Evidence map›Paper›PMID 36794502›Full record

ArticleHaematologica2023

Integrated genetic and clinical prognostic factors for aggressive adult T-cell leukemia/lymphoma.

Takuro Kameda, Keisuke Kataoka, Ayako Kamiunten, Michihiro Hidaka, Hiroaki Miyoshi, Nobuaki Nakano, Kisato Nosaka, Makoto Yoshimitsu, Jun-Ichirou Yasunaga, Yasunori Kogure and 29 more

Abstract read
In one paragraph

Article in Haematologica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Identification of AK4 and RHOC as potential oncogenes addicted by adult T cell leukemia.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

39 authors.

Takuro KamedaDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki.
Keisuke KataokaDivision of Hematology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan; Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo.
Ayako KamiuntenDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki.
Michihiro HidakaNational Hospital Organization Kumamoto Medical Center, Kumamoto.
Hiroaki MiyoshiDepartment of Pathology, Kurume University School of Medicine, Kurume.
Nobuaki NakanoDepartment of Hematology, Imamura General Hospital, Kagoshima.
Kisato NosakaDepartment of Hematology, Rheumatology and Infectious Diseases, Faculty of Life Sciences, Kumamoto University of Medicine, Kumamoto.
Makoto YoshimitsuDepartment of Hematology and Rheumatology, Kagoshima University Hospital, Kagoshima.
Jun-Ichirou YasunagaDepartment of Hematology, Rheumatology and Infectious Diseases, Faculty of Life Sciences, Kumamoto University of Medicine, Kumamoto, Japan; Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto.
Yasunori KogureDivision of Molecular Oncology, National Cancer Center Research Institute, Tokyo.
Kotaro ShideDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki.
Masaharu MiyaharaDepartment of Internal Medicine, Karatsu Red Cross Hospital, Saga.
Takashi SakamotoDepartment of Hematology and Oncology, Graduate School of Medicine, Kyoto University, Kyoto.
Keiichi AkizukiDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki.
Tomonori HidakaDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki.
Yoko KubukiDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki.
Junji KoyaDivision of Molecular Oncology, National Cancer Center Research Institute, Tokyo.
Noriaki KawanoDepartment of Internal medicine, Miyazaki Prefectural Miyazaki Hospital, Miyazaki.
Kiyoshi YamashitaDepartment of Internal medicine, Miyazaki Prefectural Miyazaki Hospital, Miyazaki.
Hiroshi KawanoDepartment of Internal medicine, Koga General Hospital, Miyazaki.
Takanori ToyamaDepartment of Internal medicine, Miyazaki Prefectural Nobeoka Hospital, Miyazaki.
Kouichi MaedaNational Hospital Organization Miyakonojo Medical center, Miyazaki.
Kosuke MarutsukaDepartment of Anatomic Pathology, Miyazaki Prefectural Miyazaki Hospital, Miyazaki.
Yoshitaka ImaizumiDepartment of Hematology, Atomic Bomb Disease and Hibakusha Medicine Unit, Atomic Bomb Disease Institute, Nagasaki University, Nagasaki.
Koji KatoDepartment of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka.
Takeshi SugioDepartment of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka.
Masahito TokunagaDepartment of Hematology, Imamura General Hospital, Kagoshima.
Yukie TashiroDepartment of Pathology, Imamura General Hospital, Kagoshima.
Akifumi Takaori-KondoDepartment of Hematology and Oncology, Graduate School of Medicine, Kyoto University, Kyoto.
Yasushi MiyazakiDepartment of Hematology, Atomic Bomb Disease and Hibakusha Medicine Unit, Atomic Bomb Disease Institute, Nagasaki University, Nagasaki.
Koichi AkashiDepartment of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka.
Kenji IshitsukaDepartment of Hematology and Rheumatology, Kagoshima University Hospital, Kagoshima.
Masao MatsuokaDepartment of Hematology, Rheumatology and Infectious Diseases, Faculty of Life Sciences, Kumamoto University of Medicine, Kumamoto.
Koichi OhshimaDepartment of Pathology, Kurume University School of Medicine, Kurume.
Toshiki WatanabeDepartment of Practical Management of Medical Information, St Marianna University, Graduate School of Medicine, Tokyo.
Akira KitanakaDepartment of Laboratory Medicine, Kawasaki Medical School, Kurashiki.
Atae UtsunomiyaDepartment of Hematology, Imamura General Hospital, Kagoshima.
Seishi OgawaDepartment of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto.
Kazuya ShimodaDivision of Hematology, Diabetes, and Endocrinology, Department of Internal Medicine, Faculty of Medicine, University of Miyazaki, Miyazaki. kshimoda@med.miyazaki-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prognosis of aggressive adult T-cell leukemia/lymphoma (ATL) is poor, and allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative treatment. In order to identify favorable prognostic patients after intensive chemotherapy, and who therefore might not require upfront allo-HSCT, we aimed to improve risk stratification of aggressive ATL patients aged <70 years. The clinical risk factors and genetic mutations were incorporated into risk modeling for overall survival (OS). We generated the m7-ATLPI, a clinicogenetic risk model for OS, that included the ATL prognostic index (PI) (ATL-PI) risk category, and non-silent mutations in seven genes, namely TP53, IRF4, RHOA, PRKCB, CARD11, CCR7, and GATA3. In the training cohort of 99 patients, the m7-ATLPI identified a low-, intermediate-, and highrisk group with 2-year OS of 100%, 43%, and 19%, respectively (hazard ratio [HR] =5.46; P<0.0001). The m7-ATLPI achieved superior risk stratification compared to the current ATL-PI (C-index 0.92 vs. 0.85, respectively). In the validation cohort of 84 patients, the m7-ATLPI defined low-, intermediate-, and high-risk groups with a 2-year OS of 81%, 30%, and 0%, respectively (HR=2.33; P=0.0094), and the model again outperformed the ATL-PI (C-index 0.72 vs. 0.70, respectively). The simplified m7-ATLPI, which is easier to use in clinical practice, achieved superior risk stratification compared to the ATLPI, as did the original m7-ATLPI; the simplified version was calculated by summing the following: high-risk ATL-PI category (+10), low-risk ATL-PI category (-4), and non-silent mutations in TP53 (+4), IRF4 (+3), RHOA (+1), PRKCB (+1), CARD11 (+0.5), CCR7 (-2), and GATA3 (-3).

Indexed as

Hematopoietic Stem Cell TransplantationLeukemia-Lymphoma, Adult T-CellLymphomaAdultHumansPrognosisReceptors, CCR7Retrospective StudiesReceptors, CCR7

Identifiers

PMID36794502
PMCPMC10388278

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