Time point-dependent concordance of flow cytometry and real-time quantitative polymerase chain reaction for minimal residual disease detection in childhood acute lymphoblastic leukemia
- PMID: 22581001
- PMCID: PMC3487561
- DOI: 10.3324/haematol.2011.060426
Time point-dependent concordance of flow cytometry and real-time quantitative polymerase chain reaction for minimal residual disease detection in childhood acute lymphoblastic leukemia
Abstract
Background: Flow cytometric analysis of leukemia-associated immunophenotypes and polymerase chain reaction-based amplification of antigen-receptor genes rearrangements are reliable methods for monitoring minimal residual disease. The aim of this study was to compare the performances of these two methodologies in the detection of minimal residual disease in childhood acute lymphoblastic leukemia.
Design and methods: Polymerase chain reaction and flow cytometry were simultaneously applied for prospective minimal residual disease measurements at days 15, 33 and 78 of induction therapy on 3565 samples from 1547 children with acute lymphoblastic leukemia enrolled into the AIEOP-BFM ALL 2000 trial.
Results: The overall concordance was 80%, but different results were observed according to the time point. Most discordances were found at day 33 (concordance rate 70%) in samples that had significantly lower minimal residual disease. However, the discordance was not due to different starting materials (total versus mononucleated cells), but rather to cell input number. At day 33, cases with minimal residual disease below or above the 0.01% cut-off by both methods showed a very good outcome (5-year event-free survival, 91.6%) or a poor one (5-year event-free survival, 50.9%), respectively, whereas discordant cases showed similar event-free survival rates (around 80%).
Conclusions: Within the current BFM-based protocols, flow cytometry and polymerase chain reaction cannot simply substitute each other at single time points, and the concordance rates between their results depend largely on the time at which they are used. Our findings suggest a potential complementary role of the two technologies in optimizing risk stratification in future clinical trials.
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