SynthesisPeerJ2026
Risk prediction models for venous thromboembolism among patients with multiple myeloma: a systematic review and meta-analysis.
Synthesis in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Risk prediction models help identify multiple myeloma (MM) patients at high risk of venous thromboembolism (VTE) and guide clinical decisions. However, their applicability and accuracy remain unclear. This study aims to systematically review existing VTE risk models in MM patients. Methods: We systematically searched PubMed, Embase, Cochrane Library, and Web of Science for studies on VTE risk prediction models in patients with MM, up to March 31, 2026. Two investigators independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies using the PROBAST tool. Data analysis was performed using the "meta" and "metafor" packages in R software. Results: A total of 14 studies on VTE risk prediction models in MM patients were included, involving the development and/or validation of seven risk assessment tools. Meta-analysis showed that the overall VTE incidence in MM patients was 7.9% (95% CI [6.2-10.1%]). The combined area under the curve (AUCs) of the seven tools ranged from 0.57 to 0.68, with the IMPEDE VTE and IMPEDED VTE scores showing the best performance. Only two studies used the Hosmer-Lemeshow test for model calibration, and all studies presented the models in formula form. All included studies were at high risk of bias, mainly in the outcome and analysis domains. Conclusion: Existing VTE risk models for MM patients show low predictive performance (pooled AUC < 0.7) and limited clinical use. Future research should focus on model updating and external validation to improve accuracy and applicability. PROSPERO Registration number ID: CRD420251024346.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.