301. Charlson comorbidity index predicts poor outcome in CML patients treated with tyrosine kinase inhibitor.
- Author
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Uemura M, Imataki O, Kawachi Y, Kawakami K, Hoshijima Y, Matsuoka A, and Kadowaki N
- Subjects
- Comorbidity, Female, Humans, Leukemia, Myelogenous, Chronic, BCR-ABL Positive complications, Leukemia, Myelogenous, Chronic, BCR-ABL Positive drug therapy, Leukemia, Myelogenous, Chronic, BCR-ABL Positive mortality, Male, Middle Aged, Protein-Tyrosine Kinases antagonists & inhibitors, Severity of Illness Index, Surveys and Questionnaires, Survival Rate, Treatment Outcome, Leukemia, Myelogenous, Chronic, BCR-ABL Positive diagnosis, Protein Kinase Inhibitors therapeutic use
- Abstract
Although the Sokal and Hasford scoring systems are well-known prognostic models specific to chronic myeloid leukemia (CML), whether they can effectively predict outcomes in elderly CML patients with comorbidities has not been fully elucidated. We evaluated the association between comorbidity at diagnosis with treatment outcome and survival in chronic phase CML patients. A questionnaire was administered to patients diagnosed with CML between 2001 and 2012 and treated with tyrosine kinase inhibitors (TKIs). The Charlson comorbidity index (CCI) was used to determine concomitant diseases. In total, 79 patients (33 females; median age, 57 years) were enrolled. CCI scores at diagnosis were between 2 and 11. At the last follow-up, 46 patients showed a major molecular response. Complete cytogenetic response was achieved in 73.4 % of the cases 12 months after TKI administration. We observed only five deaths during the 55.5-month median follow-up period. The risk categories (low/intermediate/high) associated with Sokal and Hasford scores were 33/27/7 and 21/43/3, respectively. The 27 cases with a CCI score >3 had significantly poorer survival after diagnosis (52 cases had a CCI score <2). CCI scores were inversely associated to overall survival. Concomitant comorbidity at diagnosis is associated with poor outcome in CML patients treated with TKIs.
- Published
- 2016
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