Predicting non-relapse mortality following allogeneic hematopoietic cell transplantation during first remission of acute myeloid leukemia View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2020-08-14

AUTHORS

Masamitsu Yanada, Takaaki Konuma, Shohei Mizuno, Masuho Saburi, Akihito Shinohara, Masatsugu Tanaka, Atsushi Marumo, Masashi Sawa, Naoyuki Uchida, Yukiyasu Ozawa, Makoto Onizuka, Satoshi Yoshioka, Hirohisa Nakamae, Tadakazu Kondo, Takafumi Kimura, Junya Kanda, Takahiro Fukuda, Yoshiko Atsuta, Hideki Nakasone, Shingo Yano

ABSTRACT

The aim of this study was to develop a comprehensive system for predicting non-relapse mortality after allogeneic hematopoietic cell transplantation (HCT) during first complete remission (CR) of acute myeloid leukemia (AML). After dividing 2344 eligible patients randomly into a training set and a validation set, we first identified and scored five parameters, that is, age, sex, performance status, HCT-comorbidity index (HCT-CI), and donor type, on the basis of their impact on non-relapse mortality for patients in the training set. The non-relapse mortality-J (NRM-J) index using the sum of these scores was then applied to patients in the validation set, resulting in a clear differentiation of non-relapse mortality, with expected 2-year rates of 11%, 16%, 27%, and 33%, respectively (P < 0.001). The estimated c-statistic was 0.67, which was significantly higher than that of the European Society for Blood and Marrow Transplantation score (0.60, P = 0.002) and the HCT-CI (0.57, P < 0.001). The NRM-J index showed a significant association with overall survival, but not with relapse. Our findings demonstrate that the NRM-J index is useful for predicting post-transplant non-relapse mortality for patients with AML in first CR, for whom the decision of whether to perform allogeneic HCT is critical. More... »

PAGES

387-394

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41409-020-01032-9

    DOI

    http://dx.doi.org/10.1038/s41409-020-01032-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1130099020

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/32796950


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