Microbiologically documented infections and infection-related mortality in children with acute myeloid leukemia

Lillian Sung, Beverly J. Lange, Robert B. Gerbing, Todd A. Alonzo and James Feusner


The primary objective was to describe the prevalence and characteristics of microbiologically defined infections and infection-related mortality (IRM) in 492 children with acute myeloid leukemia enrolled on CCG 2961. Secondary objectives were to determine the relationship between demographic, disease-related, and therapeutic variables, and infections and IRM. Institutions documented infections prospectively. Age, ethnicity, body mass index, leukemia karyotype, treatment, and institutional size were examined for association with infection outcomes. More than 60% of children experienced such infections in each of 3 phases of chemotherapy. There were 58 infectious deaths; cumulative incidence of IRM was 11% plus or minus 2%. Thirty-one percent of infectious deaths were associated with Aspergillus, 25.9% with Candida, and 15.5% with alpha hemolytic streptococci. Age older than 16 years (hazard ratio [HR], 3.32; 95% confidence interval [CI], 1.87-5.89; P < .001), nonwhite ethnicity (HR, 1.85; 95% CI, 1.10-3.09; P = .02), and underweight status (HR, 3.06; 95% CI, 1.51-6.22; P = .002) were associated with IRM, while size of the treating institution was not. Thus, age, ethnicity, and BMI were important contributors to IRM. Fungi and Gram-positive cocci were the most common organisms associated with IRM and, in particular, Aspergillus species was the largest contributor to infectious deaths.


Infections are an important cause of morbidity and mortality for children and adults with acute myeloid leukemia (AML). These patients are at particularly high risk of infection, likely related to the intensity of their therapy resulting in repeated episodes of prolonged and profound neutropenia. Infections not only contribute to mortality but also prolong hospitalization, compromise chemotherapy delivery, affect quality of life, and increase health care utilization. Furthermore, protracted empiric and therapeutic use of broad-spectrum antibiotics may contribute to evolution of resistant microbiologic flora.

Although it is known that invasive infections are common in children with AML, little is known about predictors of infections in this population. A recent report from the Children's Cancer Group (CCG) found that body mass index (BMI) was associated with treatment-related mortality.1 More specifically, the authors found that in children enrolled onto the phase 3 trial, CCG 2961, overweight patients were less likely to survive (HR, 1.88; 95% CI, 1.25-2.83; P = .002) and more likely to experience treatment-related mortality (HR, 3.49; 95% CI, 1.99-6.10; P < .001) compared with middleweight patients. However, the analysis did not focus on infection-related mortality.

Given this finding, we wished to specifically explore infections and infection-related mortality in children with AML and to determine how they are influenced by BMI and other potential predictors of outcome, which included age, ethnicity, leukemia cytogenetics, and size of the treating institution. Our primary objective was to describe the prevalence and characteristics of infections and infectious deaths in children with AML enrolled onto CCG 2961. The secondary objectives were to determine the relationship between demographic, disease-related, and therapeutic variables, and infections and infection-related mortality during AML chemotherapy in children.

Patients and methods


This study was approved by each participating institution's institutional review board (Document S1, available on the Blood website; see the Supplemental Materials link at the top of the online article). Informed consent was obtained in accordance with the Declaration of Helsinki.

The patients included in this report were those enrolled onto CCG 2961. Children between the ages of one month to 21 years with newly diagnosed AML or myelodysplastic syndrome were eligible. Patients with acute promyelocytic leukemia, Down syndrome, or AML as a second malignancy were excluded. In addition, for this specific analysis, we also excluded patients with myelodysplastic syndrome, AML patients with isolated granulocytic sarcoma, and infectious complications during phase 3 allogeneic stem cell transplantation (SCT).

Therapy consisted of 4 phases: (1) induction (idarubicin, daunomycin, cytarabine, thioguanine, etoposide, and dexamethasone [IdaDCTER]); (2) consolidation (randomization between a second IdaDCTER versus fludarabine, cytosine arabinoside, and idarubicin); (3) intensification (cytosine arabinoside and l-asparaginase or SCT for those patients with a matched related donor); and (4) immune modulation (randomization to interleukin-2 or none in patients without donors after phase 3). In phase 2, IdaDCTER contained 5 mg/m2 per day of idarubicin for 4 days and 200 mg/m2 per day of cytarabine on days 0 to 3 and days 10 to 13 as continuous infusions. The fludarabine-based regimen contained 12 mg/m2 per day of idarubicin for 3 days and 2400 mg/m2 per day of cytarabine for 3 days as a continuous infusion (B.J.L., F.O. Smith, J.F., D. Barnard, P. Dinndorf, S. Feig, N. Heerema, C. Arndt, R. Arceci, N. Seibel, M. Weiman, K. Dusenbery, K. Shannon, S. Luna-Fineman, R.B.G., and T.A.A., “Outcomes in CCG-2961, a Children's Oncology Group phase 3 trial for untreated pediatric acute myeloid leukemia (AML); a report from the Children's Oncology Group,” manuscript submitted April 2007).

For this study, drug dosing was based on weight in kilograms up to age 3 years and by body surface area for children older than 3 years. Drug doses were modified for hyperbilirubinemia only for this group of patients, and there were no dose modifications for underweight or overweight patients.

There were uniform guidelines for the use of empiric antibiotic and antifungal therapy as well as granulocyte colony-stimulating factor (G-CSF). In patients with an absolute neutrophil count of .5 × 109/L (500/μL) or less and oral temperature higher than 38°C twice in 12 hours or higher than 38.5°C once, empiric systemic antibiotics were mandated. Broad-spectrum antibiotics such as ceftazidime or triple antibiotic combinations of an aminoglycoside, extended spectrum penicillin, and an antibiotic with activity against alpha hemolytic streptococci and staphylococci were specified. In terms of empiric antifungal coverage, the protocol specified that in the setting of persistence of fever after 7 days of broad-spectrum antibiotic coverage or the emergence of a new fever in neutropenic patients with negative blood cultures, intravenous amphotericin B at 0.5 mg/kg per day was to be initiated. G-CSF was specified beginning 2 days after completion of induction and consolidation until the absolute neutrophil count was higher than 1.5 × 109/L (1500/μL).

This trial was open to patient accrual on August 30, 1996. The study was suspended in October 1999 because of concern regarding increased treatment-related mortality compared with the previous CCG AML trial. The study was reopened in May 2000 and met accrual target December 4, 2002. The analysis presented in this report is based on children that were enrolled in the presuspension period because of differences in how infections were reported in the 2 time periods.


Infections were prospectively collected by the institutional clinical research associates using a standardized data collection form. Microbiologically documented infections with the same organisms within the same phase of therapy were counted as different infections if they occurred more than 7 days apart. An infectious episode was defined as a microbiologically or a clinically documented infection. In the case of common contaminants such as coagulase-negative staphylococci and Gram-positive bacilli, insufficient clinical information was available to distinguish between likely contaminants versus invasive infections and in this study; positive cultures were included as infectious episodes. Clinically documented infections such as pneumonia or typhlitis without microbiologic documentation were documented, but are not included in this report apart from the description of infectious episodes.

Potential predictors related to demographics, disease, and treatment

Potential predictors of infection outcomes that were examined were age (0-< 2, 2-16 and > 16 years), ethnicity (white versus nonwhite), BMI (overweight, middleweight, and underweight BMI status), leukemia cytogenetics, time to an absolute neutrophil count of at least 1.0 × 109/L (1000/μL; more than and fewer than the median number of days) and institution size (≤ or > median of 6 patients per year annual accrual).

Body mass index at diagnosis was calculated as weight in kilograms divided by the square of the height in meters.2 For patients older than 2 years, underweight was defined as BMI of 10th percentile or lower; overweight, as BMI of the 95th percentile or higher; and middleweight, as BMI higher than the 10th to lower than the 95th percentile. For patients ages 1 to 2 years, 95th percentile or higher and 10th percentile or lower of weight for length were used to define overweight and underweight, respectively.2 Those younger than 1 year were not included in the analysis by BMI because of lack of consensus definitions for overweight and underweight in this age group.

Statistical analysis

Data were analyzed through to June 9, 2006. Observed differences in proportions were tested using the chi-squared test and Fisher exact test when data were sparse. To account for each patient having different lengths of time at risk related to relapse, death, or SCT, the number of infections was expressed as the rate of infections per day. The time period at risk was during on-study chemotherapy administration and did not include time following removal from study for any reason, relapse or SCT. The number of infections was modeled using Poisson regression and treatment effects were expressed as the incidence rate ratio (IRR). The IRR expresses the increase in risk of an outcome for a one-unit change in the covariate and can be considered analogous to a relative risk.

Infection-related mortality was analyzed using a Cox proportional hazards model where the primary event was death attributed to infection.3 Patients who relapsed, had a noninfection-related death, completed protocol therapy, or underwent protocol SCT were censored at the time of the event. Patients who withdrew from protocol therapy before completion were censored 30 days from the time they were taken off study. The 5-year estimate for infection-related mortality was calculated by cumulative incidence where patients who died due to infection were the primary events. Patients who either relapsed or died not due to infection were competing events, and patients who underwent protocol SCT were censored. For all analyses, patients lost to follow-up were censored at their date of last known contact or at a cutoff 6 months prior to June 9, 2006, to compensate for the tendency of deaths and relapses being reported sooner than ongoing follow-up. All statistical analysis was performed using the SAS statistical program (SAS-PC, Version 9.1; SAS Institute, Cary, NC). All tests of significance were 2-sided and statistical significance was defined as P value less than .05.


A total of 492 children were included in this analysis. Table 1 illustrates the demographics of these children. The median age was 9.6 years (range, 0.005-21.0 years). Of the 492 children, 48 (10%) were overweight and 150 (30%) were underweight. Following phase 1, 389 (80%) children were in complete remission, 35 (7%) were in partial remission, and 27 (6%) had persistent disease. Six withdrew from the study, and 2 were not evaluable. During phase 1, 33 (7%) died.

Table 1

Demographic variables and treatment response of 492 children with de novo acute myeloid leukemia enrolled in CCG 2961

The most common sites of microbiologically documented infections were blood, pulmonary, and gastrointestinal tract (Table 2). The majority of subjects had at least one microbiologically documented infection during each phase of therapy (Table 3). Infections with Gram-positive cocci predominated as the etiology of microbiologically documented infections. More specifically, coagulase-negative Staphylococcus and alpha hemolytic Streptococcus were the most common cause of at least one infection during each phase of therapy, with 18%, 17%, and 19% of patients having at least one positive culture with coagulase-negative Staphylococcus, and 10%, 27%, and 20% of patients having at least one positive culture with alpha hemolytic Streptococcus, in phases 1, 2, and 3, respectively. Pseudomonas species, Escherichia coli, and Klebsiella species were the most common Gram-negative organisms. Fungi also were a prominent cause of such infections, occurring in 18%, 21%, and 14% of subjects in phases 1, 2, and 3, respectively. Four percent to 10% of patients had at least one infection with Candida species. However in phase 2 almost twice as many patients had at least one Aspergillus species compared with Candida species infections.

Table 2

Sites of microbiologically documented infections

Table 3

Percentage of patients with at least one microorganism during each phase of therapy

To examine whether alpha hemolytic streptococci were associated with severe infection, we compared patients with and without at least one episode of alpha hemolytic streptococcal bacteremia with respect to reporting of any grade 3 or 4 toxicity and, specifically, grade 3 or 4 pulmonary, renal, or cardiac toxicity. Those with alpha hemolytic streptococci were more likely to have any reported severe toxicity (80% versus 63% [P = .018] in phase 1 and 69% versus 49% [P = .018] in phase 3). In addition, those with alpha hemolytic streptococcal bacteremia were more likely to have grade 3 or 4 clinical pulmonary toxicity (dyspnea at rest or with normal activity) (10% versus 3% [P = .046] for phase 1 and 6% versus 2% [P = .019] for phase 2) and grade 3 or 4 functional pulmonary toxicity (required oxygen or assisted ventilation) (27% versus 14% [P = .016] for phase 1 and 18% versus 10% [P = .048] for phase 2).

Recurrence of infection was common between phases 1 and 2 but less so for all 3 phases. For example, in the 51 children with alpha hemolytic streptococci isolated in phase 1 (23 of whom completed all 3 phases), 14 also had a positive culture for the same organism in phase 2, while only 1 child had a positive culture in all 3 phases. Similarly, for the 7 children with respiratory syncytial virus in phase 1 (3 of whom completed all 3 phases), 3 also had a positive culture for this virus in phase 2, while only 1 child had a positive culture in all 3 phases.

To account for the possibility of subjects having more than one infection and differing periods at risk, Table 4 illustrates the results of the Poisson regression. Table 4 illustrates that the rates of microbiologically documented bacterial infections per day in each of the 3 phases of therapy were similar. Table 4 also illustrates that BMI impacted the rate of bacterial infections only during phase 2, with a significantly higher rate of infections in overweight children. Conversely, age, ethnicity, duration of neutropenia, and institution size did not significantly impact the rate of bacterial infections. In terms of institution size, we chose to compare institutions with more than 6 versus 6 or fewer accruals per year, as that was the median accrual rate for all institutions participating in the trial. In addition, we also examined cutoffs of 2, 3, 4, and 5 patients per year; none of them was significantly associated with the rate of bacterial infections (data not shown). In phase 2, BMI also was predictive of the number of all microbiologically documented infections (P = .007), the number of infectious episodes (P = .003), and the number of bacteremias (P = .038), with overweight children having more infections compared with normal weight children (data not shown).

Table 4

Univariate regression predicting the risk of microbiologically documented bacterial infection (any site) by phase of treatment

The cumulative incidence of infection-related mortality was 11% plus or minus 2% during the period at risk that excluded SCT, relative to the cumulative incidence of death from any cause as a first event of 18% plus or minus 4%. Table 5 illustrates the microorganisms associated with infection-related mortality. When both polymicrobial and single-pathogen infection-related mortality were considered, coagulase-negative staphylococci, alpha hemolytic streptococci, Candida species, and Aspergillus species were the most common etiologic agents related to infectious deaths. In particular, in phase 2, Aspergillus species accounted for 46% of infection-related deaths on protocol therapy. The following lists the proportion of infections with specific pathogens that resulted in fatal infections: coagulase-negative staphylococci 14 (6.7%) of 208, alpha hemolytic streptococci 9 (4.3%) of 209, Candida species 15 (17.6%) of 85, and Aspergillus species 18 (26.1%) of 69. Pseudomonas species contributed to 6 deaths, Klebsiella species to 7, and other Gram-negative bacilli to 15. Of the 58 infection-related deaths, the proportion attributed to specific organisms were as follows: coagulase-negative staphylococci 14 (24.1%) of 58, alpha hemolytic streptococci 9 (15.5%) of 58, Candida species 15 (25.9%) of 58, and Aspergillus species 18 (31.0%) of 58. In other words, Aspergillus species was the largest contributor to infection-related mortality in these children. It is important to note that this study could not distinguish which coagulase-negative staphylococcal infections were contaminants. Thus it is likely that some of these infections were not the cause of death. In addition, it is important to emphasize that many infectious deaths were polymicrobial, and one infection or treatment of one infection may have led to subsequent lethal infections.

Table 5

Microorganisms responsible for infection-related mortality on protocol therapy

If infection-related mortality is classified by association with a single or multiple pathogens, then 22 (37.9%) were associated with only one microorganism, most often Aspergillus species (7 deaths). The next most common causes of single-pathogen–associated infection-related mortality were Escherichia coli and Pseudomonas aeruginosa in 3 children for both. In other words, polymicrobial infection-related mortality was more common than single-pathogen infection-related mortality. In particular, only 2 of 14 fatal infections with coagulase-negative Staphylococcus had this organisms as the sole isolate.

Table 6 illustrates potential predictors of infectious mortality in univariate analysis and demonstrates that BMI was significantly associated with infection-related mortality, with underweight children having a 3-fold increase in mortality and overweight children having a 1.5-fold increase in mortality. In addition, nonwhite children were more likely to die of infection with a hazard ratio of 1.85. In addition, children older than 16 years were more likely to die of infections compared with children 2 to 16 years of age. Neither cytogenetics nor institution size was associated with infection-related mortality. We also examined whether the cumulative risk of death as a first event or infection-related mortality was significantly different between those enrolled prior to and after March 16, 1998 (n = 290 in each group). These were not different, with 5-year cumulative incidences of death as a first event of 17.0% plus or minus 5% in the earlier group and 18.0% plus or minus 5.0% in the latter group (P = .639 by Gray test) and infection-related mortality of 11.0% plus or minus 3.0% in both groups (P = .804 by Gray test).

Table 6

Potential predictors of infection-related mortality

A multiple regression analysis then was conducted to examine whether the effects of BMI, ethnicity, and age were independently associated with infection-related mortality. Because only children older than one year were included in the BMI analysis, the multiple regression model included age as a dichotomous variable by older than 16 years of age versus younger children. In this model, age older than 16 years (HR, 3.46; 95% CI, 1.94 to 6.17; P < .001), nonwhite ethnicity (HR, 2.05; 95% CI, 1.17 to 3.58; P = .012), and underweight status (HR, 3.59; 95% CI, 1.74 to 7.39; P = .001) all remained independent predictors of infection-related mortality.

There was one randomized intervention relevant to our analysis, which was the randomization during phase 2 between IdaDCTER versus the fludarabine-based regimen. During phase 2, there were 24 treatment-related deaths and there was significantly more treatment-related mortality associated with the fludarabine-based regimen, with 7 deaths with IdaDCTER and 17 deaths with fludarabine (P = .01). Infection-related mortality also was higher with the fludarabine regimen (HR, 1.92; 95% CI, 0.97 to 3.81; P = .063). There was no difference in the rate of bacterial infections between the 2 randomized regimens, with an IRR of 1.09 (95% CI, 0.90 to 1.32; P = .357). However, the rate of alpha hemolytic streptococcal bacteremia was higher in the fludarabine-based regimen compared with IdaDCTER (IRR, 1.84; 95% CI, 1.25 to 2.72; P = .002), and those allocated to the fludarabine-based regimen had a higher percentage of patients with at least one alpha hemolytic streptococcal infection compared with IdaDCTER (22.4% for IdaDCTER versus 33.2% for the fludarabine regimen, P = .016). The duration of neutropenia did not explain these differences, as the median time to absolute neutrophil count recovery was shorter for the fludarabine-based regimen (49 days for IdaDCTER versus 40 days for the fludarabine-based regimen; P < .001). Similarly, prevalence of mucositis did not explain these differences, and occurred in 32.2% with IdaDCTER versus 25.7% with the fludarabine regimen (P = .185).


We found that most children with AML experience invasive infections and that Gram-positive cocci are the most common microbiologically documented etiology of these infections. The cumulative incidence of infection-related mortality was 11% plus or minus 2% during chemotherapy administration excluding SCT. Polymicrobial infections are commonly associated with infection-related mortality in AML patients as a group, and in individual patients, fungi are implicated in more than half of infectious deaths. More specifically, Aspergillus species was the largest contributor to infection-related mortality. Children who were underweight, nonwhite, and older than 16 years were at higher risk of deaths from infection.

Our report is important for several reasons. First, to our knowledge, we have the only large pediatric AML study in which infections were collected prospectively and in which a specific emphasis was placed on collecting infection data. This distinction is important as it likely increased the quality and compliance of infection reporting, thus making our study a more accurate reflection of the real incidence of microbiologically documented infections compared with studies in which these data were collected retrospectively. Second, we have described one of the largest cohorts of children with AML in which infection-related mortality is described. This point is important as infection-related mortality is the most clinically relevant infection end point, and our study is one of a few pediatric AML studies sufficiently powered to model infectious deaths. Finally, our study is the only one to track individual patients over several courses of chemotherapy and, thus, we have been able to describe the recurrence risks with specific microorganisms.

Infection-related mortality in this study was higher than that demonstrated in other pediatric AML studies. An infection-related mortality of 25 (7.3%) of 341 during chemotherapy was reported for children treated according to a United Kingdom protocol, Medical Research Council 10 trial (MRC-10).4 A retrospective analysis of a German study AML-BFM 93 noted 855 infectious complications occurring in 304 children with AML, with 20 (6.6%) dying of infection (5.4% in non–Down syndrome children).5 Similarly, a single institution study found that 5 (6.4%) of 78 of their children with AML died of infection.6 The reason for higher infection-related mortality on CCG 2961 may be related to the intensely myelosuppressive nature of this chemotherapy regimen. Alternatively, in intensive chemotherapy protocols, treatment-related mortality may decline as treating centers become more familiar with managing these complex children.7 More specifically, children enrolled on MRC-10 had a decline in treatment-related mortality from 17.8% in the earlier period to 9.6% in the later period.7 Given that we are presenting infection-related mortality for the earliest children enrolled on CCG 2961, our higher rates may reflect an early experience with a new treatment protocol rather than fundamentally different rates of infection-related mortality.

It is not known why underweight children with AML have higher infection-related mortality and overweight children have more infections depending on the specific chemotherapy administered. One possible explanation is that since drug doses were not modified depending on BMI, that drug exposure was significantly different in underweight and overweight children. However, this hypothesis is not supported by the duration of neutropenia and time to initiation of the next phase of chemotherapy, which were shorter in overweight children treated on this protocol.1 Another possibility is that underweight and overweight children have important comorbidities or nutritional compromise that could explain differences in infection outcomes.

The factors predictive of microbiologic documented infections did not precisely match those predictive of infection-related mortality. For example, while overweight status was predictive of microbiologically documented infections in phase 2, only underweight children were at significantly high risk of infection-related mortality. Similarly, while we did not find that ethnicity was a significant predictor of microbiologically documented infections, we found that nonwhite children had a higher risk of infection-related mortality. This divergence could be hypothesized to be related to several potential issues. First, infection-related mortality includes mortality related to clinically documented infections as well as microbiologically documented infections, and factors predictive of clinically documented infections may differ from those predictive of microbiologically documented infections. Second, the analysis of the number of infections was conducted separately for each phase, whereas infection-related mortality reflected a summary of events occurring throughout the course of therapy. Third, the inability to distinguish common contaminants from invasive infection may have diluted our ability to predict invasive microbiologically documented infections. Finally, it is possible that the lack of significantly increased infection-related mortality in the overweight group is related to sample size, given that an analysis of the entire CCG 2961 patient cohort did demonstrate increased infection-related mortality in the overweight group.1

As CCG 2961 contained one randomization in phase 2, this design provided an opportunity to more precisely estimate the contribution of different drugs to infection outcomes. It is interesting that the fludarabine-based regimen was associated with more treatment-related mortality and a higher rate of alpha hemolytic streptococcal infection despite also being associated with a shorter duration of neutropenia. There were 3 major differences between the 2 regimens that might explain these findings, namely, the presence of fludarabine, higher daily dose of idarubicin, and higher daily dose of cytarabine associated with the fludarabine-based regimen (although the cumulative doses of idarubicin and cytarabine were similar). Given previous reports that have found that high-dose cytarabine is a risk factor for invasive viridans group streptococcal infections,813 it seems that the latter may be the more likely etiologic factor behind worse infection outcomes associated with the fludarabine regimen.

A limitation of our study is that insufficient clinical information was available to distinguish between likely contaminants versus invasive infections. Therefore, the estimate of the number of Gram-positive infections may be an overestimate. Similarly, we did not know whether urine specimens were catheter, midstream, or bagged specimens and thus, we likely have overestimated the rate of this infection as well. Conversely, given that our classification of infection relied on microbiology, we likely underestimated the risk of Aspergillus infections, an important point when considering the large apparent contribution of Aspergillus to infection-related mortality even when only microbiology was considered. Finally, we chose to censor patients at the completion of protocol therapy or 30 days following removal from protocol to exclude those who died of infection related to a relapse or salvage protocol. However, it is possible that some patients may have experienced late infection-related mortality (for example, from Aspergillus) following completion of protocol therapy or removal from protocol therapy, and thus we may have underestimated both the risk of infection-related mortality as well as the contribution of Aspergillus to infectious deaths.

For those caring for children with AML, knowledge of the polymicrobial nature of infection-related mortality emphasizes the need to continue broad-spectrum coverage in these patients during neutropenic infectious episodes, even if investigations reveal a specific microorganism. In addition, given the large contribution of invasive fungal infection and in particular Aspergillus to infectious deaths, careful consideration of antifungal coverage and thorough evaluation for fungus are warranted in the appropriate setting.

In summary, microbiologically documented infections and infection-related mortality are common in pediatric AML. Aspergillus species was the most common contributor to infectious deaths. Age, ethnicity, and BMI were predictors of infection-related mortality. Further understanding of the etiology behind this relationship will help develop future AML protocols.

Supplementary PDF file available online.


Contribution: R.B.G. and T.A.A. analyzed the data; L.S. wrote the paper. All authors designed and performed the research, revised the paper for critical content, and approved the final version of the paper.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Correspondence: Lillian Sung, Division of Haematology/Oncology, Hospital for Sick Children, 555 University Avenue, Toronto, ON Canada M5G 1X8; e-mail: lillian.sung{at}


L.S. is supported by a Career Development Award with the Canadian Child Health Clinician Scientist Training Program, a strategic training program with the Canadian Institutes of Health Research. B.J.L. holds the Yetta Dietch Novotny Chair in Clinical Oncology. We also acknowledge the support of Cancer Control and Acute Myeloid Leukemia committees at the Children's Oncology Group.


  • The online version of this article contains a data supplement.

  • The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

  • Submitted May 24, 2007.
  • Accepted July 25, 2007.


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