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Prognostic value of low-level MRD in adult acute lymphoblastic leukemia detected by low- and high-throughput methods

Michaela Kotrová, Johannes Koopmann, Heiko Trautmann, Nael Alakel, Joachim Beck, Kathrin Nachtkamp, Björn Steffen, Simon Raffel, Andreas Viardot, Klaus Wethmar, Nikos Darzentas, Claudia D. Baldus, Nicola Gökbuget, Monika Brüggemann

2022Blood Advances39 citationsDOIOpen Access PDF

Abstract

Persistence of minimal residual disease (MRD) after induction/consolidation therapy in acute lymphoblastic leukemia is the leading cause of relapse. The GMALL 07/2003 study used MRD detection by real-time quantitative polymerase chain reaction of clonal immune gene rearrangements with 1 × 10-4 as discriminating cutoff: levels ≥1 × 10-4 define molecular failure and MRD-negativity with an assay sensitivity of at least 1 × 10-4 defining complete molecular response. The clinical relevance of MRD results not fitting into these categories is unclear and termed "molecular not evaluable" (MolNE) toward MRD-based treatment decisions. Within the GMALL 07/03 study, 1019 consecutive bone marrow samples after first consolidation were evaluated for MRD. Patients with complete molecular response had significantly better outcome (5-year overall survival [OS] = 85% ± 2%, n = 603; 5-year disease-free survival [DFS] = 73% ± 2%, n = 599) compared with patients with molecular failure (5-year OS = 40% ± 3%, n = 238; 5-year DFS = 29% ± 3%, n = 208), with patients with MolNE in between (5-year OS = 66% ± 4%; 5-year DFS = 52% ± 4%, n = 178). Of MolNE samples reanalyzed using next-generation sequencing (NGS), patients with undetectable NGS-MRD (n = 44; 5-year OS = 88% ± 5%, 5-year DFS = 70% ± 7%) had significantly better outcome than those with positive NGS-MRD (n = 42; 5-year OS = 37% ± 8%; 5-year DFS = 33% ± 8%). MolNE MRD results not just are borderline values with questionable relevance but also form an intermediate-risk group, assignment of which can be further improved by NGS.

Topics & Concepts

Lymphoblastic LeukemiaValue (mathematics)OncologyMedicineThroughputInternal medicineLeukemiaCancer researchComputer scienceMachine learningTelecommunicationsWirelessAcute Lymphoblastic Leukemia researchLymphoma Diagnosis and TreatmentAcute Myeloid Leukemia Research