ArticleBone marrow transplantation2012
Identification by random forest method of HLA class I amino acid substitutions associated with lower survival at day 100 in unrelated donor hematopoietic cell transplantation.
Article in Bone marrow transplantation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Analysis of the different subpeptidomes presented by the HLA class I molecules of the B7 supertype.Cellular immunology · 2023Pooled it
- Guideline
- In silico prediction of nonpermissive HLA-DPB1 mismatches in unrelated HCT by functional distance.Blood advances · 2018Trial
- HLA micropolymorphisms confine neoantigen conformational adaptability and guide T cell receptor selectivity.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Identification of Critical Variables and Critical Gap Variables in Hospital Nurses' Job Satisfaction During the Dynamic Adjustment Phase of COVID-19 Prevention in China: A Hybrid Machine Learning and Decision Analysis Approach.Journal of nursing management · 2026Article
- HLA3D: an integrated structure-based computational toolkit for immunotherapy.Briefings in bioinformatics · 2022Article
- The Impact of Multiple Sclerosis Disease Status and Subtype on Hematological Profile.International journal of environmental research and public health · 2021Article
- Association of ProtectiveFrontiers in genetics · 2021Article
- Exploratory Study of Predicted Indirectly ReCognizable HLA Epitopes in Mismatched Hematopoietic Cell Transplantations.Frontiers in immunology · 2019Article
- Multistate recursively imputed survival trees for time-to-event data analysis: an application to AIDS and mortality post-HIV infection data.BMC medical research methodology · 2018Article
- Identification of high-risk amino-acid substitutions in hematopoietic cell transplantation: a challenging task.Bone marrow transplantation · 2016Article
- HLA-C expression levels define permissible mismatches in hematopoietic cell transplantation.Blood · 2014Article
- Article
- Identification of a permissible HLA mismatch in hematopoietic stem cell transplantation.Blood · 2014Article
- Association between CTL Precursor Frequency to HLA-C Mismatches and HLA-C Antigen Cell Surface Expression.Frontiers in immunology · 2014Article
- HLA-C Incompatibilities in Allogeneic Unrelated Hematopoietic Stem Cell Transplantation.Frontiers in immunology · 2014Review
- Article
- Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?Briefings in bioinformatics · 2013Article
- Unrelated hematopoietic stem cell donor matching probability and search algorithm.Bone marrow research · 2012Article
- Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The identification of important amino acid substitutions associated with low survival in hematopoietic cell transplantation (HCT) is hampered by the large number of observed substitutions compared with the small number of patients available for analysis. Random forest analysis is designed to address these limitations. We studied 2107 HCT recipients with good or intermediate risk hematological malignancies to identify HLA class I amino acid substitutions associated with reduced survival at day 100 post transplant. Random forest analysis and traditional univariate and multivariate analyses were used. Random forest analysis identified amino acid substitutions in 33 positions that were associated with reduced 100 day survival, including HLA-A 9, 43, 62, 63, 76, 77, 95, 97, 114, 116, 152, 156, 166 and 167; HLA-B 97, 109, 116 and 156; and HLA-C 6, 9, 11, 14, 21, 66, 77, 80, 95, 97, 99, 116, 156, 163 and 173. In all 13 had been previously reported by other investigators using classical biostatistical approaches. Using the same data set, traditional multivariate logistic regression identified only five amino acid substitutions associated with lower day 100 survival. Random forest analysis is a novel statistical methodology for analysis of HLA mismatching and outcome studies, capable of identifying important amino acid substitutions missed by other methods.
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