Risk assessment models for PICC-related venous thrombosis in adult patients with cancer: A network meta-analysis
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View abstract on PubMed
Summary
This summary is machine-generated.The Michigan risk score (MRS) shows promise as the most accurate tool for predicting peripherally inserted central catheter-related venous thrombosis (PICC-RVT) in cancer patients. Further research is needed to confirm its effectiveness across diverse clinical settings.
Area Of Science
- Oncology
- Vascular Access
- Medical Informatics
Background
- Peripherally inserted central catheters (PICCs) are crucial for cancer patient care but carry a risk of venous thrombosis (PICC-RVT).
- Accurate risk assessment models (RAMs) are needed to identify high-risk patients and guide preventative strategies.
Purpose Of The Study
- To systematically compare the predictive performance of various RAMs for PICC-RVT in adult cancer patients.
- To identify the most accurate RAM for this specific patient population.
Main Methods
- A systematic literature search was performed across ten databases up to October 20, 2023.
- Included studies compared the accuracy of at least two RAMs for predicting PICC-RVT.
- A Bayesian network meta-analysis (NMA) was employed to evaluate RAM performance.
Main Results
- Seven studies involving 10 RAMs were included after screening 1931 records.
- The Caprini, Padua prediction score, Autar, Michigan risk score (MRS), and Seeley score were among the most frequently evaluated RAMs.
- The MRS demonstrated significantly greater predictive accuracy compared to the Caprini and Autar RAMs, and higher specificity than six other models.
Conclusions
- The MRS appears to be the most accurate RAM for identifying cancer patients at high risk of PICC-RVT.
- Additional high-quality studies are recommended to validate the accuracy of the MRS in varied clinical contexts.
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