Hanfstein, B.; Shlyakhto, V.; Lauseker, Michael; Hehlmann, R.; Saussele, S.; Dietz, C. T.; Erben, P.; Fabarius, A.; Proetel, U.; Schnittger, S.; Krause, S. W.; Schubert, J.; Einsele, H.; Hänel, M.; Dengler, J.; Falge, C.; Kanz, L.; Neubauer, A.; Kneba, M.; Stegelmann, F.; Pfreundschuh, M.; Waller, C. F.; Spiekermann, K.; Baerlocher, G. M.; Pfirrmann, Markus; Hasford, Joerg; Hofmann, W. K.; Hochhaus, A.; Muller, M. C. (October 2014): Velocity of early BCR-ABL transcript elimination as an optimized predictor of outcome in chronic myeloid leukemia (CML) patients in chronic phase on treatment with imatinib. In: Leukemia, Vol. 28, No. 10: pp. 1988-1992 |
Abstract
Early assessment of response at 3 months of tyrosine kinase inhibitor treatment has become an important tool to predict favorable outcome. We sought to investigate the impact of relative changes of BCR-ABL transcript levels within the initial 3 months of therapy. In order to achieve accurate data for high BCR-ABL levels at diagnosis, beta glucuronidase (GUS) was used as a reference gene. Within the German CML-Study IV, samples of 408 imatinib-treated patients were available in a single laboratory for both times, diagnosis and 3 months on treatment. In total, 301 of these were treatment-naïve at sample collection. RESULTS: (i) with regard to absolute transcript levels at diagnosis, no predictive cutoff could be identified; (ii) at 3 months, an individual reduction of BCR-ABL transcripts to the 0.35-fold of baseline level (0.46-log reduction, that is, roughly half-log) separated best (high risk: 16% of patients, 5-year overall survival (OS) 83% vs 98%, hazard ratio (HR) 6.3, P=0.001); (iii) at 3 months, a 6% BCR-ABL(IS) cutoff derived from BCR-ABL/GUS yielded a good and sensitive discrimination (high risk: 22% of patients, 5-year OS 85% vs 98%, HR 6.1, P=0.002). Patients at risk of disease progression can be identified precisely by the lack of a half-log reduction of BCR-ABL transcripts at 3 months.
Item Type: | Journal article |
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Faculties: | Medicine > Institute for Medical Information Processing, Biometry and Epidemiology |
Subjects: | 600 Technology > 610 Medicine and health |
ISSN: | 0887-6924 |
Language: | English |
ID Code: | 39904 |
Deposited On: | 19. Jul 2017 06:38 |
Last Modified: | 04. Nov 2020 13:16 |
- BASE
- Hanfstein, B.
- Shlyakhto, V.
- Lauseker, Michael
- Hehlmann, R.
- Saussele, S.
- Dietz, C. T.
- Erben, P.
- Fabarius, A.
- Proetel, U.
- Schnittger, S.
- Krause, S. W.
- Schubert, J.
- Einsele, H.
- Hänel, M.
- Dengler, J.
- Falge, C.
- Kanz, L.
- Neubauer, A.
- Kneba, M.
- Stegelmann, F.
- Pfreundschuh, M.
- Waller, C. F.
- Spiekermann, K.
- Baerlocher, G. M.
- Pfirrmann, Markus
- Hasford, Joerg
- Hofmann, W. K.
- Hochhaus, A.
- Muller, M. C.
- Google Scholar
- Hanfstein, B.
- Shlyakhto, V.
- Lauseker, Michael
- Hehlmann, R.
- Saussele, S.
- Dietz, C. T.
- Erben, P.
- Fabarius, A.
- Proetel, U.
- Schnittger, S.
- Krause, S. W.
- Schubert, J.
- Einsele, H.
- Hänel, M.
- Dengler, J.
- Falge, C.
- Kanz, L.
- Neubauer, A.
- Kneba, M.
- Stegelmann, F.
- Pfreundschuh, M.
- Waller, C. F.
- Spiekermann, K.
- Baerlocher, G. M.
- Pfirrmann, Markus
- Hasford, Joerg
- Hofmann, W. K.
- Hochhaus, A.
- Muller, M. C.