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CLINICAL OBSERVATIONS, INTERVENTIONS, AND THERAPEUTIC TRIALS
From the City of Hope National Medical Center, Duarte,
CA.
The associations of cytogenetics with complete remission (CR)
rates, overall survival (OS), and outcomes after CR were studied in 609 previously untreated AML patients younger than 56 years old in a
clinical trial comparing 3 intensive postremission therapies: intensive
chemotherapy, autologous transplantation (ABMT), or allogeneic bone
marrow transplantation (alloBMT) from matched related donors. Patients
were categorized into favorable, intermediate, unfavorable, and unknown
cytogenetic risk groups based on pretreatment karyotypes. CR rates
varied significantly (P < .0001) among the 4 groups:
favorable, 84% (95% confidence interval [CI], 77%-90%); intermediate, 76% (CI, 71%-81%); unfavorable, 55% (CI, 48%-63%); and unknown, 54% (CI, 33%-74%). There was similar significant heterogeneity of OS (P < .0001), with the estimated
relative risk of death from any cause being 1.50 (CI, 1.10-2.05), 3.33 (CI, 2.43-4.55), and 2.66 (CI, 1.59-4.45) for the intermediate,
unfavorable, and unknown risk groups, respectively, compared with the
favorable group. In multivariate analyses, the effects of cytogenetic
risk status on CR rate and OS could not be explained by other patient or disease characteristics. Among postremission patients, survival from
CR varied significantly among favorable, intermediate, and unfavorable
groups (P = .0003), with significant evidence of
interaction (P = .017) between the effects of treatment
and cytogenetic risk status on survival. Patients with favorable
cytogenetics did significantly better following ABMT and alloBMT
than with chemotherapy alone, whereas patients with unfavorable
cytogenetics did better with alloBMT. Cytogenetic risk status is a
significant factor in predicting response of AML patients to
therapy; however, to tighten treatment correlates within
genetically defined AML subsets, a significantly larger leukemia
cytogenetic database is warranted.
(Blood. 2000;96:4075-4083) Cytogenetic analysis performed at diagnosis is
generally recognized as the single most valuable prognostic factor in
acute myeloid leukemia (AML).1,2 Characterization of adult
patients with AML according to presentation karyotype provides an
important basis for selection of therapy. For example, the outcome for
patients with t(15;17) acute promyelocytic leukemia has substantially
improved with the use of all-trans-retinoic acid in
combination with chemotherapy, but the drug is without benefit for
patients lacking this translocation.3,4 A recent report
categorizing patients to one of 3 cytogenetic groups, core binding
factor (CBF) positive, normal, or all other karyotypic abnormalities,
followed by randomization to either standard, intermediate, or
high-dose cytarabine, suggested that the effect of cytarabine
intensification varied significantly among the cytogenetic risk groups,
with the major benefit of high-dose cytarabine restricted to patients
with CBF karyotypes.5 The German AML Cooperative recently
reported improved complete remission (CR) rates for unfavorable
cytogenetics using a double induction strategy of
cytarabine/daunorubicin/6-thioguanine (TAD), followed by high-dose
cytarabine with mitoxantrone (HAM).6 Taken together, these
data suggest that therapeutic strategies based on expected response of
specific disease karyotype subsets may improve the outcome of therapy
in AML.
Optimal postremission therapy for young patients with AML remains a
topic of lively discussion. The postremission strategies of high-dose
cytarabine and allogeneic and autologous stem cell transplantation all
have contributed to improved outcome for adult patients with AML. To
date, randomized studies comparing these therapies have led to
inconsistent conclusions.7-9 In most of these studies,
outcome was not analyzed according to cytogenetic risk group. To
investigate whether the impact of different postremission strategies
might vary according to cytogenetic risk group, we analyzed the results
of a large phase III trial (E3489/S9034) for young adult (< 56 years
of age) AML patients who received idarubicin and cytarabine as
induction therapy and allogeneic or autologous bone marrow
transplantation or intensive chemotherapy as postremission therapy. The
objectives of this analysis were (1) to examine the relationship of
disease karyotype with CR rate, overall survival (OS), and
postremission outcomes and (2) to examine the effect of cytogenetic
risk groups within the 3 postremission arms. To allow comparison with
the 10th United Kingdom Medical Research Council AML trial (MRC
AML 10 trial), the cytogenetic data were also coded and analyzed
according to published MRC criteria.10
Patients and protocol
Cytogenetic analyses
Cytogenetic abnormalities were grouped according to published criteria
adopted by SWOG.2,5,10,12-16 Four cytogenetic categories were defined (Table 1). The
favorable risk category included patients with abnormalities
(abn) of inv(16)/t(16;16)/del(16q) or t(15;17) with any additional
abnormalities, or t(8;21) without either a del(9q) or being part of a
complex karyotype. The presence of a del(9q) in patients with t(8;21)
leukemia has been reported as a poor risk indicator requiring more
aggressive treatment.15 The intermediate risk
category included patients characterized by +8,
To allow comparison with the MRC AML 10 trial, the cytogenetic data
were also coded and analyzed according to published MRC criteria.10 The major differences between these 2 systems
are the definition of complex karyotypes ( Criteria for treatment outcomes Complete response and relapse were defined according to standard criteria.17 OS was measured from the day of registration on study until death from any cause, censored for patients known to be alive at last contact. Survival from CR was defined similarly but from the date CR was achieved. Disease-free survival (DFS) was measured from the date of CR until either relapse or death from any cause, censored at last contact for patients last known to be alive without report of relapse.Statistical analysis Collection and quality control of patient pretreatment and outcome data were performed according to standard ECOG procedures. Analyses involving postremission therapy were based on intention to treat, with all patients analyzed according to their postremission treatment arms irrespective of whether they actually received the designated treatment. Distributions of OS and DFS were estimated by the method of Kaplan and Meier.18 Prognostic significance of cytogenetic categories, treatment assignments, and other pretreatment factors (age, sex, performance status, FAB classification, marrow and peripheral counts, disease signs and symptoms, and extramedullary involvement) were investigated in logistic regression models for CR and proportional hazards regression models for OS, survival from CR, and DFS. Quantitative factors such as age, blood or marrow cell counts, or percentages were treated as continuous variables in these regression models. The prognostic effects of the SWOG and MRC cytogenetic classification systems were compared indirectly, as follows. In regression models, collapsing categories of a qualitative predictor variable restricts the model's ability to fit the data. Measures of the resulting "loss of fit" provide formal statistical tests of whether the collapsed categorization fits the data significantly worse than the original, finer categorization. Such tests are not available if, like the SWOG and MRC schemes, one categorization cannot be obtained by collapsing categories of the other. Therefore, the relative prognostic values of the 2 schemes were examined by testing the loss of fit associated with each one compared with a model with categories defined by the combination of both. If the resulting loss of fit was statistically significant for one scheme but not the other, the latter scheme could be viewed as having greater prognostic value. All P values are 2-tailed. Analyses were based on data available as of July 7, 1998.
Between March 1990 and February 1995, a total of 808 patients
entered study E3489/S9034, including 293 from SWOG and 492 from ECOG
(Figure 1). The remaining 23 patients
from a third cooperative group were omitted from this study. Eighteen
of the SWOG and ECOG patients were ineligible for study E3489/S9034,
and 4 other patients never began protocol therapy. Of the 763 SWOG and
ECOG patients eligible for this prospective study, 609 (80%) had
acceptable karyotypic studies at the time of central review for this
study. Reasons for exclusion included no specimen submitted (n = 30), no growth (n = 62), and inadequate number of cells analyzed,
inadequate specimen processing, or poor unevaluable morphology
(n = 62). The 609 evaluable patients (284F, 325M) had median age of
39 (range 16-55).
The ECOG and SWOG patients were similar with respect to the proportion
with normal studies (40% for both groups) and the ratios of favorable,
intermediate, unfavorable, and unknown risk groups (Table
2). They were also similar in the
prevalence of specific clonal abnormalities, with the exception of
inv(3q), for which 11 of 12 cases were from ECOG, most likely
reflecting a random chance imbalance. However, the prevalence of
"complex" and miscellaneous "other" abnormalities was higher in
the SWOG cohort (14% and 24%, respectively) than the ECOG cohort
(10% and 17%, respectively). Characteristics of included
patients and leukemic specimens, by SWOG cytogenetic risk assessment,
are given in Table 3.
Response to induction therapy A total of 584 of the 609 patients had sufficient data to confirm their responses to remission induction therapy. Of these, 412 (71%) achieved CR. The CR rate varied significantly (P < .0001) among the 3 groups with known cytogenetic risk status, ranging from 84% (98 of 117; 95% confidence interval [CI], 77%-90%) for favorable to 76% (205 of 270; CI, 71%-81%) for intermediate to 55% (96 of 173; CI, 48%-63%) for unfavorable (Table 4). This heterogeneity was largely due to the lower CR rate in the unfavorable group compared with the other 2 combined (P < .0001); the difference between intermediate and favorable groups was not significant (P = .080). The CR rates were similar in the 2 Groups: 242 of 348 (70%) for ECOG and 170 of 236 (72%) for SWOG, and there was no significant interaction between the effects of Group and the 3 cytogenetic risk categories (P = .64). Thus, the prognostic significance of cytogenetic category was similar in the 2 Groups despite differences in the proportions of patients with complex or miscellaneous "other" abnormalities.
Multiple logistic regression analyses that explored the prognostic effects of the available pretreatment variables, including all of those listed in Table 3, along with cytogenetic risk status were performed for the 560 patients with known risk status and response. These analyses suggested that only cytogenetic risk status and either performance status (PS) (P = .0059) or fever at presentation (P = .0080) were highly significant prognostic factors for response. After adjusting for either or both PS and fever, the heterogeneity of CR rates among the 3 cytogenetic categories remained highly significant (P < .0001). These analyses suggested that the effects of cytogenetics on CR rate could not be explained by any of the other patient or disease characteristics considered. Overall survival by cytogenetic risk status Of the 609 patients with evaluable cytogenetics, 403 have died. The other 206 have survived a median of 58 months (range 8 to 94 months). Among the 583 patients with known cytogenetic risk status, OS varied significantly according to cytogenetic risk status (P < .0001) (Figure 2). Comparisons of OS within cytogenetic risk groups are summarized in Table 4. The estimated relative risk (RR) of death compared with the favorable group was 1.50 (CI, 1.10-2.05) for the intermediate group and 3.33 (CI, 2.43-4.55) for the unfavorable group.
Multiple proportional hazards regression analyses were performed to investigate whether the apparent effect of cytogenetic risk status on OS might be explained by the effects of other prognostic factors. After adjusting for the effect of cytogenetic risk status, 3 variables had significant prognostic effects: OS decreased with increasing age (P < .0001) and white blood count (WBC) (P = .0072) and with worsening PS (P = .0002). The effect of cytogenetic risk status remained highly significant (P < .0001) after adjusting for the effects of these 3 factors. None of the other factors considered were significantly associated with OS after accounting for the effects of risk status, age, WBC, and PS. Thus, it did not appear that the effect of risk status on survival could be attributed to the other factors. Further analyses of the unfavorable group Further investigation of the unfavorable group examined the role of complex abnormalities in the presence or absence of 5/5q and/or
7/7q. There was significant heterogeneity of outcomes in the 4 resulting groups (P = .0068 for CR, P = .0018
for survival) (Table 5). In particular,
the patients with aberrations of chromosome 5 and/or 7 in a complex
karyotype had a particularly low CR rate (37%), and all died within
2.5 years. Patients in the unfavorable risk group without 5/5q,
7/7q, or complex karyotype had a 68% CR rate, although this did
not result in markedly superior long-term survival compared with the
remaining unfavorable subgroups.
Postremission therapy Of the 412 patients who achieved CR, 149 (36%) were not registered for postremission therapy. Reasons for failure to register have been previously published.9 The remaining 263 were assigned to alloBMT (n = 89, 34%) or randomized between ABMT (n = 84, 32%) and consolidation (n = 90, 34%). The distributions of cytogenetic categories are shown by treatment arm in Table 6. These distributions, based on centrally reviewed karyotypes, differ slightly from those reported in Table 1 of the original report of clinical results from this study.9 For the 399 patients with known cytogenetic risk status who achieved CR, the distribution of cytogenetic categories did not vary significantly among the 4 postremission treatment groups (3 treatment arms and nonregistered; P = .68).
The proportions of patients who received their assigned postremission
treatments varied widely among the treatment arms and cytogenetic
groups (Table 7). Among the 86 consolidation patients, at least 90% received their study therapy
regardless of cytogenetic group. However, among the 84 allogeneic and
83 autologous transplant patients, the proportions receiving
transplants on study were lower overall and decreased sharply with
worsening risk status. In the unfavorable risk group, only 61% and
50% of the alloBMT and ABMT patients, respectively, received their
transplants on study.
A total of 140 of the 263 patients registered for postremission therapy
have died, and the remaining have survived between 8 months and 7.5 years (median 4.8 years) after achieving CR. Survival from CR did not
vary significantly among the 3 treatment arms (P = .50)
(Figure 3A). However, among the 253 patients with known cytogenetic risk status, there was significant
heterogeneity of survival among the 3 cytogenetic groups
(P = .0003) (Figure 3B). The estimated probability of
surviving 5 years after achieving CR was 57% (CI, 44%-69%) for
patients with favorable karyotypes, compared with 48% (CI, 39%-58%)
for the intermediate group and 23% (CI, 12%-35%) for the unfavorable
group. Compared with the favorable group, the RRs of death were 1.13 (CI, 0.72-1.77) and 2.37 (CI, 1.47-3.82) for the intermediate and
unfavorable groups, respectively. Thus, the intermediate and favorable
groups did not differ significantly (P = .58), and the
heterogeneity was almost entirely due to relatively poor survival of
patients in the unfavorable group (RR = 2.18 compared with favorable
and intermediate combined [CI, 1.51-3.14; P = .0001]).
Too few complete responders in the unknown cytogenetic risk group were
registered for postremission therapy (n = 10) to evaluate their
post-CR survival reliably.
Exploratory analyses were performed to investigate whether treatment
effects might vary among the cytogenetic groups, based on the 253 patients with known cytogenetic risk status who were registered for
postremission therapy. There was significant heterogeneity of survival
after CR among the 9 subgroups defined by treatment arm and risk group
(P = .0001) (Table 8). This
heterogeneity was largely due to the differences mentioned above;
however, after accounting for the differences between cytogenetics
groups, the heterogeneity remaining among the 9 groups was marginally
significant (P = .017). This suggests that differences
between the treatment arms may vary according to cytogenetic group. As
shown in Table 8, among patients with favorable karyotypes, those in
the ABMT arm had the best (RR = 0.70 compared with the alloBMT arm)
survival from CR, whereas the chemotherapy arm had the worst
(RR = 2.04) survival from CR (P = .051 for heterogeneity
among the 3 treatment arms) (Figure 3C). In the intermediate group, in
contrast, ABMT patients had the worst survival from CR (RR = 1.43)
and chemotherapy the best (RR = 0.70) outcomes
(P = .076) (Figure 3D). Finally, in the unfavorable group
both ABMT (RR = 2.22) and chemotherapy patients (RR = 1.82) had
poorer outcomes than alloBMT patients (P = .11) (Figure
3E). Of particular interest was the possibility that alloBMT might be
more beneficial than ABMT or further chemotherapy for patients with
unfavorable cytogenetics. Combining the latter 2 treatment arms yielded
an RR of 2.00 (CI, 0.98-4.06) compared with alloBMT. This difference,
although only marginally significant (P = .043), is
consistent with the hypothesis that alloBMT is more effective than ABMT
or chemotherapy in overcoming the detrimental impact of unfavorable
cytogenetics.
After accounting for the effect of cytogenetic risk status, increasing age was also a significant prognostic factor for survival (P = .0038). In age-adjusted analyses, the heterogeneity of survival from CR remained significant (P = .0002), with estimated RRs (0.97 [CI, 0.62-1.54] and 2.20 [CI, 1.36-3.56] for intermediate and unfavorable, respectively) only slightly less than from those of the unadjusted comparisons (1.13 [CI, 0.72-1.77] and 2.37 [CI, 1.47-3.82]). After accounting for the effects of age and cytogenetic risk group, none of the other factors contributed significantly to the prognosis for survival from CR, suggesting that the effect of risk status could not be attributed to other factors. Disease-free survival The analysis of DFS gave essentially the same results as the analysis of survival from CR, with no significant heterogeneity of DFS among the treatment arms (P = .079), highly significant heterogeneity among cytogenetic risk groups (P < .0001), and an interaction between the effects of risk status and treatment assignment (P = .017 after accounting for differences between risk groups).Comparison of SWOG and MRC cytogenetic classifications The SWOG and MRC cytogenetic risk classifications were identical for 503 patients but differed for 106 patients (Table 9). Eighty patients coded as unfavorable by SWOG were coded as favorable (9 patients) or intermediate (71 patients) by MRC criteria. Consequently, the proportion of patients with unfavorable karyotypes was markedly smaller according to the MRC criteria (17%, compared with 30% using SWOG criteria). All 26 patients who were not classified in the SWOG scheme were coded intermediate in the MRC scheme. Analyses similar to those described above were performed with the patients classified according to the MRC rather than SWOG criteria. Results of the 2 sets of analyses were generally similar (results not shown).
As shown in Table 9, patients were classified into 6 of the 12 possible combinations of SWOG and MRC categories. In logistic regression analysis of CR rates, the loss of fit associated with collapsing the 6 combined categories into the 4 SWOG categories was highly significant (P = .0001), but that associated with the MRC classification was only marginally significant (P = .030). This comparatively poor fit of the SWOG system occurred largely because it classified as unfavorable 67 patients in the MRC intermediate group with a CR rate of 67% and classified 8 in the MRC favorable group with a CR rate of 100%. Proportional hazards regression models for survival and DFS were examined in an analogous manner. For OS, significant loss of fit was observed for both the SWOG (P = .0067) and MRC (P = .0004) classification schemes (results not shown). In similar analyses of survival from CR, there was no significant loss of fit for the SWOG classification (P = .29) but significant loss of fit for the MRC scheme (P = .0020). In summary, the MRC scheme provided a better prognostic model for CR, and the SWOG scheme provided a better model for survival from CR. Both schemes were deficient at predicting OS. Analyses of the joint effects of MRC risk classification and postremission treatment were not pursued, because only 23 of the 43 remitting patients in the MRC unfavorable group were registered for postremission therapy (9 alloBMT, 6 ABMT, and 8 chemotherapy).
The results described above suggest that cytogenetic characteristics present at diagnosis are associated not only with response to induction therapy for adult AML but also with outcomes of postremission therapy. This analysis was based on information obtained in a large multicenter trial for adult patients with previously untreated AML. The strengths of this trial included its large number of patients, well-defined eligibility criteria (including pretreatment cytogenetic studies), uniform treatment regimens for induction and postremission therapies, and stratification by karyotype category in the randomization between ABMT and chemotherapy. However, this trial also presented some key limitations for analysis. Many remitting patients (36%) were not registered for postremission therapy on study, and the number registered (263 patients) was rather small for comparisons involving 3 treatment arms and 3 or 4 cytogenetic groups. Other disadvantages were the relatively high proportion (26%) of patients who were registered for postremission therapy but did not receive their assigned treatments and, also, the fact that this proportion varied among treatment arms and cytogenetic groups. As reported previously, compared with chemotherapy patients, relatively fewer transplant patients received their protocol postremission therapy, and their times to initiation of posttransplantation therapy were significantly longer in the transplant arms.9 The present analysis showed that the proportion receiving protocol postremission therapy also decreased with worsening cytogenetic risk status. These differences may reflect greater caution by physicians awaiting the patient's complete recovery from induction therapy before starting intensive transplant regimens and may reflect greater risk of early relapse (before starting postremission therapy) among patients with unfavorable cytogenetics. As a result, differences in postremission outcomes between treatment arms cannot be attributed with certainty to the treatment regimens. Instead, in this intent-to-treat analysis, the differences reflect the combined effects of treatment and the likelihood that assigned treatment will be received. The proportion of favorable alloBMT patients who received their assigned treatment was 84%, almost as high as the proportion receiving chemotherapy (95%), with fewer patients receiving their planned treatment in the autologous setting (65%). Nevertheless, the transplant patients had better survival after CR, with 5-year estimates more than 60% for either transplant arm, compared with 35% for the chemotherapy arm. These differences must be interpreted with caution in view of their marginal statistical significance (P = .05) amid the large number of comparisons performed in this study. However, these data are consistent with the MRC AML 10 conclusion that the addition of autologous BMT as intensification provides superior DFS for patients with good risk or favorable cytogenetic patients.19 Conversely, several randomized studies comparing these postremission therapies have failed to confirm improvement with ABMT,7-9 including the intergroup treatment trial of this investigation.9 Although a meta-analysis of these randomized trials might assist in defining the best postremission therapy in cytogenetically defined subgroups of AML, the lack of standardization among investigators may confound the analysis. The cytogenetic risk classification defined all patients with
inv(16)/t(16;16) or t(15;17) as favorable, regardless of additional abnormalities. As a result, 7 patients in the favorable group had
complex abnormalities in addition to inv(16)/t(16;16) or t(15;17). Two
of the 7 had inv(16)/t(16;16) along with Although all-trans-retinoic acid was not available at the time this study was initiated, few patients with t(15;17) would currently be treated without its addition. Accordingly, we performed analyses of the good risk group (n = 121) with and without the inclusion of the 27 t(15;17) patients (results not shown). The results were quantitatively unchanged by their exclusion. The pattern of outcomes in the intermediate risk group differed from that of the favorable group, with the ABMT arm having the poorest survival, with an estimated 36% probability 5 years after CR, compared with more than 50% for the alloBMT and chemotherapy arms (P = .076). The intermediate risk group is heterogeneous, including a large proportion of patients with normal karyotypes (88%), with the remainder having a variety of abnormalities, including loss of a sex chromosome without additional aberrations, or other uncommon karyotypic aberrations with unknown prognostic significance. More extensive molecular analyses may help to identify prognostic tumor markers for both stratification and detection of minimal residual disease in these patients. Patients with karyotypically normal AML represent a heterogeneous population. Caligiuri et al detected submicroscopic duplications of the MLL gene in about 10% of karyotypically normal AML patients.20 Newer molecular cytogenetic techniques have detected additional clonal aberrations not resolvable by classic cytogenetics, in both karyotypically normal and abnormal leukemia cases.21-23 These techniques have revealed abnormalities that would, if detected by classical methods, have resulted in the reclassification of some patients from intermediate risk to the unfavorable risk category.21,23 The prognostic significance of these abnormalities when they are present but undetectable by classical cytogenetics is currently unknown. Further molecular characterization may be useful in defining effective treatment modalities specific for the various patient subpopulations that compose the intermediate risk group. In the unfavorable group, heterogeneity among the 3 postremission treatment arms was not statistically significant (P = .11), although patients appeared to benefit when treated with alloBMT, (P = .043 compared with ABMT and chemotherapy arms combined). The alloBMT arm had an estimated 44% probability of surviving 5 years after CR, compared with 15% or less in the chemotherapy and ABMT arms. This difference was observed even though the proportion of patients actually receiving their assigned postremission treatment was much higher in the chemotherapy arm (90%) than the transplant arms (52% for ABMT, 58% for alloBMT). The observation that patients with poor-risk cytogenetics appear to have a better OS and DFS after HLA-matched sibling transplants suggests that alloBMT using alternative donors might be considered for such patients without matched siblings. Additional investigation of the unfavorable risk group suggested that further prognostic subdivision of this group may be possible. In particular, only 37% of the 33 patients with chromosome 5 or 7 aberrations in a complex karyotype achieved CR, and all 33 died within 2.5 years. These data emphasize the need for novel treatment strategies for the karyotypically complex leukemias bearing chromosome 5 and 7 aberrations. Direct comparisons of cytogenetic data among published reports are compromised by the inconsistent definitions of selected aberrations, in particular, del(9q) or 11q23 aberrations, complex karyotypes, or the inclusion or exclusion of particular chromosome aberrations such as t(15;17) in the prognostic subgroupings. In addition, groups vary somewhat in their definitions of response criteria. Despite these differences, the cytogenetic data presented in this study were analyzed using 2 different classification schemes, which differed in the classification of 17% of the patients. Our rationale to perform this analysis was to describe the differences and similarities used by different cooperative groups to guide future investigations. The MRC coding appeared to separate the patients into 3 groups with a wider range of CR rates than did SWOG criteria. In particular, by moving a number of patients from the unfavorable to the intermediate risk group and moving the rare aberrations from unknown to intermediate, the MRC coding appears to more effectively identify patients with low CR rate (44%, compared with 55% for those in the SWOG unfavorable risk category). This shift resulted in a lower CR rate in the more heterogeneous intermediate risk group, and it limited the number of unfavorable risk patients randomized to postremission treatment. Conversely, the SWOG scheme was superior in predicting survival from CR. Interestingly, both schemes were deficient at predicting OS, suggesting the need for a more robust classification scheme to tighten treatment correlates in genetically defined AML subsets. In this adult AML study, 11q23 aberrations were coded as unfavorable based on their wide reported CR range of 25% to 83% and their overall poor survival.1 Similarly, the German AML cooperative group coded 11q23 aberrations as unfavorable.6 In contrast, the MRC AML 10 trial coded 11q23 aberrations as intermediate risk.10 In pediatric AML, the Pediatric Oncology Group has described an unfavorable outcome for 11q23 leukemias, with an overall 4-year event-free survival rate of 23.8%,2 whereas others have reported a more favorable outcome.24 This inconsistency in outcome may result from the multiplicity of 11q23 aberrations resulting in different fusion partners, variable molecular rearrangements (balanced rearrangements vs deletions vs truncated chimeric transcripts), or the presence of additional cytogenetic or genetic alterations imparting a prognostic impact, all potentially influencing disease course. Leukemias characterized by del(9q) may follow a similar pattern. Schoch et al15 reported that the additional aberration of del(9q) in t(8;21) leukemia imparts an unfavorable outcome, with a significantly shorter median OS, compared with patients with t(8;21) with or without loss of a sex chromosome (12.5 months vs median survival not reached, P = .0010). Because only 17 patients had del(9q) in the present study, definitive conclusions cannot be drawn; however, the data suggest an intermediate/unfavorable risk rather than favorable, with a CR rate of 71% (12 of 17 patients; 95% CI, 44%-90%). Twelve of the 17 patients died, with a median survival of 20 months and 5-year survival of 27% (95% CI, 5%-49%). A recent analysis of del(9q) using pooled data from 3 MRC AML trials suggests that OS at 5 years among patients with del(9q) varies with its genotypic makeup. Specifically, they report survival of 80%, 36%, and 31% in patients with del(9q) with t(8;21), del(9q) alone, or del(9q) with other abnormalities, respectively.25 Such data suggest that certain cytogenetic aberrations provide general prognostic risk assessment, but complete genotypic characterization will be needed for targeted therapeutic approaches and the possibility of individualized therapy strategies. What is clearly needed is a generally accepted cytogenetic classification system and leukemia cytogenetic database to provide prognostic scoring and real-time data updates, principally for the less frequent and secondary cytogenetic aberrations. Our study suggests that pretreatment cytogenetics is a significant prognostic factor in determining response to induction therapy for AML. More importantly, the relative impact of different postremission therapies may vary according to cytogenetic risk group. Many of the weaknesses associated with current cytogenetic risk assessment are also evident from our study. First, current categorizations vary among different investigators. Second, enormous variability in response remains with current categories. Third, as we break down categories into smaller groups, much larger clinical trials will be required to describe potential differential effects of treatments. We suggest that an extensive, perhaps international, leukemia cytogenetic database with patient demographics, treatment, and clinical outcome data be developed to establish well-defined cytogenetic subgroups using uniform criteria. Further analyses of these cytogenetic subsets, perhaps using array technology, should increase our understanding of leukemogen-esis and define common biologic categories. Just as we can probably lump t(8;21) and inv(16) into a common CBF group, other common groupings may emerge. The adaptation of technologic advances in cytogenetics and integration of molecular biological techniques will most likely enable genetic-based assessments to contribute to understanding the biology of AML and its response to treatment.
We thank Dr Joyce Murata-Collins for her critical review of this manuscript and Ms Trudy Trimmer for her assistance in database management.
The affiliations of the authors participating in this study are given in an Appendix at the end of this article.
Submitted April 6, 2000; accepted August 23, 2000.
Supported in part by Department of Health and Human Services National Institutes of Health grants to the SWOG Leukemia, Leukemia Biology, Cytogenetics, and Stem Cell Transplantation Programs (CA-38926) and to the Eastern Cooperative Leukemia Program (CA-21115, CA-66636, CA-23318). M.L.S. is a member of the City of Hope National Cancer Center program and is supported in part by grants CA-3372 and CA-30206.
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 U.S.C. section 1734.
Reprints: Southwest Oncology Group (SWOG-9034), Operations Office, 14980 Omicron Dr, San Antonio, TX 78245-3217.
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The affiliations of the authors of this study include the City of Hope National Medical Center, Duarte, CA; Southwest Oncology Group Statistical Center, Seattle, WA; University of Miami Sylvester Comprehensive Cancer Center, Miami, FL; Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA; Fred Hutchinson Cancer Research Center, Seattle, WA; Ohio State University, Columbus, OH; Wayne State University, Detroit, MI; Albert Einstein Cancer Center at Montefiore Medical Center, Bronx, NY; University of New Mexico, Albuquerque, NM; Vanderbilt Clinical Laboratory, Nashville, TN; and Rambam Medical Center, Technion, Haifa, Israel; for the Southwest Oncology Group, San Antonio, TX, and the Eastern Cooperative Group, Brookline, MA.
© 2000 by The American Society of Hematology.
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M. D. Radmacher, G. Marcucci, A. S. Ruppert, K. Mrozek, S. P. Whitman, J. W. Vardiman, P. Paschka, T. Vukosavljevic, C. D. Baldus, J. E. Kolitz, et al. Independent confirmation of a prognostic gene-expression signature in adult acute myeloid leukemia with a normal karyotype: a Cancer and Leukemia Group B study Blood, September 1, 2006; 108(5): 1677 - 1683. [Abstract] [Full Text] [PDF]
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P. Paschka, G. Marcucci, A. S. Ruppert, K. Mrozek, H. Chen, R. A. Kittles, T. Vukosavljevic, D. Perrotti, J. W. Vardiman, A. J. Carroll, et al. Adverse Prognostic Significance of KIT Mutations in Adult Acute Myeloid Leukemia With inv(16) and t(8;21): A Cancer and Leukemia Group B Study J. Clin. Oncol., August 20, 2006; 24(24): 3904 - 3911. [Abstract] [Full Text] [PDF]
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C. Schmid, M. Schleuning, R. Schwerdtfeger, B. Hertenstein, E. Mischak-Weissinger, D. Bunjes, S. v. Harsdorf, C. Scheid, U. Holtick, H. Greinix, et al. Long-term survival in refractory acute myeloid leukemia after sequential treatment with chemotherapy and reduced-intensity conditioning for allogeneic stem cell transplantation Blood, August 1, 2006; 108(3): 1092 - 1099. [Abstract] [Full Text] [PDF]
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C. S. Wilson, G. S. Davidson, S. B. Martin, E. Andries, J. Potter, R. Harvey, K. Ar, Y. Xu, K. J. Kopecky, D. P. Ankerst, et al. Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction Blood, July 15, 2006; 108(2): 685 - 696. [Abstract] [Full Text] [PDF]
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S. Faderl, S. Verstovsek, J. Cortes, F. Ravandi, M. Beran, G. Garcia-Manero, A. Ferrajoli, Z. Estrov, S. O'Brien, C. Koller, et al. Clofarabine and cytarabine combination as induction therapy for acute myeloid leukemia (AML) in patients 50 years of age or older Blood, July 1, 2006; 108(1): 45 - 51. [Abstract] [Full Text] [PDF]
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S. S. Farag, K. J. Archer, K. Mrozek, A. S. Ruppert, A. J. Carroll, J. W. Vardiman, M. J. Pettenati, M. R. Baer, M. B. Qumsiyeh, P. R. Koduru, et al. Pretreatment cytogenetics add to other prognostic factors predicting complete remission and long-term outcome in patients 60 years of age or older with acute myeloid leukemia: results from Cancer and Leukemia Group B 8461 Blood, July 1, 2006; 108(1): 63 - 73. [Abstract] [Full Text] [PDF]
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M. Monzo, S. Brunet, A. Urbano-Ispizua, A. Navarro, G. Perea, J. Esteve, R. Artells, M. Granell, J. Berlanga, J. M. Ribera, et al. Genomic polymorphisms provide prognostic information in intermediate-risk acute myeloblastic leukemia Blood, June 15, 2006; 107(12): 4871 - 4879. [Abstract] [Full Text] [PDF]
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F. R. Appelbaum, H. Gundacker, D. R. Head, M. L. Slovak, C. L. Willman, J. E. Godwin, J. E. Anderson, and S. H. Petersdorf Age and acute myeloid leukemia Blood, May 1, 2006; 107(9): 3481 - 3485. [Abstract] [Full Text] [PDF]
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J. M. Pagel, F. R. Appelbaum, J. F. Eary, J. Rajendran, D. R. Fisher, T. Gooley, K. Ruffner, E. Nemecek, E. Sickle, L. Durack, et al. 131I-anti-CD45 antibody plus busulfan and cyclophosphamide before allogeneic hematopoietic cell transplantation for treatment of acute myeloid leukemia in first remission Blood, March 1, 2006; 107(5): 2184 - 2191. [Abstract] [Full Text] [PDF]
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D. E. Hogge, L. Yalcintepe, S.-H. Wong, B. Gerhard, and A. E. Frankel Variant Diphtheria Toxin-Interleukin-3 Fusion Proteins with Increased Receptor Affinity Have Enhanced Cytotoxicity against Acute Myeloid Leukemia Progenitors Clin. Cancer Res., February 15, 2006; 12(4): 1284 - 1291. [Abstract] [Full Text] [PDF]
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Y. Oki, H. M. Kantarjian, X. Zhou, J. Cortes, S. Faderl, S. Verstovsek, S. O'Brien, C. Koller, M. Beran, B. N. Bekele, et al. Adult acute megakaryocytic leukemia: an analysis of 37 patients treated at M.D. Anderson Cancer Center Blood, February 1, 2006; 107(3): 880 - 884. [Abstract] [Full Text] [PDF]
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K. Mrozek and C. D. Bloomfield Chromosome Aberrations, Gene Mutations and Expression Changes, and Prognosis in Adult Acute Myeloid Leukemia Hematology, January 1, 2006; 2006(1): 169 - 177. [Abstract] [Full Text] [PDF]
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G. Marcucci, C. D. Baldus, A. S. Ruppert, M. D. Radmacher, K. Mrozek, S. P. Whitman, J. E. Kolitz, C. G. Edwards, J. W. Vardiman, B. L. Powell, et al. Overexpression of the ETS-Related Gene, ERG, Predicts a Worse Outcome in Acute Myeloid Leukemia With Normal Karyotype: A Cancer and Leukemia Group B Study J. Clin. Oncol., December 20, 2005; 23(36): 9234 - 9242. [Abstract] [Full Text] [PDF]
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S. Schnittger, C. Schoch, W. Kern, C. Mecucci, C. Tschulik, M. F. Martelli, T. Haferlach, W. Hiddemann, and B. Falini Nucleophosmin gene mutations are predictors of favorable prognosis in acute myelogenous leukemia with a normal karyotype Blood, December 1, 2005; 106(12): 3733 - 3739. [Abstract] [Full Text] [PDF]
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R. G. W. Verhaak, C. S. Goudswaard, W. van Putten, M. A. Bijl, M. A. Sanders, W. Hugens, A. G. Uitterlinden, C. A. J. Erpelinck, R. Delwel, B. Lowenberg, et al. Mutations in nucleophosmin (NPM1) in acute myeloid leukemia (AML): association with other gene abnormalities and previously established gene expression signatures and their favorable prognostic significance Blood, December 1, 2005; 106(12): 3747 - 3754. [Abstract] [Full Text] [PDF]
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M. Kalaycio, M. Sekeres, R. Sobecks, L. Rybicki, B. Pohlman, A. Advani, E. Kuczkowski, and B. Bolwell Cytogenetic Classification Systems and Overall Survival Following Bone Marrow Transplant (BMT) for Acute Myelogenous Leukemia (AML). Blood (ASH Annual Meeting Abstracts), November 16, 2005; 106(11): 4500 - 4500. [Abstract]
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R. E. Gale, R. Hills, P. D. Kottaridis, S. Srirangan, K. Wheatley, A. K. Burnett, and D. C. Linch No evidence that FLT3 status should be considered as an indicator for transplantation in acute myeloid leukemia (AML): an analysis of 1135 patients, excluding acute promyelocytic leukemia, from the UK MRC AML10 and 12 trials Blood, November 15, 2005; 106(10): 3658 - 3665. [Abstract] [Full Text] [PDF]
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K. Kojima, M. Konopleva, I. J. Samudio, M. Shikami, M. Cabreira-Hansen, T. McQueen, V. Ruvolo, T. Tsao, Z. Zeng, L. T. Vassilev, et al. MDM2 antagonists induce p53-dependent apoptosis in AML: implications for leukemia therapy Blood, November 1, 2005; 106(9): 3150 - 3159. [Abstract] [Full Text] [PDF]
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E. Jourdan, J.-M. Boiron, N. Dastugue, N. Vey, G. Marit, F. Rigal-Huguet, L. Molina, N. Fegueux, A. Pigneux, C. Recher, et al. Early Allogeneic Stem-Cell Transplantation for Young Adults With Acute Myeloblastic Leukemia in First Complete Remission: An Intent-to-Treat Long-Term Analysis of the BGMT Experience J. Clin. Oncol., October 20, 2005; 23(30): 7676 - 7684. [Abstract] [Full Text] [PDF]
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S. Frohling, C. Scholl, D. G. Gilliland, and R. L. Levine Genetics of Myeloid Malignancies: Pathogenetic and Clinical Implications J. Clin. Oncol., September 10, 2005; 23(26): 6285 - 6295. [Abstract] [Full Text] [PDF]
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L. Bullinger and P. J.M. Valk Gene Expression Profiling in Acute Myeloid Leukemia J. Clin. Oncol., September 10, 2005; 23(26): 6296 - 6305. [Abstract] [Full Text] [PDF]
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C. Schmid, M. Schleuning, G. Ledderose, J. Tischer, and H.-J. Kolb Sequential Regimen of Chemotherapy, Reduced-Intensity Conditioning for Allogeneic Stem-Cell Transplantation, and Prophylactic Donor Lymphocyte Transfusion in High-Risk Acute Myeloid Leukemia and Myelodysplastic Syndrome J. Clin. Oncol., August 20, 2005; 23(24): 5675 - 5687. [Abstract] [Full Text] [PDF]
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G. Marcucci, K. Mrozek, A. S. Ruppert, K. Maharry, J. E. Kolitz, J. O. Moore, R. J. Mayer, M. J. Pettenati, B. L. Powell, C. G. Edwards, et al. Prognostic Factors and Outcome of Core Binding Factor Acute Myeloid Leukemia Patients With t(8;21) Differ From Those of Patients With inv(16): A Cancer and Leukemia Group B Study J. Clin. Oncol., August 20, 2005; 23(24): 5705 - 5717. [Abstract] [Full Text] [PDF]
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H. Tamura, K. Dan, K. Tamada, K. Nakamura, Y. Shioi, H. Hyodo, S.-D. Wang, H. Dong, L. Chen, and K. Ogata Expression of Functional B7-H2 and B7.2 Costimulatory Molecules and Their Prognostic Implications in De novo Acute Myeloid Leukemia Clin. Cancer Res., August 15, 2005; 11(16): 5708 - 5717. [Abstract] [Full Text] [PDF]
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M. S. Tallman, D. G. Gilliland, and J. M. Rowe Drug therapy for acute myeloid leukemia Blood, August 15, 2005; 106(4): 1154 - 1163. [Abstract] [Full Text] [PDF]
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C.-C. Chen, C.-F. Yang, M.-H. Yang, K.-D. Lee, W.-K. Kwang, J.-Y. You, Y.-B. Yu, C.-H. Ho, C.-H. Tzeng, W.-K. Chau, et al. Pretreatment prognostic factors and treatment outcome in elderly patients with de novo acute myeloid leukemia Ann. Onc., August 1, 2005; 16(8): 1366 - 1373. [Abstract] [Full Text] [PDF]
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B. Z. Carter, M. Gronda, Z. Wang, K. Welsh, C. Pinilla, M. Andreeff, W. D. Schober, A. Nefzi, G. R. Pond, I. A. Mawji, et al. Small-molecule XIAP inhibitors derepress downstream effector caspases and induce apoptosis of acute myeloid leukemia cells Blood, May 15, 2005; 105(10): 4043 - 4050. [Abstract] [Full Text] [PDF]
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D. A. Breems, W. L.J. Van Putten, P. C. Huijgens, G. J. Ossenkoppele, G. E.G. Verhoef, L. F. Verdonck, E. Vellenga, G. E. De Greef, E. Jacky, J. Van der Lelie, et al. Prognostic Index for Adult Patients With Acute Myeloid Leukemia in First Relapse J. Clin. Oncol., March 20, 2005; 23(9): 1969 - 1978. [Abstract] [Full Text] [PDF]
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B. Falini, C. Mecucci, E. Tiacci, M. Alcalay, R. Rosati, L. Pasqualucci, R. La Starza, D. Diverio, E. Colombo, A. Santucci, et al. Cytoplasmic Nucleophosmin in Acute Myelogenous Leukemia with a Normal Karyotype N. Engl. J. Med., January 20, 2005; 352(3): 254 - 266. [Abstract] [Full Text] [PDF]
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K. K. Ballen and R. P. Hasserjian Case 2-2005 - A 39-Year-Old Woman with Headache, Stiff Neck, and Photophobia N. Engl. J. Med., January 20, 2005; 352(3): 274 - 283. [Full Text] [PDF]
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S. S. Farag, A. S. Ruppert, K. Mrozek, R. J. Mayer, R. M. Stone, A. J. Carroll, B. L. Powell, J. O. Moore, M. J. Pettenati, P. R.K. Koduru, et al. Outcome of Induction and Postremission Therapy in Younger Adults With Acute Myeloid Leukemia With Normal Karyotype: A Cancer and Leukemia Group B Study J. Clin. Oncol., January 20, 2005; 23(3): 482 - 493. [Abstract] [Full Text] [PDF]
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J. J. Cornelissen and B. Lowenberg Role of Allogeneic Stem Cell Transplantation in Current Treatment of Acute Myeloid Leukemia Hematology, January 1, 2005; 2005(1): 151 - 155. [Abstract] [Full Text] [PDF]
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S. Castaigne, S. Chevret, E. Archimbaud, P. Fenaux, D. Bordessoule, H. Tilly, T. de Revel, M. Simon, B. Dupriez, M. Renoux, et al. Randomized comparison of double induction and timed-sequential induction to a "3 + 7" induction in adults with AML: long-term analysis of the Acute Leukemia French Association (ALFA) 9000 study Blood, October 15, 2004; 104(8): 2467 - 2474. [Abstract] [Full Text] [PDF]
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G. Marcucci, K. Mrozek, A. S. Ruppert, K. J. Archer, M. J. Pettenati, N. A. Heerema, A. J. Carroll, P. R.K. Koduru, J. E. Kolitz, L. J. Sterling, et al. Abnormal Cytogenetics at Date of Morphologic Complete Remission Predicts Short Overall and Disease-Free Survival, and Higher Relapse Rate in Adult Acute Myeloid Leukemia: Results From Cancer and Leukemia Group B Study 8461 J. Clin. Oncol., June 15, 2004; 22(12): 2410 - 2418. [Abstract] [Full Text] [PDF]
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L. Bullinger, K. Dohner, E. Bair, S. Frohling, R. F. Schlenk, R. Tibshirani, H. Dohner, and J. R. Pollack Use of Gene-Expression Profiling to Identify Prognostic Subclasses in Adult Acute Myeloid Leukemia N. Engl. J. Med., April 15, 2004; 350(16): 1605 - 1616. [Abstract] [Full Text] [PDF]
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P. J.M. Valk, R. G.W. Verhaak, M. A. Beijen, C. A.J. Erpelinck, S. B. v. W. van Doorn-Khosrovani, J. M. Boer, H. B. Beverloo, M. J. Moorhouse, P. J. van der Spek, B. Lowenberg, et al. Prognostically Useful Gene-Expression Profiles in Acute Myeloid Leukemia N. Engl. J. Med., April 15, 2004; 350(16): 1617 - 1628. [Abstract] [Full Text] [PDF]
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P. L. Greenberg, S. J. Lee, R. Advani, M. S. Tallman, B. I. Sikic, L. Letendre, K. Dugan, B. Lum, D. L. Chin, G. Dewald, et al. Mitoxantrone, Etoposide, and Cytarabine With or Without Valspodar in Patients With Relapsed or Refractory Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndrome: A Phase III Trial (E2995) J. Clin. Oncol., March 15, 2004; 22(6): 1078 - 1086. [Abstract] [Full Text] [PDF]
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J. C. Byrd, A. S. Ruppert, K. Mrozek, A. J. Carroll, C. G. Edwards, D. C. Arthur, M. J. Pettenati, J. Stamberg, P. R.K. Koduru, J. O. Moore, et al. Repetitive Cycles of High-Dose Cytarabine Benefit Patients With Acute Myeloid Leukemia and inv(16)(p13q22) or t(16;16)(p13;q22): Results from CALGB 8461 J. Clin. Oncol., March 15, 2004; 22(6): 1087 - 1094. [Abstract] [Full Text] [PDF]
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S. Frohling, R. F. Schlenk, I. Stolze, J. Bihlmayr, A. Benner, S. Kreitmeier, K. Tobis, H. Dohner, and K. Dohner CEBPA Mutations in Younger Adults With Acute Myeloid Leukemia and Normal Cytogenetics: Prognostic Relevance and Analysis of Cooperating Mutations J. Clin. Oncol., February 15, 2004; 22(4): 624 - 633. [Abstract] [Full Text] [PDF]
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J. M. Rowe, D. Neuberg, W. Friedenberg, J. M. Bennett, E. Paietta, A. Z. Makary, J. L. Liesveld, C. N. Abboud, G. Dewald, F. A. Hayes, et al. A phase 3 study of three induction regimens and of priming with GM-CSF in older adults with acute myeloid leukemia: a trial by the Eastern Cooperative Oncology Group Blood, January 15, 2004; 103(2): 479 - 485. [Abstract] [Full Text] [PDF]
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R. M. Stone, M. R. O'Donnell, and M. A. Sekeres Acute Myeloid Leukemia Hematology, January 1, 2004; 2004(1): 98 - 117. [Abstract] [Full Text] [PDF]
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C. Schoch, S. Schnittger, M. Klaus, W. Kern, W. Hiddemann, and T. Haferlach AML with 11q23/MLL abnormalities as defined by the WHO classification: incidence, partner chromosomes, FAB subtype, age distribution, and prognostic impact in an unselected series of 1897 cytogenetically analyzed AML cases Blood, October 1, 2003; 102(7): 2395 - 2402. [Abstract] [Full Text] [PDF]
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C. D. Baldus, S. M. Tanner, A. S. Ruppert, S. P. Whitman, K. J. Archer, G. Marcucci, M. A. Caligiuri, A. J. Carroll, J. W. Vardiman, B. L. Powell, et al. BAALC expression predicts clinical outcome of de novo acute myeloid leukemia patients with normal cytogenetics: a Cancer and Leukemia Group B Study Blood, September 1, 2003; 102(5): 1613 - 1618. [Abstract] [Full Text] [PDF]
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S. Suciu, F. Mandelli, T. de Witte, R. Zittoun, E. Gallo, B. Labar, G. De Rosa, A. Belhabri, R. Giustolisi, R. Delarue, et al. Allogeneic compared with autologous stem cell transplantation in the treatment of patients younger than 46 years with acute myeloid leukemia (AML) in first complete remission (CR1): an intention-to-treat analysis of the EORTC/GIMEMAAML-10 trial Blood, August 15, 2003; 102(4): 1232 - 1240. [Abstract] [Full Text] [PDF]
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Abstract
Introduction
3 unrelated karyotypic differences in SWOG vs 
