联合社会人口学因素及临床因素预测初发慢性髓性白血病慢性期患者治疗反应及结局

OBJECTIVE: To explore the impacts of socio-demographic and clinical co-variates on treatment responses and outcomes in patients with chronic myeloid leukemia in the chronic phase (CML-CP) receiving tyrosine kinase inhibitor (TKI) and identified the predictive models for them. METHODS: Data of newly diagnosed adult patients with CML-CP receiving first-line TKI and having complete socio-demographic data and clinical information were reviewed. Cox model was used to identify the independent variables associated with complete cytogenetic response (CCyR), major molecular response (MMR), molecular response 4 (MR(4)) and molecular response 4.5 (MR(4.5)), as well as failure-free survival (FFS), progression-free survival (PFS), overall survival (OS) and CML-related OS. RESULTS: A total of 1414 CML-CP patients treated with first-line imatinib (n＝1176), nilotinib (n＝170) or dasatinib (n＝68) were reviewed. Median age was 40 (18–83) years and 873 patients (61.7％) were males. Result of the multivariate analysis showed that lower educational level (P<0.001−0.070) and EUTOS long-term survival intermediate or high-risk (P<0.001−0.009) were significantly associated with lower cumulative incidences of CCyR, MMR, MR(4) and MR(4.5), as well as the inferior FFS, PFS, OS and CML-related OS. In addition, those who were males, from rural households, had white blood cells (WBC) ≥120×10(9)/L, hemoglobin (HGB) <115 g/L and treated with first-line imatinib had significantly lower cumulative incidences of cytogenetic and/or molecular responses. Being single, divorced or widowed, having, rural household registration, WBC≥120×10(9)/L, HGB<15 g/L, and comorbidity (ies) was significantly associated with inferior FFS, PFS, OS, and/or CML-related OS. Thereafter, the patients were classified into several subgroups using the socio-demographic characteristics and clinical variables by cytogenetic and molecular responses, treatment failure and disease progression, as well as overall survival and CML-related OS, respectively. There were significant differences in treatment responses and outcomes among the subgroups (P<0.001). CONCLUSION: Except for clinical co-variates, socio-demographic co-variates significantly correlated with TKI treatment responses and outcomes in CML-CP patients. Models established by the combination of independent socio-demographic and clinical co-variates could effectively predict the responses and outcome.