Predictive model for CRT risk in cancer patients with central venous access devices: a systematic review and meta-analysis.

IF 3.1 3区医学 Q1 MEDICINE, GENERAL & INTERNAL

Frontiers in Medicine Pub Date : 2025-06-27 eCollection Date: 2025-01-01 DOI:10.3389/fmed.2025.1580920

Wenjuan Yang, Meng Fang, Kangqin Cai, Qin Pan, Cheng Zhang, Jiquan Zhang

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引用次数: 0

Abstract

Introduction: With the high incidence of central venous access device catheter-related thrombosis (CRT) in patients with cancer, its early onset, and the characteristics of clinically insignificant symptoms, risk assessment is essential for the targeted application of thromboprophylaxis. The aim of this paper was to review the risk prediction models developed for central venous access device CRT in patients with cancer and to evaluate their performance.

Methods: PubMed, Embase, Web of Science, Cochrane Library, CNKI, SinoMed, Wanfang Data, and VIP databases were searched, and the search timeframes ranged from the establishment of the database to May 22, 2024. Two researchers independently performed literature screenings, data extractions, and quality assessments. The risk of bias and applicability of the included studies were assessed using the Predictive Model Risk of Bias Assessment Tool. A meta-analysis of the areas under the curve (AUC) values for model validation was performed using Stata 17.0 software.

Results: Nineteen papers with 29 predictive models were included in this systematic review, reporting AUC values of 0.470-1.000. The incidence of central venous access device CRT in cancer patients ranges from 2.02 to 39.4%. The most commonly used predictors are D-dimer levels, BMI, and diabetes. All studies were judged to have a high risk of bias, mainly due to poor reporting of the areas analyzed. The combined AUC value of the six validated models was 0.81 (95% confidence interval: 0.76-0.86), indicating good model discrimination.

Discussion: Most available CRT prediction models exhibited moderate-to-good predictive performance. However, all the studies were rated as having a high risk of bias according to the PROBAST scale. Future studies should adhere to methodological and reporting guidelines for large-sample, multi-center external validation of models, focusing on studies that report rigorous design and optimization or on the development of new models.

Systematic review registration: PROSPERO, identifier: CRD42024516563.

查看原文本刊更多论文

使用中心静脉通路装置的癌症患者CRT风险的预测模型：一项系统回顾和荟萃分析。

导言：肿瘤患者中心静脉通路装置导管相关性血栓形成（CRT）发生率高、起病早、临床症状不明显等特点，风险评估对于有针对性地应用血栓预防至关重要。本文的目的是回顾中心静脉通路装置CRT在癌症患者中的风险预测模型，并评估其性能。方法：检索PubMed、Embase、Web of Science、Cochrane Library、CNKI、SinoMed、万方数据、VIP等数据库，检索时间范围为建库至2024年5月22日。两名研究人员独立进行文献筛选、数据提取和质量评估。使用预测模型偏倚风险评估工具评估纳入研究的偏倚风险和适用性。采用Stata 17.0软件对模型验证的曲线下面积（AUC）值进行meta分析。结果：本系统综述共纳入19篇论文29个预测模型，报告AUC值为0.470 ~ 1.000。中心静脉通路CRT在肿瘤患者中的发病率为2.02 ~ 39.4%。最常用的预测指标是d -二聚体水平、BMI和糖尿病。所有的研究都被判定为有高偏倚风险，主要是由于对所分析领域的报道不充分。6个验证模型的综合AUC值为0.81(95%置信区间为0.76 ~ 0.86)，表明模型判别性较好。讨论：大多数可用的CRT预测模型表现出中等到良好的预测性能。然而，根据PROBAST量表，所有的研究都被评为具有高偏倚风险。未来的研究应遵循大样本、多中心模型外部验证的方法学和报告指南，重点关注报告严格设计和优化或开发新模型的研究。系统评价注册：PROSPERO，标识符：CRD42024516563。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Medicine Medicine-General Medicine

CiteScore

5.10

自引率

5.10%

发文量

3710

审稿时长

12 weeks

期刊介绍： Frontiers in Medicine publishes rigorously peer-reviewed research linking basic research to clinical practice and patient care, as well as translating scientific advances into new therapies and diagnostic tools. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. In addition to papers that provide a link between basic research and clinical practice, a particular emphasis is given to studies that are directly relevant to patient care. In this spirit, the journal publishes the latest research results and medical knowledge that facilitate the translation of scientific advances into new therapies or diagnostic tools. The full listing of the Specialty Sections represented by Frontiers in Medicine is as listed below. As well as the established medical disciplines, Frontiers in Medicine is launching new sections that together will facilitate - the use of patient-reported outcomes under real world conditions - the exploitation of big data and the use of novel information and communication tools in the assessment of new medicines - the scientific bases for guidelines and decisions from regulatory authorities - access to medicinal products and medical devices worldwide - addressing the grand health challenges around the world