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イトウ トモキ
ITO TOMOKI 伊藤 量基 所属 関西医科大学 内科学第一講座 職種 教授 |
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| 論文種別 | 原著(症例報告除く) |
| 言語種別 | 英語 |
| 査読の有無 | 査読あり |
| 表題 | Elevation of Early Plasma Biomarkers in Patients with Clinical Risk Factors Predicts Increased Nonrelapse Mortality after Allogeneic Hematopoietic Stem Cell Transplantation |
| 掲載誌名 | 正式名：Transplantation and cellular therapy 略 称：Transplant Cell Ther ISSNコード：26666375/26666367 |
| 掲載区分 | 国外 |
| 巻・号・頁 | 27(8),pp.660.e1-660.e8 |
| 著者・共著者 | Hotta M, Satake A, Yoshimura H, Fujita S, Katayama Y, Ota S, Hanamoto H, Oyake T, Ito S, Okada M, Nakanishi T, Ito T, Ishii K, Nomura S. |
| 発行年月 | 2021/08 |
| 概要 | Early prediction of nonrelapse mortality (NRM) in patients undergoing allogeneic
hematopoietic stem cell transplantation (allo-HSCT) based on the results of laboratory tests is challenging. Thus, there is a need to evaluate biomarkers for prediction of NRM, a major problem that offsets the advantages of allo-HSCT. We tested the validity and efficacy of 2 plasma biomarkers, ST2 and Reg3α, based on the Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm, for early prediction of NRM in Japanese patients who underwent allo-HSCT. We conducted a multicenter retrospective study to analyze the clinical data of 112 patients with hematopoietic malignancies who underwent allo-HSCT. Patient blood samples on day 7 after allo-HSCT were obtained from 6 hospitals. The plasma concentrations of ST2 and Reg3α were used to calculate a 6-month NRM risk score. Based on the scores determined in this study, we identified 64 low-risk patients and 48 high-risk patients for the 6-month NRM. The cumulative incidence of 6-month NRM was 29.2% in the high-risk group and 10.9% in the low-risk group (P < .05). The cumulative incidence of relapse mortality was similar in the high-risk and low-risk patients. The biomarker score was predictive in patients with an unrelated donor, an HLA-mismatched donor, high/very high Disease Risk Index, and Hematopoietic Cell Transplantation Comorbidity Index ≥1. Multivariate analysis identified high biomarker probability as a significant predictor of NRM. The MAGIC algorithm based on blood samples obtained at 7 days after allo-HSCT can identify individuals at high risk for NRM among patients with clinical risk factors for NRM in a Japanese cohort. |
| DOI | 10.1016/j.jtct.2021.04.025 |
| PMID | 33989832 |