Evidence map›Paper›PMID 41552715›Full record

ReviewAsia-Pacific journal of oncology nursing2026

Development and preliminary validation of a PICC-related venous thrombosis risk prediction model for cancer patients: A systematic review and meta-analysis predominantly based on Chinese populations.

Jiwen Zhang, Caiyun Li, Huijuan Zhang, Wenbo Wu, Xiaoshuang Sun, Wei Zhang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Asia-Pacific journal of oncology nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jiwen ZhangDepartment of Nursing, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Caiyun LiDepartment of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Huijuan ZhangDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wenbo WuDepartment of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaoshuang SunDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wei ZhangDepartment of Nursing, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To identify key risk factors for peripherally inserted central catheter -related deep venous thrombosis (PICC-RVT) in patients with cancer through a systematic review and meta-analysis, develop risk prediction model and validate its performance. Methods: A systematic literature search was performed in Pubmed, EMBASE, Web of Science (core collection), Scopus, CINAHL and Ovid databases from the time of their inception to June 2025. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) checklist. Meta-analysis was performed using RevMan 5.4 statistical software to identify independent risk factors for PICC-RVT in adult patients with cancer, then the effect of each independent risk factor was determined using Results: A total of 32 cohort studies involving 28,813 individuals (28 from China, 2 from UK, 1 each from US and Canada) were included. Twenty-one independent risk factors were identified through meta-analysis. The risk prediction model was developed using Conclusions: This study developed a PICC-RVT risk prediction model based primarily on Chinese patients with cancer. The model demonstrated moderate discrimination in preliminary single-center validation, but requires multi-center validation with adequate event numbers before clinical implementation. The model provides a framework for PICC-RVT risk stratification in Chinese and similar healthcare settings. Systematic review registration: PROSPERO (CRD420250651190).

Indexed as

Deep venous thrombosisMeta-analysisPatients with cancerPICCRisk prediction model

Identifiers

PMID41552715
PMCPMC12810564

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.