Objectives: This review aims to compare the performance of available risk assessment models (RAMs) for predicting peripherally inserted central catheter-related venous thrombosis (PICC-RVT) in adult patients with cancer.
Methods: A systematic search was conducted across ten databases from inception to October 20, 2023. Studies were eligible if they compared the accuracy of a RAM to that of another RAM for predicting the risk of PICC-RVT in adult patients with cancer. Two reviewers independently performed the study selection, data extraction and risk of bias assessments. A Bayesian network meta-analysis (NMA) was used to evaluate the performance of the RAMs.
Results: A total of 1931 studies were screened, and 7 studies with 10 RAMs were included in the review. The most widely used RAMs were the Caprini (4 studies), Padua prediction score (3 studies), Autar (3 studies), Michigan risk score (2 studies) and Seeley score (2 studies). The sensitivity, specificity and accuracy varied markedly between the models. Notably, the Caprini score achieved higher sensitivity than 4 RAMs (Wells, Revised Geneva, modified MRS, MRS). The Michigan risk score had greater specificity than did the other 6 RAMs (Caprini, Autar, Padua, Seeley, the novel RAM, Wells). The predictive accuracy of the MRS is significantly greater than that of the Caprini and Autar RAM.
Conclusion: The MRS could be the most accurate RAM for identifying patients at high risk of PICC-RVT. However, as limited studies are available, more rigorous studies should be conducted to examine the accuracy of the Michigan risk score for PICC-RVT in different contexts.
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