Abstract
Abstract 992
Poster Board I-14
Background:
Acute myeloid leukemia (AML) is a common disease in individuals ≥ 65 years old. Overall survival (OS) is significantly shorter in older patients compared with younger patients. Many patients do not receive chemotherapy due to age or co-morbidities. The aim of our study is to investigate the biologic characteristics of AML in the elderly using variables on survival.
Methods:
For this single-center, retrospective study, authors analyzed the following variables for the outcome patients ≥ 65 years old: age at diagnosis, gender, WBC, HGB, LDH, % blasts, risk factors, chemotherapy, co-morbidities, cytogenetics, and documented MDS/cancer.
Statistical Analysis:
All variables were summarized using descriptive statistics: mean (SD) for continuous variables and frequency (percent) for categorical variables. Kaplan-Meier survival curves were obtained, and univariate Cox proportional hazards models and multivariate Cox proportional hazards models were applied. A p-value of less than 0.05 indicated a statistical significance. SAS 9.1.3 (SAS Institute INC, Cary, NC) was used for data management and statistical analysis.
Results:
Seventy-four patients 65 or older were included for the analysis by Kaplan – Meier survival. The median survival time was 3.8 months. Seventy patients have died and 4 have survived until 1/2009. Patients over 80 years old had the worst survival, 0.7 month, compare to age 65 – 70 group which was 4 months and 71 – 80 group which was 4.6 months. Results with univariate Cox proportional hazards model shows WBC group (p=0.0390), LDH group (p=0.0153), and chemotherapy (p<0.0001) were significant variables on survival. LDH group and cytogenetics were not included in the multivariate model due to many missing measurements (43%; 32 out of 74) and (27%; 17 out of 74), respectively. Final multivariate model including all significant variables revealed significant effect of WBC group (p=0.0074) and chemotherapy (p<0.0001) on survival.
Discussion and Conclusions:
Prior results from clinical trials and single-center studies evaluating the prognostic factors in older patients are conflicting. In our study, patients who received chemotherapy (standard or intensive chemotherapy) had better survival (median 5.2 months) compare to untreated patients with median survival 0.4 months (p<0.0001). The tendency is to exclude elderly patients for the treatment because of poor performance status (PS), organ dysfunction, and co-morbid conditions. The approach to withhold chemotherapy in elderly patients is not supported by our results. To the contrary, it appears that chemotherapy should be pursued and may offer longer survival except for elderly patients over the age of 80. High WBC ' 10 × 103 /μL at presentation had an adverse impact on survival rates (p=0.034). Other studies have shown mixed results in regards to survival. LDH > 300 U/L was an adverse prognostic factor for survival. A higher leukocyte count probably is representative of high tumor burden and more aggressive disease biology. Cytogenetics (with MDS and without MDS) at diagnosis was not predictive of survival but our cytogenetic evaluation was incomplete due to missing data. Co-morbidities such as cardiovascular disease, diabetes, hepatic disease, pulmonary disease, and cancer did not impact on the survival. We observed adverse impact of increasing age on survival only in patients over 80. Some investigators reported no effects, and others showed increasing age as a poor prognostic factor for both CR and survival or survival alone. The cause of this discrepancy is not clear. Patients > 80 years comprise 28% of our study group and exhibited the worst survival time; they may represent a different patient population with distinct biological features. We conclude that age, biological features, chemotherapy and leukocyte count are the most important determinants of survival.
Disclosures:
No relevant conflicts of interest to declare.
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