Abstract
Cytogenetic abnormalities are currently the most important predictors of response and clinical outcome for patients with acute myeloid leukemia (AML) or advanced-stage myelodysplastic syndrome (MDS). However, clinical outcomes of patients in each cytogenetic subgroup are very heterogeneous, and additional biological markers are needed to improve disease management. Most of the recently reported biomarkers, especially in patients with normal karyotypes, provide marginal value for predicting behavior or require significant and technically difficult procedures, such as gene expression profiling. We assessed the utility of measuring proteasome chymotrypsin-like (Ch-L) activity in plasma, using fluorogenic kinetic assays, to predict response and overall survival of patients with AML (N=174) and advanced-stage MDS (N=52); results from AML and MDS patients were pooled for all analyses after demonstrating similar findings. In a univariate logistic regression model, significant predictors of response were age group (< vs ≥70 years; odds ratio [OR]=1.92; 95% confidence interval [CI]=1.06, 3.48), cytogenetics (OR=2.20; 95% CI=1.28, 3.78), BUN as a continuous variable (OR=1.04, 95% CI=1.01, 1.07), and Ch-L activity as a continuous variable (OR=1.41, 95% CI=1.14, 1.76) (all P<0.01). Ch-L activity as continuous variable, cytogenetics, and age group remained independent predictors of response in a multivariate logistic regression model. A univariate Cox regression model identified the following as predictors of overall survival: cytogenetics (hazard ratio [HR]=2.30, 95% CI=1.70, 3.13), beta-2 microglobulin as a continuous variable (HR=1.07, 95% CI=1.04, 1.10), age (< vs ≥70 years; HR=1.92, 95% CI=1.51, 2.89), performance status (HR=1.65, 95% CI=1.51, 3.03), BUN as a continuous variable (HR=1.04, 95% CI=1.03, 1.06), and Ch-L activity as a continuous variable (HR=1.41, 95% CI=1.11, 1.33) (all P<0.01). However, in multivariate Cox regression models only cytogenetics, age, performance status, and BUN and Ch-L activity as continuous variables were independent predictors of overall survival; these factors were also independent predictors of event-free survival. In patients with normal karyotype (N=83), Ch-L activity as a continuous variable was a strong predictor of survival (P<0.001), independent of age grouping, performance status, and BUN. In conclusion, these findings indicate that measuring plasma Ch-L activity provides a powerful biomarker for predicting clinical behavior in patients with AML and advanced-stage MDS. Although dichotomizing patients using cut-off points for Ch-L activity demonstrated significant survival differences between groups (not shown), Ch-L as a continuous variable was a more powerful predictor and could be incorporated into a nomogram-based model to stratify AML and advanced-stage MDS patients for potential new therapeutic approaches. Further studies are needed to confirm the clinical value of such a nomogram.
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