BACKGROUND: Currently used treatment response criteria in multiple myeloma (MM) are based in part on serum monoclonal protein (M-protein) measurements. A drawback of these criteria is that response is determined solely by the best level of M-protein reduction, without considering the serial trend. The authors hypothesized that metrics incorporating the serial trend of M-protein would be better predictors of progression-free survival (PFS). METHODS: Fifty-five patients with measurable disease at baseline (M-protein > or = 1 g/dL) who received > or = 4 cycles of treatment from 2 clinical trials in previously untreated MM were included. Three metrics based on the percentage of M-protein remaining relative to baseline (residual M-protein) were considered: metrics based on the number of times residual M-protein fell within prespecified thresholds, metrics based on area under the residual M-protein curve, and metrics based on the average residual M-protein reduction between Cycles 1 and 4. The predictive value of these metrics was assessed in Cox models using landmark analysis. RESULTS: The average residual M-protein reduction was found to be significantly predictive of PFS (P = .02; hazard ratio, 0.37), in which a patient with a 10% lower average residual M-protein reduction from Cycle 1 to 4 was estimated to be at least 2.7x more likely to develop disease progression or die early. None of the other metrics was predictive of PFS. The concordance index for the average residual M-protein reduction was 0.63, compared with 0.56 for best response. CONCLUSIONS: The average residual M-protein reduction metric is promising and needs further validation. This exploratory analysis is the first step in the search for treatment-based trend metrics predictive of outcomes in MM. Copyright 2009 American Cancer Society.
BACKGROUND: Currently used treatment response criteria in multiple myeloma (MM) are based in part on serum monoclonal protein (M-protein) measurements. A drawback of these criteria is that response is determined solely by the best level of M-protein reduction, without considering the serial trend. The authors hypothesized that metrics incorporating the serial trend of M-protein would be better predictors of progression-free survival (PFS). METHODS: Fifty-five patients with measurable disease at baseline (M-protein > or = 1 g/dL) who received > or = 4 cycles of treatment from 2 clinical trials in previously untreated MM were included. Three metrics based on the percentage of M-protein remaining relative to baseline (residual M-protein) were considered: metrics based on the number of times residual M-protein fell within prespecified thresholds, metrics based on area under the residual M-protein curve, and metrics based on the average residual M-protein reduction between Cycles 1 and 4. The predictive value of these metrics was assessed in Cox models using landmark analysis. RESULTS: The average residual M-protein reduction was found to be significantly predictive of PFS (P = .02; hazard ratio, 0.37), in which a patient with a 10% lower average residual M-protein reduction from Cycle 1 to 4 was estimated to be at least 2.7x more likely to develop disease progression or die early. None of the other metrics was predictive of PFS. The concordance index for the average residual M-protein reduction was 0.63, compared with 0.56 for best response. CONCLUSIONS: The average residual M-protein reduction metric is promising and needs further validation. This exploratory analysis is the first step in the search for treatment-based trend metrics predictive of outcomes in MM. Copyright 2009 American Cancer Society.
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Authors: Jerry A Katzmann; Raynell J Clark; Roshini S Abraham; Sandra Bryant; James F Lymp; Arthur R Bradwell; Robert A Kyle Journal: Clin Chem Date: 2002-09 Impact factor: 8.327