Claudia Lanvers-Kaminsky1, Andrea Rüffer1, Gudrun Würthwein1, Joachim Gerss2, Massimo Zucchetti3, Andrea Ballerini4, Andishe Attarbaschi5,6, Petr Smisek7, Christa Nath8,9, Samiuela Lee8,9, Sara Elitzur10,11, Martin Zimmermann12, Anja Möricke13, Martin Schrappe13, Carmelo Rizzari14, Joachim Boos1. 1. Department of Pediatric Hematology and Oncology, University Children's Hospital of Muenster. 2. Institute of Biostatistics and Clinical Research, University of Muenster, Muenster, Germany. 3. Laboratory of Cancer Pharmacology, Department of Oncology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri. 4. Department of Oncology and Onco-Hematology, University of Milan, Milan, Italy. 5. Department of Pediatric Hematology and Oncology, St. Anna Children's Hospital. 6. Department of Pediatrics and Adolescent Medicine, Medical University, Vienna, Germany. 7. Department of Pediatric Hematology and Oncology, University Hospital Motol, Praha, Czech Republic. 8. Department of Biochemistry and Oncology, The Children's Hospital at Westmead. 9. Faculty of Pharmacy, University of Sydney, Sydney, Australia. 10. Pediatric Hematology-Oncology, Schneider Children's Medical Center, Petah-Tikva. 11. Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. 12. Department of Paediatric Haematology and Oncology, Hannover Medical School, Hannover. 13. Klinik für Allgemeine Pädiatrie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Kiel, Germany. 14. Clinica Pediatrica, Ospedale S. Gerardo, Università di Milano-Bicocca, Monza, Italy.
Abstract
BACKGROUND: In the international AIEOP-BFM ALL 2009 trial, asparaginase (ASE) activity was monitored after each dose of pegylated Escherichia coli ASE (PEG-ASE). Two methods were used: the aspartic acid β-hydroxamate (AHA) test and medac asparaginase activity test (MAAT). As the latter method overestimates PEG-ASE activity because it calibrates using E. coli ASE, method comparison was performed using samples from the AIEOP-BFM ALL 2009 trial. METHODS: PEG-ASE activities were determined using MAAT and AHA test in 2 sets of samples (first set: 630 samples and second set: 91 samples). Bland-Altman analysis was performed on ratios between MAAT and AHA tests. The mean difference between both methods, limits of agreement, and 95% confidence intervals were calculated and compared for all samples and samples grouped according to the calibration ranges of the MAAT and the AHA test. RESULTS: PEG-ASE activity determined using the MAAT was significantly higher than when determined using the AHA test (P < 0.001; Wilcoxon signed-rank test). Within the calibration range of the MAAT (30-600 U/L), PEG-ASE activities determined using the MAAT were on average 23% higher than PEG-ASE activities determined using the AHA test. This complies with the mean difference reported in the MAAT manual. With PEG-ASE activities >600 U/L, the discrepancies between MAAT and AHA test increased. Above the calibration range of the MAAT (>600 U/L) and the AHA test (>1000 U/L), a mean difference of 42% was determined. Because more than 70% of samples had PEG-ASE activities >600 U/L and required additional sample dilution, an overall mean difference of 37% was calculated for all samples (37% for the first and 34% for the second set). CONCLUSIONS: Comparison of the MAAT and AHA test for PEG-ASE activity confirmed a mean difference of 23% between MAAT and AHA test for PEG-ASE activities between 30 and 600 U/L. The discrepancy increased in samples with >600 U/L PEG-ASE activity, which will be especially relevant when evaluating high PEG-ASE activities in relation to toxicity, efficacy, and population pharmacokinetics.
BACKGROUND: In the international AIEOP-BFM ALL 2009 trial, asparaginase (ASE) activity was monitored after each dose of pegylated Escherichia coli ASE (PEG-ASE). Two methods were used: the aspartic acid β-hydroxamate (AHA) test and medac asparaginase activity test (MAAT). As the latter method overestimates PEG-ASE activity because it calibrates using E. coli ASE, method comparison was performed using samples from the AIEOP-BFM ALL 2009 trial. METHODS:PEG-ASE activities were determined using MAAT and AHA test in 2 sets of samples (first set: 630 samples and second set: 91 samples). Bland-Altman analysis was performed on ratios between MAAT and AHA tests. The mean difference between both methods, limits of agreement, and 95% confidence intervals were calculated and compared for all samples and samples grouped according to the calibration ranges of the MAAT and the AHA test. RESULTS:PEG-ASE activity determined using the MAAT was significantly higher than when determined using the AHA test (P < 0.001; Wilcoxon signed-rank test). Within the calibration range of the MAAT (30-600 U/L), PEG-ASE activities determined using the MAAT were on average 23% higher than PEG-ASE activities determined using the AHA test. This complies with the mean difference reported in the MAAT manual. With PEG-ASE activities >600 U/L, the discrepancies between MAAT and AHA test increased. Above the calibration range of the MAAT (>600 U/L) and the AHA test (>1000 U/L), a mean difference of 42% was determined. Because more than 70% of samples had PEG-ASE activities >600 U/L and required additional sample dilution, an overall mean difference of 37% was calculated for all samples (37% for the first and 34% for the second set). CONCLUSIONS: Comparison of the MAAT and AHA test for PEG-ASE activity confirmed a mean difference of 23% between MAAT and AHA test for PEG-ASE activities between 30 and 600 U/L. The discrepancy increased in samples with >600 U/L PEG-ASE activity, which will be especially relevant when evaluating high PEG-ASE activities in relation to toxicity, efficacy, and population pharmacokinetics.
Authors: Micaela M ViÑa-Romero; Ruth Ramos-Diaz; Ivette Mourani-Padron; Hector Gonzalez-Mendez; Macarena Gonzalez-Cruz; Gloria Julia Nazco-Casariego; Javier F Merino-Alonso; Jesica Diaz-Vera; Fernando GutiÉrrez-NicolÁs Journal: In Vivo Date: 2020 Sep-Oct Impact factor: 2.155
Authors: Elke Schaeffeler; Simon U Jaeger; Verena Klumpp; Jun J Yang; Svitlana Igel; Laura Hinze; Martin Stanulla; Matthias Schwab Journal: Genet Med Date: 2019-02-07 Impact factor: 8.822
Authors: Carmelo Rizzari; Claudia Lanvers-Kaminsky; Maria Grazia Valsecchi; Andrea Ballerini; Cristina Matteo; Joachim Gerss; Gudrun Wuerthwein; Daniela Silvestri; Antonella Colombini; Valentino Conter; Andrea Biondi; Martin Schrappe; Anja Moericke; Martin Zimmermann; Arend von Stackelberg; Christin Linderkamp; Michael C Frühwald; Sabine Legien; Andishe Attarbaschi; Bettina Reismüller; David Kasper; Petr Smisek; Jan Stary; Luciana Vinti; Elena Barisone; Rosanna Parasole; Concetta Micalizzi; Massimo Zucchetti; Joachim Boos Journal: Haematologica Date: 2019-01-31 Impact factor: 9.941