model developed in this study has good prediction efficiency and can provide a reference for the clinical evaluation of the risk of adverse outcomes in patients with cancer receiving chemoradiotherapy.

查看原文本刊更多论文

预测接受癌症化放疗的住院患者癌症相关静脉血栓栓塞的提名图。

目的：本研究旨在开发一种新型提名图，用于预测接受化学放疗的住院癌症患者的癌症相关静脉血栓栓塞症（CAT）：这是一项回顾性队列研究，研究对象是2010年1月至2022年12月期间接受化放疗的住院癌症患者。采用单变量和多变量逻辑回归分析确定了CAT的预测因素，并基于提名图构建了风险预测模型，并在内部进行了验证。使用接收器操作特征（ROC）、校准曲线和决策曲线分析（DCA）评估了提名图的性能：共有 778 名患者符合研究条件。提名图包含 5 个独立风险因素：年龄、癌症分期、使用非甾体抗炎药、D-二聚体水平和糖尿病史。训练队列和验证队列的提名图曲线下面积（AUC）分别为 0.816 和 0.781，95% 置信区间（CI）分别为 0.770-0.861 和 0.703-0.860。校准曲线和DCA曲线也显示了提名图模型的良好一致性和临床适用性：结论：在接受化放疗的癌症患者中，CAT的发生率相对较高。结论：在接受化疗放疗的癌症患者中，CAT的发生率相对较高，本研究建立的提名图风险模型具有良好的预测效率，可为临床评估癌症患者接受化疗放疗的不良结局风险提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cancer Control ONCOLOGY-

CiteScore

3.80

自引率

0.00%

发文量

148

审稿时长

>12 weeks

期刊介绍： Cancer Control is a JCR-ranked, peer-reviewed open access journal whose mission is to advance the prevention, detection, diagnosis, treatment, and palliative care of cancer by enabling researchers, doctors, policymakers, and other healthcare professionals to freely share research along the cancer control continuum. Our vision is a world where gold-standard cancer care is the norm, not the exception.