{"title":"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。","authors":"Wenjuan Yang, Meng Fang, Kangqin Cai, Qin Pan, Cheng Zhang, Jiquan Zhang","doi":"10.3389/fmed.2025.1580920","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>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.</p><p><strong>Systematic review registration: </strong>PROSPERO, identifier: CRD42024516563.</p>","PeriodicalId":12488,"journal":{"name":"Frontiers in Medicine","volume":"12 ","pages":"1580920"},"PeriodicalIF":3.1000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12245904/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictive model for CRT risk in cancer patients with central venous access devices: a systematic review and meta-analysis.\",\"authors\":\"Wenjuan Yang, Meng Fang, Kangqin Cai, Qin Pan, Cheng Zhang, Jiquan Zhang\",\"doi\":\"10.3389/fmed.2025.1580920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>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.</p><p><strong>Systematic review registration: </strong>PROSPERO, identifier: CRD42024516563.</p>\",\"PeriodicalId\":12488,\"journal\":{\"name\":\"Frontiers in Medicine\",\"volume\":\"12 \",\"pages\":\"1580920\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12245904/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fmed.2025.1580920\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fmed.2025.1580920","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Predictive model for CRT risk in cancer patients with central venous access devices: a systematic review and meta-analysis.
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.
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
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