Machine Learning Prognostic Models for Acute Leukemia and Decision Making Tools for Clinical Practice and Patients.
Project/Area Number |
19K16975
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 52010:General internal medicine-related
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Research Institution | Niigata University |
Principal Investigator |
Fuse Kyoko 新潟大学, 医歯学総合病院, 講師 (40783329)
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Project Period (FY) |
2019-04-01 – 2023-03-31
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Project Status |
Completed (Fiscal Year 2022)
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Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2021: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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Keywords | 急性白血病 / 予後因子 / 機械学習 / 急性骨髄性白血病 / 医療費 / 治療方針決定ツール / 意思決定補助 / 予測モデル / 個別化医療 |
Outline of Research at the Start |
急性白血病は小児から高齢者まで幅広い年齢層に発症する難治性疾患で、若年者では標準的化学療法や造血幹細胞移植、高齢者では減弱した治療や支持療法を行う。最近は新薬の開発と導入も進み、治療選択肢は増え、また患者ごとの背景も多様である。複数の因子を総合的に判断し患者毎に治療をカスタマイズするような個別化医療が可能となれば、急性白血病の予後はさらに改善できると考える。 本研究では、急性白血病患者の疾患背景、診療・患者情報をもとに機械学習で経過予測モデルの作成と治療の成功パターン検出を行う。この成果により担当医の診療補助や患者の自己決定の補助として有用なツールの開発を目指す。
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Outline of Final Research Achievements |
We attempted to create a predictive model for the course of acute leukemia patients in order to synthesize multiple prognostic factors and customize treatment for each patient. First, we searched for novel prognostic factors to create the model. We identified the Marker chromosome as the molecular background of the disease, WT-1 mRNA expression thresholds, intensive oral care as supportive care to prevent complications, and HLA gene polymorphisms involved in tumor immune response.It was pointed out that the ADTree program has the potential to improve prognosis by changing the transplant source according to disease and stage prior to HSCT, and that preventive intervention may be possible by predicting the frequency of graft-versus-host disease.
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Academic Significance and Societal Importance of the Research Achievements |
機械学習による予後予測モデルで治療成功のための分岐点を抽出する可能性を明らかにできた。今後の個別化医療に応用が期待でいる。機械学習の精度を高めるためには、診療記録・データの質とばらつき、解析データの量などが今後の課題と考えられる。今後は、特に予備能が低い高齢者において治療選択と予後、医療費への影響に関する個別経過予測モデルの構築を試みたい。
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Report
(5 results)
Research Products
(39 results)
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[Journal Article] Comparison of transplant outcomes between haploidentical transplantation and single cord blood transplantation in non‐remission acute myeloid leukaemia: A nationwide retrospective study2023
Author(s)
K Matsuda , T Konuma , K Fuse , M Masuko , K Kawamura , M Hirayama , N Uchida , K Ikegame , A Wake , T Eto , N Doki , S Miyakoshi , M Tanaka , S Takahashi , M Onizuka , K Kato , T Kimura , T Ichinohe , N Takayama , H Kobayashi , H Nakamae , Y Atsuta , J Kanda , M Yanada
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Journal Title
British Journal of Haematology
Volume: 201
Issue: 1
Pages: 106-113
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] WT1-specific CD8+ cytotoxic T cells with the capacity for antigen-specific expansion accumulate in the bone marrow in MDS.2021
Author(s)
Tatsuya Suwabe, Yasuhiko Shibasaki, Hiroyuki Sato, Suguru Tamura, Takayuki Katagiri, Hiroki Nemoto, Takuya Kasami, Takashi Kozakai, Ayako Nanba, Toshiki Kitajima, Kyoko Fuse, Takashi Ushiki, Hirohito Sone, Miwako Narita, Masayoshi Masuko
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Journal Title
International journal of hematology
Volume: 113
Issue: 5
Pages: 723-734
DOI
Related Report
Peer Reviewed
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[Journal Article] Patient-based Prediction Algorithm of Relapse After allo-HSCT for Acute Leukemia and Its Usefulness in the Decision-Making Process Using a Machine Learning Approach2019
Author(s)
Fuse K, Uemura S, Tamura S, Suwabe T, Katagiri T, Tanaka T, Ushiki T, Shibasaki Y, Sato N, Yano T, Kuroha T, Hashimoto S, Furukawa T, Narita M, Sone H, Masuko M.
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Journal Title
Cancer Med.
Volume: Sep;8(11)
Issue: 11
Pages: 5058-5067
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] Using a machine learning algorithm to predict acute graft-versus-host disease following allogeneic transplantation.2019
Author(s)
Arai Y, Kondo T, Fuse K, Shibasaki Y, Masuko M, Sugita J, Teshima T, Uchida N, Fukuda T, Kakihana K, Ozawa Y, Eto T, Tanaka M, Ikegame K, Mori T, Iwato K, Ichinohe T, Kanda Y, Atsuta Y.
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Journal Title
Blood Adv.
Volume: 3(22)
Issue: 22
Pages: 3626-3634
DOI
NAID
Related Report
Peer Reviewed / Open Access
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[Presentation] Stratification of Intermediate-Risk Acute Myeloid Leukemia According to the Expression Level of WT1 mRNA at Diagnosis.2021
Author(s)
Fuse K, Kaihatsu A, Kitajima T, Momoi A, Kasami T, Katagiri T, Shibasaki Y, Furukawa T, Narita M, Sone H, Masuko M.
Organizer
第63回米国血液学会総会
Related Report
Int'l Joint Research
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[Presentation] Post-transplant relapse of AML within one year is associated with a high mortality rate2021
Author(s)
片桐隆幸, 本宮奈津子, 武田ルイ, 水戸部正樹, 米沢穂高, 諏訪部達也, 布施香子, 柴崎康彦, 瀧澤淳, 曽根博仁, 増子正義
Organizer
第83回日本血液学会学術集会
Related Report
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[Presentation] Significance of Marker Chromosome on the Outcome of Allogeneic Hematopoietic Stem Cell Transplantation for AML.2020
Author(s)
Fuse K, Masuko M, Mizuno S, Harada K, Uchida N, Doki N, Fukuda T, Tanaka M, Ozawa Y, Ikegame K, Eto T, Kanda Y, Ichinohe T, Atsuta Y, Yanada M.
Organizer
62nd ASH Annual Meeting and Exposition
Related Report
Int'l Joint Research
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[Presentation] Genetic Manipulation Resulting in Decreased Donor Chondroitin sulfate Synthesis Mitigates GVHD Following Allogeneic Hematopoietic Cell Transplantation in a Murine Model.2020
Author(s)
Tamura S, Ushiki T, Suwabe T, Katagiri T, Tanaka T, Fuse K, Shibasaki Y, Narita M, Igarashi M, Sone H, Masuko M.
Organizer
62nd ASH Annual Meeting and Exposition
Related Report
Int'l Joint Research
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[Presentation] INTENSIVE ORAL CARE CAN REDUCE BLOOD STREAM INFECTION POST NEUTROPHIL ENGRAFTMENT IN ALLOGENEIC HSCT.2019
Author(s)
Suwabe T, Fuse K, Katsura K, Tanaka K, Tamura S, Katairi T, Tanaka T, Ushiki T, Shibasaki Y, Narita M, Sone H, Masuko M.
Organizer
The 24th EHA (European Hematology Association) Congress.
Related Report
Int'l Joint Research
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[Presentation] MARKER CHROMOSOME IS A STRONG POOR PROGNOSIS FACTOR AFTER ALLOGENEIC HSCT FOR AML PATIENTS.2019
Author(s)
Fuse K, Tanaka T, Uemura S, Tamura S, Suwabe T, Katagiri T, Ushiki T, Shibasaki Y, Satou N, Yano T, Kuroha T, Hashimoto S, Furukawa T, Narita M, Sone H, Masuko M.
Organizer
The 24th EHA (European Hematology Association) Congress.
Related Report
Int'l Joint Research
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