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Blood: An individualized method that guides AML patients when to perform hematopoietic stem cell transplants.

 Last Update: 2020-10-03
 Source: Internet
 Author: User

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Recently, a multi-stage model (Knowledge Base (KB) algorithm) guided by a large data set was developed to improve AML prognosis and tailor treatment decisions, including hematopoietic stem cell transplantation (HSCT).
the study, researchers evaluated the performance of KB guidance in HSCT during the first complete remission phase (CR1) in 656 AML patients under the age of 60 in the ALFA-0702 trial.
KB's forecast for total survival rate (OS) is better than ELN's 2017 risk stratosity forecast (C Index 68.9 vs 63.0).
patients who received CR1, HSCT was used as a time-dependent covariative variable in patients with better risk stratition and NPM1 MRD-negative ELN2017.
The researchers found in a similar time-dependent analysis that there was a significant interaction between KB scores and HSCT, and that HSCT in CR1 was harmful only in patients with a good prognosis based on KB simulation.
, the researchers consolidated ELN 2017, NPM1 MRD and KB scores, spliting 545 CR1 patients into 278 (51.0%) HSCT candidates and 267 (49.0%) single chemotherapy candidates.
in time dependence and six-month milestone analysis, HSCT can significantly improve the OS of HSCT candidates, although it can also significantly shorten the OS of pure chemotherapy candidates.
, combining KB prediction with ELN 2017 and MRD may be an effective way to optimize HSCT timing in young AML patients.
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