Social Parameters Are Independent Predictors for Survival in Chronic Myeloid Leukemia

Introduction and data: Social and demographic personal data are important to be included in analysis and interpretation of results of any population studies in oncology. But it looks like social status is underestimated as cofounder for survival of patients with chronic myeloid leukemia (CML). The aim of this study was to check the prognostic value of social parameters like marital status and education level in comparison with standard risk factors. Russian CML Registry include more than 10 thousand patients (pts) data. In the analysis 8326 CML pts in chronic phase (CP) with first line TKI therapy were included: 91% of pts were treated by Imatinib and 9% by other TKIs. Mean age was 49years, 4607 f/ 3705 m. Me of follow-up-4.24years. Overall survival(OS) was estimated starting the diagnosis date, event was death from any reason, date of last contact was censored for alive pts. Survival analysis was performed by SAS procedures. Results:Firstly, we perform one-way survival analysis and estimate OS depending upon the 3 parameters Sokal Score, Marital Status and Education. There are high significant dependences OS on all three factors as shown on picture 1 (OS estimates depending on values of: 1A) Sokal score (low, intermediate, high), 1B) Marital Status (married, single, widowed/divorced), 1C) Education (low/secondary, higher). Marital Status and Education are correlated with Sokal Score (corresponding Pearson's coefficients are 0.19 and 0.12, p<0.0001). This association is caused by age but is not so strong. Than we have estimate OS in each Sokal's risk groups (picture 2. OS estimates depending on Marital Status (single, married - blue line, widowed/divorced - green line) in different Sokal's risk groups: 2A) - low, 2B) - intermediate, 2C) - high). OS estimates depending on Education (picture 3; (low/secondary red line, higher- blue line) in different Sokal's risk groups: 3A) low, 3B) intermediate, 3C) high. And we see that Marital Status and Education are predictive in each risk group but the most influent in high risk group. Marital Status and Education are correlated with other impotent cofounder- age. It should be checked in additional multi factor analysis we plan to do. We also run the proportional risk regression Cox's model on this data. Hazard ratio (HR) and significance (Px²) for included parameters are following: Sokal score - HR=1.59, Px²<0.0001; Education- HR=1.76, Px²<0.0001; Marital Status- HR=1.40, Px²<0.0006. Conclusions: The social and demographic personal data should be included in any analysis of CML population data. Marital Status and Educationare obviously associated with adherence behavior of CML patients and must influent on longitude therapy output. The highly education level is favorable factor, widowed/divorced marital status is unfavorable factor for OS prognosis.

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