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Patient-specific molecular response dynamics can predict the possibility of relapse during the second treatment-free remission attempt in chronic myelogenous leukemia

Authors :
Eunjung Kim
Eo-Jin Hwang
Junghye Lee
Dae-Young Kim
Jae-Young Kim
Dong-Wook Kim
Source :
Neoplasia: An International Journal for Oncology Research, Vol 32, Iss , Pp 100817- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

In chronic myelogenous leukemia (CML), treatment-free remission (TFR) is defined as maintaining a major molecular response (MMR) without a tyrosine kinase inhibitor (TKI), such as imatinib (IM). Several studies have investigated the safety of the first TFR (TFR1) attempt and suggested recommendation guidelines for such an attempt. However, the plausibility and predictive factors for a second TFR (TFR2) have yet to be reported.The present study included 21 patients in chronic myeloid leukemia who participated in twice repeated treatment stop attempts. We develop a mathematical model to analyze and explain the outcomes of TFR2. Our mathematical model framework can explain patient-specific molecular response dynamics. Fitting the model to longitudinal BCR-ABL1 transcripts from the patients generated patient-specific parameters. Binary tree decision analyses of the model parameters suggested a model based predictive binary classification factor that separated patients into low- and high-risk groups of TFR2 attempts with an overall accuracy of 76.2% (sensitivity of 81.1% and specificity of 69.9%). The low-risk group maintained a median TFR2 of 28.2 months, while the high-risk group relapsed at a median time of 3.25 months. Further, our model predicted a patient-specific optimal IM treatment duration before the second IM stop that could achieve the desired TFR2 (e.g., 5 years).

Details

Language :
English
ISSN :
14765586
Volume :
32
Issue :
100817-
Database :
Directory of Open Access Journals
Journal :
Neoplasia: An International Journal for Oncology Research
Publication Type :
Academic Journal
Accession number :
edsdoj.221332d0f7d34244800339484540badb
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neo.2022.100817