PURPOSE: Molecular diagnostics and early assessment of treatment response that use methodologies capable of detecting submicroscopic disease can distinguish subgroups of patients with leukemia at differing relapse risk. Such information is being incorporated into risk-stratified protocols; however, there are few data concerning prospective use of sequential minimal residual disease (MRD) monitoring to identify more precisely those patients destined to experience relapse, which would allow more tailored therapies. METHODS: Real-time quantitative polymerase chain reaction (RQ-PCR) assays to detect leukemia-specific transcripts (ie, PML-RARA, RARA-PML) were used to prospectively analyze 6,727 serial blood and marrow samples from 406 patients with newly diagnosed acute promyelocytic leukemia (APL) who were receiving all-trans-retinoic acid and anthracycline-based chemotherapy. RESULTS: MRD monitoring according to the recommended schedule successfully identified the majority of patients subject to relapse and provided the most powerful predictor of relapse-free survival (RFS) in multivariable analysis (hazard ratio, 17.87; 95% CI, 6.88 to 46.41; P < .0001); MRD monitoring was far superior to presenting WBC (hazard ratio, 1.02; 95% CI, 1.00 to 1.03; P = .02), which is currently widely used to guide therapy. In patients who were predicted to experience relapse on the basis of MRD monitoring, early treatment intervention with arsenic trioxide prevented progression to overt relapse in the majority, and the RFS rate at 1 year from molecular relapse was 73%. By using this strategy, 3-year cumulative incidence of clinical relapse was only 5% in the Medical Research Council AML15 trial. CONCLUSION: Rigorous sequential RQ-PCR monitoring provides the strongest predictor of RFS in APL and, when coupled with pre-emptive therapy, provides a valid strategy to reduce rates of clinical relapse. This provides a model for development of a more individualized approach to management of other molecularly defined subtypes of acute leukemia.
PURPOSE: Molecular diagnostics and early assessment of treatment response that use methodologies capable of detecting submicroscopic disease can distinguish subgroups of patients with leukemia at differing relapse risk. Such information is being incorporated into risk-stratified protocols; however, there are few data concerning prospective use of sequential minimal residual disease (MRD) monitoring to identify more precisely those patients destined to experience relapse, which would allow more tailored therapies. METHODS: Real-time quantitative polymerase chain reaction (RQ-PCR) assays to detect leukemia-specific transcripts (ie, PML-RARA, RARA-PML) were used to prospectively analyze 6,727 serial blood and marrow samples from 406 patients with newly diagnosed acute promyelocytic leukemia (APL) who were receiving all-trans-retinoic acid and anthracycline-based chemotherapy. RESULTS: MRD monitoring according to the recommended schedule successfully identified the majority of patients subject to relapse and provided the most powerful predictor of relapse-free survival (RFS) in multivariable analysis (hazard ratio, 17.87; 95% CI, 6.88 to 46.41; P < .0001); MRD monitoring was far superior to presenting WBC (hazard ratio, 1.02; 95% CI, 1.00 to 1.03; P = .02), which is currently widely used to guide therapy. In patients who were predicted to experience relapse on the basis of MRD monitoring, early treatment intervention with arsenic trioxide prevented progression to overt relapse in the majority, and the RFS rate at 1 year from molecular relapse was 73%. By using this strategy, 3-year cumulative incidence of clinical relapse was only 5% in the Medical Research Council AML15 trial. CONCLUSION: Rigorous sequential RQ-PCR monitoring provides the strongest predictor of RFS in APL and, when coupled with pre-emptive therapy, provides a valid strategy to reduce rates of clinical relapse. This provides a model for development of a more individualized approach to management of other molecularly defined subtypes of acute leukemia.
Authors: Roland B Walter; Frederick R Appelbaum; Martin S Tallman; Noel S Weiss; Richard A Larson; Elihu H Estey Journal: Blood Date: 2010-06-10 Impact factor: 22.113
Authors: Frank S Ong; Kingshuk Das; Jay Wang; Hana Vakil; Jane Z Kuo; Wendell-Lamar B Blackwell; Stephen W Lim; Mark O Goodarzi; Kenneth E Bernstein; Jerome I Rotter; Wayne W Grody Journal: Expert Rev Mol Diagn Date: 2012-07 Impact factor: 5.225