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.
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.
Authors: E R van Wering; B E van der Linden-Schrever; T Szczepański; M J Willemse; E A Baars; H M van Wijngaarde-Schmitz; W A Kamps; J J van Dongen Journal: Br J Haematol Date: 2000-07 Impact factor: 6.998
Authors: Martin Schrappe; Maria Grazia Valsecchi; Claus R Bartram; André Schrauder; Renate Panzer-Grümayer; Anja Möricke; Rosanna Parasole; Martin Zimmermann; Michael Dworzak; Barbara Buldini; Alfred Reiter; Giuseppe Basso; Thomas Klingebiel; Chiara Messina; Richard Ratei; Giovanni Cazzaniga; Rolf Koehler; Franco Locatelli; Beat W Schäfer; Maurizio Aricò; Karl Welte; Jacques J M van Dongen; Helmut Gadner; Andrea Biondi; Valentino Conter Journal: Blood Date: 2011-06-30 Impact factor: 22.113
Authors: C Eckert; A Biondi; K Seeger; G Cazzaniga; R Hartmann; B Beyermann; M Pogodda; J Proba; G Henze Journal: Lancet Date: 2001-10-13 Impact factor: 79.321
Authors: Michael N Dworzak; Gertraud Fröschl; Dieter Printz; Georg Mann; Ulrike Pötschger; Nora Mühlegger; Gerhard Fritsch; Helmut Gadner Journal: Blood Date: 2002-03-15 Impact factor: 22.113
Authors: P Bader; J Hancock; H Kreyenberg; N J Goulden; D Niethammer; A Oakhill; C G Steward; R Handgretinger; J F Beck; T Klingebiel Journal: Leukemia Date: 2002-09 Impact factor: 11.528
Authors: Elaine Coustan-Smith; Jose Sancho; Frederick G Behm; Michael L Hancock; Bassem I Razzouk; Raul C Ribeiro; Gaston K Rivera; Jeffrey E Rubnitz; John T Sandlund; Ching-Hon Pui; Dario Campana Journal: Blood Date: 2002-07-01 Impact factor: 22.113
Authors: Leonid Karawajew; Michael Dworzak; Richard Ratei; Peter Rhein; Giuseppe Gaipa; Barbara Buldini; Giuseppe Basso; Ondrej Hrusak; Wolf-Dieter Ludwig; Günter Henze; Karl Seeger; Arend von Stackelberg; Ester Mejstrikova; Cornelia Eckert Journal: Haematologica Date: 2015-05-22 Impact factor: 9.941
Authors: Olga Sala Torra; Megan Othus; David W Williamson; Brent Wood; Ilan Kirsch; Harlan Robins; Lan Beppu; Margaret R O'Donnell; Stephen J Forman; Frederick R Appelbaum; Jerald P Radich Journal: Biol Blood Marrow Transplant Date: 2017-01-03 Impact factor: 5.742