Trial reportBlood advances2018
A novel predictive approach for GVHD after allogeneic SCT based on clinical variables and cytokine gene polymorphisms.
Trial report in Blood advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Review of Genetic Variation as a Predictive Biomarker for Chronic Graft-Versus-Host-Disease After Allogeneic Stem Cell Transplantation.Frontiers in immunology · 2020Pooled it
- Validated clinical risk score for acute graft-versus-host disease in adult allogeneic hematopoietic cell transplantation.Blood advances · 2026Article
- Deep insight into cytokine storm: from pathogenesis to treatment.Signal transduction and targeted therapy · 2025Review
- Identification of predictive models including polymorphisms in cytokines genes and clinical variables associated with post-transplant complications after identical HLA-allogeneic stem cell transplantation.Frontiers in immunology · 2024Article
- Allogeneic stem cell transplantation in the treatment of acute myeloid leukemia: An overview of obstacles and opportunities.World journal of clinical cases · 2023Review
- Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy.Frontiers in neurology · 2023Article
- Risk prediction of CMV reactivation after allogeneic stem cell transplantation using five non-HLA immunogenetic polymorphisms.Annals of hematology · 2022Article
- Observational
- Genetic susceptibility to acute graft versus host disease in pediatric patients undergoing HSCT.Bone marrow transplantation · 2021Article
- The Association Between Single-Nucleotide Polymorphisms of Co-Stimulatory Genes Within Non-HLA Region and the Prognosis of Leukemia Patients With Hematopoietic Stem Cell Transplantation.Frontiers in immunology · 2021Article
- A gut microbiota score predicting acute graft-versus-host disease following myeloablative allogeneic hematopoietic stem cell transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020Article
- Biomarkers for Allogeneic HCT Outcomes.Frontiers in immunology · 2020Review
- Multiple functional variants in theBlood advances · 2019Article
- Validation of genetic associations with acute GVHD and nonrelapse mortality in DISCOVeRY-BMT.Blood advances · 2019Article
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Authors and funding
29 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite considerable advances in our understanding of the pathophysiology of graft-versus-host disease (GVHD), its prediction remains unresolved and depends mainly on clinical data. The aim of this study is to build a predictive model based on clinical variables and cytokine gene polymorphism for predicting acute GVHD (aGVHD) and chronic GVHD (cGVHD) from the analysis of a large cohort of HLA-identical sibling donor allogeneic stem cell transplant (allo-SCT) patients. A total of 25 SNPs in 12 cytokine genes were evaluated in 509 patients. Data were analyzed using a linear regression model and the least absolute shrinkage and selection operator (LASSO). The statistical model was constructed by randomly selecting 85% of cases (training set), and the predictive ability was confirmed based on the remaining 15% of cases (test set). Models including clinical and genetic variables (CG-M) predicted severe aGVHD significantly better than models including only clinical variables (C-M) or only genetic variables (G-M). For grades 3-4 aGVHD, the correct classification rates (CCR1) were: 100% for CG-M, 88% for G-M, and 50% for C-M. On the other hand, CG-M and G-M predicted extensive cGVHD better than C-M (CCR1: 80% vs. 66.7%, respectively). A risk score was calculated based on LASSO multivariate analyses. It was able to correctly stratify patients who developed grades 3-4 aGVHD (
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