Outcome Of Acute Leukemia Patients Research Articles

Survival and Predictors of Outcome in Acute Leukemia Patients Admitted to the Intensive Care Unit.

Background: Patients with acute leukemia fare poorly when admitted to intensive care units (ICUs). Predictors of outcome and rates of successful discharge have not been defined in the United States.Methods: This is a retrospective analysis of 78 acute leukemia patients admitted to the medical ICU from 2001–2004. Patients were identified by ICD-9 codes and a sudden increase in daily hospital charges (indicating a direct ICU admission or transfer to the ICU from a medical floor). The primary endpoints were improvement and subsequent ICU discharge with continued aggressive leukemia management and survival to 2 months following hospital discharge. Secondary endpoints included 6 and 12 month survival. Univariate and multivariate logistic regression analyses were performed to identify factors predicting outcome.Results: Sixty-five patients were diagnosed with AML and 13 with ALL. Seven patients had good-risk cytogenetics, 32 intermediate, 30 poor and 9 unknown, as defined by CALGB 8461. Fever or infection (37.2%) was the leading cause of hospital admission. The mean age was 53 years, 85% were Caucasian and 51% were female. The median white blood cell (WBC) count was 6.9K.On average, patients were transferred to the ICU on hospital day 13. Of the 69 patients who received chemotherapy, 29 (42%) were in the induction phase and 40 (58%) in the consolidation or relapsed/refractory phase, with a mean chemotherapy day of 15. The most common reason for transfer to the ICU was respiratory compromise (68%) with sepsis (56%) second. Most patients transferred to the ICU had either 1 (47%) or 2 (45%) reasons for transfer. While in the ICU 57 patients required mechanical ventilation with 21 eventually extubated (19 improved; 2 withdrew care). Hemodynamic support (pressors) was used in 41 patients. The mean length of stay in the ICU was 7 days. The mean APACHE II score was 23 ± 7, predicting a mortality of 40%. Overall, 22 patients (28%) improved and 49 (63%) died in the ICU. Seven patients (9%) died after transfer out of the ICU. Two month survival following hospital discharge was 21%. At 6 and 12 months, 13% and 12% were alive, respectively. In univariate analysis, patients with lower APACHE II scores were more likely to improve in the ICU (p=0.002) and to live 2 months post-discharge (p=0.004) than those with higher scores; these findings remained significant in multivariate analysis. In univariate analysis, patients requiring hemodynamic support had lower 6 and 12 month survival than patients not requiring support (p=0.017 and 0.025); these findings remained significant in multivariate analysis (p=0.007 and 0.013). Multivariate analysis also showed that patients with poor risk cytogenetics had lower 6 and 12 month survival than patients with good or intermediate risk cytogenetics (p=0.026 and 0.05). Neither age, WBC, or treatment phase predicted outcome.Conclusion: Higher APACHE II score, use of pressors and adverse cytogenetics predicted for worse outcome. Increased age and presenting WBC did not. One out of five patients survived an ICU admission to be discharged from the hospital. Aggressive medical management is appropriate for patients with acute leukemia and should not be withheld even in patients with advanced age.

A LDI-PCR Based Method Allows the Identification of Any MLL Rearrangement.

Chromosomal rearrangements of the MLL gene are responsible for 5–10% of all acute leukemias, biphenotypic leukemias and myelodysplastic syndromes. 5–10% of these MLL aberrations are therapy-related leukemias with the frequent fusion partners ELL, MLLT3, MLLT10 and MLLT2. The large number of known and unknown MLL fusions (>80) renders a precise diagnosis a demanding task. Even though all MLL rearrangements are associated with high risk acute leukemias, the outcome (favorable or poor) depends on the partner gene. Thus, the identification of MLL gene fusions is necessary for rapid clinical de-ci-sions resulting in specific therapy regimens. After their cytogenetic identification, only the most common MLL fusions MLLT2, MLLT3, MLLT1, MLLT4, ELL and MLLT10 (80%) are investigated by RT-PCR analysis, whereas infrequent or unknown MLL rearrangements (20%) are more or less excluded from further analysis. Therefore we established a LDI-PCR (long-distance inverse PCR) based method that uses small amounts of genomic DNA to determine any type of MLL associated chromosomal abnormality. With this diagnostic tool more than 400 prescreened und unscreened adult and pediatric samples (AML/ALL) from different European diagnostic centers have been analyzed. During this study more than 200 MLL rearrangements were characterized for their precise localization of genomic break-points. The identified MLL rearrangements consist of 25 different fusion genes including the following eight novel MLL partner genes: ACACA, ARGHEF17, BCL9L, MAML2, SELB, SMAP1, and TIRAP. The identified MLL aberrations are basically reciprocal translocations, but also deletions, inversions, insertions and interstitial duplications have been determined. Combining the data of our study and data retrieved from the literature, a total of 88 partner genes can now be annotated. 52 fusion partners (60%) have been characterized on the molecular level whereas at least 36 (40%) remain to be identified. These results demonstrate that this new diagnostic tool in combination with split-signal FISH is qualified for the rapid analysis of known as well as unknown MLL partner genes. Furthermore, the determined patient specific fusion sequences are useful for minimal residual disease (MRD) monitoring of MLL associated acute leukemias. The use of these MRD markers will contribute to improve the treatment and outcome of acute leukemia patients. A first prospective study was already initiated by the German ALL study group and verified the reliability of these genomic markers for MRD monitoring.

Molecular genetics of childhood leukemias.

This review summarizes the molecular genetics of childhood leukemias, with emphasis on pathogenesis and clinical applications. We first describe the most common genetic events that occur in pediatric acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and chronic myeloid leukemia (CML). We then illustrate how these molecular alterations may be used to alter therapy. In childhood ALL, the TEL-AML1 fusion and hyperdiploidy are both associated with excellent treatment outcomes and therefore identify patients who may be candidates for less intensive therapy. In contrast, MLL gene rearrangements and the BCR-ABL fusion confer a poor prognosis; these patients may be best treated by allogeneic bone marrow transplantation in first remission. Although clinical features are important prognostic indicators, genetic alterations of leukemic blasts may be better predictors of outcome for acute leukemia patients. We therefore favor risk-adapted therapy based on classification schemes that incorporate both genetic and clinical features.