Improved prediction of clinical outcome in chronic myeloid leukemia

We sought to develop and compare prognostic models, based on clinical and/or morphometric diagnostic data, to enable better prediction of complete cytogenetic response (CCgR). This prospective longitudinal study included a consecutive series of patients with chronic myeloid leukemia (CML) who were started on imatinib therapy. Logistic regression analysis using backward selection was performed with CCgR at 6, 12, and 18 months as the outcome variables. We evaluated both calibration and discrimination of the model. Internal validation of the model was performed with bootstrapping techniques. A total of 40 patients on imatinib therapy were included in the final analysis. Of these, 25 (62.5 %), 29 (72.5 %), and 32 (80 %), respectively, achieved CCgR at 6, 12, and 18 months after initiation of imatinib. Models included EUTOS score on diagnosis and one of the following morphometric parameters: microvascular density, length of the minor axis, area or circularity of the blood vessel. Models including morphometric parameters and EUTOS score were superior for prediction of CCgR at 6, 12, and 18 months. In particular, the superior models showed better specificity than EUTOS score alone. Using morphometric parameters in conjunction with EUTOS score improves prediction of CCgR. If validated, these models could aid in individual patient risk stratification.