Abstract

Whites have a more favorable prognosis than African Americans for a number of cancers. The relationship between race and outcome is less clear in acute myeloid leukemia (AML). Using data from 7 Cancer and Leukemia Group B studies initiated from 1985 to 1997, we conducted a retrospective cross-sectional analysis of 2570 patients (270 African American and 2300 white) with de novo AML who received induction chemotherapy. African Americans were younger than whites (48 versus 54 years, P < .001). African Americans also had different cytogenetic risk group distributions than whites (P < .001): they were more commonly classified in the favorable (23% versus 14%) and unfavorable (31% versus 23%) groups, and less commonly classified in the intermediate group (47% versus 63%). African American men had a lower complete remission (CR) rate (54%, compared with 64% for white men, 65% for white women, and 70% for African American women, P = .001) and a worse overall survival compared with all other patients (P = .004), when known risk factors are taken into account. African Americans and whites with AML differ with respect to important prognostic factors. African American men have worse CR rates and overall survival than whites and African American women, and should be considered a poor-risk group.

Appendix: CALGB members

The CALGB is chaired by Richard L. Schilsky.


Institution
 

Principal investigator
 
Main member institutions  
   Dana-Farber Partners Cancer Care   George Canellos  
   Dartmouth Medical School - Norris Cotton Cancer Center   Marc Ernstoff  
   Duke University Medical Center   Jeffrey Crawford  
   Georgetown University Medical Center, Lombardi Cancer Center   Edward P. Gelmann  
   Memorial Sloan-Kettering Cancer Center   Clifford A. Hudis  
   Mount Sinai School of Medicine   Lewis Silverman  
   North Shore - Long Island Jewish Health System   Daniel Budman  
   The Ohio State University Medical Center   Clara D. Bloomfield  
   Rhode Island Hospital   William Sikov  
   Roswell Park Cancer Institute   Ellis Levine  
   SUNY Upstate Medical University   Stephen L. Graziano  
   University of California at San Diego   Stephen Seagren  
   University of California at San Francisco   Alan Venook  
   University of Chicago Medical Center   Gini Fleming  
   University of Illinois at Chicago   Thomas Lad  
   University of Iowa Hospitals   Gerald Clamon  
   University of Maryland Cancer Center   Martin Edelman  
   University of Massachusetts Medical Center   Pankaj Bhargava  
   University of Minnesota   Bruce Peterson  
   University of Missouri/Ellis Fischel Cancer Center   Michael Perry  
   University of Nebraska Medical Center   Anne Kessinger  
   University of North Carolina at Chapel Hill   Thomas Shea  
   Vermont Cancer Center   Hyman Muss  
   Wake Forest University School of Medicine   David D. Hurd  
   Walter Reed Army Medical Center   Joseph J. Drabeck  
   Washington University School of Medicine   Nancy Bartlett  
   Weill Medical College of Cornell University   Scott Wadler  
At large institutions/CCOPs  
   Cedars-Sinai Medical Center   Alan T. Lefor  
   Christiana Care Health Services, Inc   Stephen Grubbs  
   McGill University   Gerald Batist  
   Missouri Baptist Medical Center   Alan P. Lyss  
   Mount Sinai Medical Center - Miami   Rogerio Lilenbaum  
   Northern Indiana Cancer Research CCOP   Rafat Ansari  
   Southern Nevada Cancer Research Foundation   John Ellerton  
   Southeast Cancer Control Consortium, Inc   James N. Atkins  
   Syracuse Hematology-Oncology Associates   Jeffrey Kirshner  
   University of Texas Southwestern Medical Center   Debasish Tripathy  
   Van Andel Research Institute   George F. Vande Woude  
   Western Pennsylvania Cancer Institute   Richard K. Shadduck  
   Baptist Cancer Institute CCOP   Lee S. Schwartzberg  
   Evanston Northwestern Healthcare CCOP   Gershon Y. Locker  
   Grand Rapids Clincal Oncology Program CCOP   Kathleen J. Yost  
   Greenville CCOP   Jeffrey K. Giguere  
   Illinois Oncology Research Association CCOP   John W. Kugler  
   Kansas City Community Clincal Oncology Program CCOP   Jorge C. Paradelo  
   Massey Cancer Center MBCCOP
 
John D. Roberts
 

Institution
 

Principal investigator
 
Main member institutions  
   Dana-Farber Partners Cancer Care   George Canellos  
   Dartmouth Medical School - Norris Cotton Cancer Center   Marc Ernstoff  
   Duke University Medical Center   Jeffrey Crawford  
   Georgetown University Medical Center, Lombardi Cancer Center   Edward P. Gelmann  
   Memorial Sloan-Kettering Cancer Center   Clifford A. Hudis  
   Mount Sinai School of Medicine   Lewis Silverman  
   North Shore - Long Island Jewish Health System   Daniel Budman  
   The Ohio State University Medical Center   Clara D. Bloomfield  
   Rhode Island Hospital   William Sikov  
   Roswell Park Cancer Institute   Ellis Levine  
   SUNY Upstate Medical University   Stephen L. Graziano  
   University of California at San Diego   Stephen Seagren  
   University of California at San Francisco   Alan Venook  
   University of Chicago Medical Center   Gini Fleming  
   University of Illinois at Chicago   Thomas Lad  
   University of Iowa Hospitals   Gerald Clamon  
   University of Maryland Cancer Center   Martin Edelman  
   University of Massachusetts Medical Center   Pankaj Bhargava  
   University of Minnesota   Bruce Peterson  
   University of Missouri/Ellis Fischel Cancer Center   Michael Perry  
   University of Nebraska Medical Center   Anne Kessinger  
   University of North Carolina at Chapel Hill   Thomas Shea  
   Vermont Cancer Center   Hyman Muss  
   Wake Forest University School of Medicine   David D. Hurd  
   Walter Reed Army Medical Center   Joseph J. Drabeck  
   Washington University School of Medicine   Nancy Bartlett  
   Weill Medical College of Cornell University   Scott Wadler  
At large institutions/CCOPs  
   Cedars-Sinai Medical Center   Alan T. Lefor  
   Christiana Care Health Services, Inc   Stephen Grubbs  
   McGill University   Gerald Batist  
   Missouri Baptist Medical Center   Alan P. Lyss  
   Mount Sinai Medical Center - Miami   Rogerio Lilenbaum  
   Northern Indiana Cancer Research CCOP   Rafat Ansari  
   Southern Nevada Cancer Research Foundation   John Ellerton  
   Southeast Cancer Control Consortium, Inc   James N. Atkins  
   Syracuse Hematology-Oncology Associates   Jeffrey Kirshner  
   University of Texas Southwestern Medical Center   Debasish Tripathy  
   Van Andel Research Institute   George F. Vande Woude  
   Western Pennsylvania Cancer Institute   Richard K. Shadduck  
   Baptist Cancer Institute CCOP   Lee S. Schwartzberg  
   Evanston Northwestern Healthcare CCOP   Gershon Y. Locker  
   Grand Rapids Clincal Oncology Program CCOP   Kathleen J. Yost  
   Greenville CCOP   Jeffrey K. Giguere  
   Illinois Oncology Research Association CCOP   John W. Kugler  
   Kansas City Community Clincal Oncology Program CCOP   Jorge C. Paradelo  
   Massey Cancer Center MBCCOP
 
John D. Roberts
 

Introduction

Acute myeloid leukemia (AML) is a malignant disorder arising through the acquisition of genetic mutations in hematopoietic stem or progenitor cells,2  resulting in impairment of hematopoiesis and unrestrained proliferation of an immature clone. In the United States, the annual population incidence of AML in whites is 3.7 cases per 100 000 people, whereas in African Americans it is 2.9 cases per 100 000 people.3 

For a number of cancers, particularly cancers of the colon, breast, and prostate, whites have a more favorable prognosis than African Americans in the United States.4-11  The relationship between race and outcome is less clear in leukemia. African American children with acute lymphoblastic leukemia (ALL) are less likely to achieve remission and have an inferior disease-free and overall survival compared with white children with the same disease.12,13  One recent study from the Children's Cancer Group examined racial and ethnic differences in children with ALL and found that black children were overrepresented in high-risk characteristic groups and had a worse outcome compared with white children.14  Although data concerning incidence and outcome in AML according to race or ethnic group are sparse, Latinos appear to have a higher prevalence of one of the better-risk subtypes, acute promyelocytic leukemia (APL) (French-American-British [FAB] classification M3).15-17  It is unclear whether racial differences in subtypes and outcome in leukemia result from environmental or cultural influences,17  differences in genetics, or variability in reporting at diagnosis and/or follow-up.14 

Surveillance, Epidemiology, and End Result (SEER) Program data indicate that the age-adjusted mortality rate for AML is slightly higher in whites compared with African Americans (2.5 versus 2.0 per 100 000 US population).3  The age adjustment is important, as whites are diagnosed at a median of 67 years, while the median for African Americans is 60 years. It is not known whether AML-specific mortality differences between the 2 races exist nationwide.18  In addition, racespecific death rates do not control for other prognostic factors, including cytogenetics and AML subtype.

Disparate cancer outcomes between races often are attributed to differential access to care, varying treatment aggressiveness and compliance, and biologic variability.5,6,8,11,13,19-21  Even if differential access to care and treatment aggressiveness are eliminated as potential confounders in describing racial differences in outcome for AML (as should occur within a cooperative group study), biologic variability may still play a role.22,23 

Using data from Cancer and Leukemia Group B (CALGB) AML studies initiated from 1985 to 1997, we compared baseline prognostic factors, treatment-related complications, and outcome in African American and white patients receiving similar therapy for AML.

Patients, materials, and methods

Study population

We conducted a retrospective cross-sectional study of 2570 patients with de novo AML who were eligible to receive intensive chemotherapy as part of 1 of 7 CALGB studies: CALGB 8525, 8923, 9022, 9222, 9420, and 9621, and the initial 120 patients of CALGB 9720, the only study that allowed patients with prior myelodysplastic syndrome (MDS) or patients who had received prior cytotoxic chemotherapy to be included.24-31  Patients identified their own race, and those who were classified as being neither white nor African American (221 patients) were excluded from our analyses. Patients with APL were included in CALGB 8525, 9022, 9222, and the majority of the enrollment period for 8923, but excluded from the other, more recent studies.

Treatment and clinical data

Patients were treated with the use of protocol guidelines for study entry, treatment compliance, and therapy. Induction therapy included cytarabine (Ara-C) and daunorubicin; patients in some studies also received etoposide (VP-16) as a third agent. Postremission therapy varied by protocol (Table 1). Clinical data collected at the CALGB Statistical Center (Durham, NC) on most patients included age; sex; CALGB performance status; evidence of extramedullary leukemia; baseline complete blood counts; FAB type; immunophenotype (available on 554 patients [22%]); number of induction courses; response to induction; complete remission (CR) rates (which followed accepted criteria)32 ; disease-free survival (DFS) (defined as the interval from attainment of a CR or randomization to postremission therapy to the date of relapse, the date of death from any cause, or the date the patient was last known to be in remission); and overall survival (OS), which included patients who did not attain a CR. Median follow-up time for patients was 7.3 years (interquartile range, 3.0-10.4 years).

Table 1.

Summary of included trials


 

Treatment protocol
 
      

 
8525a
 
8923b
 
9022c
 
9222d
 
9420e
 
9621f
 
9720g
 
Years of patient accrual   10/85-10/90   2/90-11/93   10/90-3/92   7/92-12/95   1/95-7/97   2/97-3/00   1/98-3/99  
Trial phase   3   3   2   3   1   1/2   3  
Patientsh        
   Total   1036   360   213   407   103   340   111  
   White, no. (%)   920 (89)   334 (93)   192 (90)   354 (87)   94 (91)   301 (89)   105 (95)  
   African American, no. (%)   116 (11)   26 (7)   21 (10)   53 (13)   9 (9)   39 (11)   6 (5)  
   Cytogenetics available, no. (%)   563 (54)   210 (58)   124 (58)   269 (66)   62 (60)   270 (79)   82 (74)  
Induction 1l  Yes   Yesi  Yes   Yes   Yesj  Yesj  Yesj 
Etoposide used in inductions 1 (and 2, if needed)   No   No   No   No   Yes: 60 or 100 mg/m2/d × 3 days   Yes: 60-150 mg/m2/d × 3 days   Yes: 60 or 100 mg/m2/d × 3 days  
Induction 2, if needed   Yes   Yes   Yes   Yes   Yesk  Yesk  Yesk 
Intensification or consolidation therapy randomized, by arm  Yes, arms A, B, C   Yes, arms A, B   No   Yes, arms A, B   No   Yes, risk-adapted, arms A, B   No  
   Intensification or consolidation therapy 1, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: M + IDAC   HDAC   A: HDAC; B: HDAC   5 + 2 + 2   A:HDAC; B: HDAC + E   5 + 2 + 2  
   Intensification or consolidation therapy 2, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: M + IDAC   E + C   A: HDAC; B: E + C   -   A: HDAC; B: SCT   -  
   Intensification or consolidation therapy 3, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: None   M + D   A: HDAC; B: M + D   -   A: HDAC; B: None   -  
   Intensification or consolidation therapy 4, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: None   -   -   -   -   -  
Maintenance therapy
 
Yes
 
No
 
No
 
No
 
Yes
 
Yes
 
Yes
 

 

Treatment protocol
 
      

 
8525a
 
8923b
 
9022c
 
9222d
 
9420e
 
9621f
 
9720g
 
Years of patient accrual   10/85-10/90   2/90-11/93   10/90-3/92   7/92-12/95   1/95-7/97   2/97-3/00   1/98-3/99  
Trial phase   3   3   2   3   1   1/2   3  
Patientsh        
   Total   1036   360   213   407   103   340   111  
   White, no. (%)   920 (89)   334 (93)   192 (90)   354 (87)   94 (91)   301 (89)   105 (95)  
   African American, no. (%)   116 (11)   26 (7)   21 (10)   53 (13)   9 (9)   39 (11)   6 (5)  
   Cytogenetics available, no. (%)   563 (54)   210 (58)   124 (58)   269 (66)   62 (60)   270 (79)   82 (74)  
Induction 1l  Yes   Yesi  Yes   Yes   Yesj  Yesj  Yesj 
Etoposide used in inductions 1 (and 2, if needed)   No   No   No   No   Yes: 60 or 100 mg/m2/d × 3 days   Yes: 60-150 mg/m2/d × 3 days   Yes: 60 or 100 mg/m2/d × 3 days  
Induction 2, if needed   Yes   Yes   Yes   Yes   Yesk  Yesk  Yesk 
Intensification or consolidation therapy randomized, by arm  Yes, arms A, B, C   Yes, arms A, B   No   Yes, arms A, B   No   Yes, risk-adapted, arms A, B   No  
   Intensification or consolidation therapy 1, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: M + IDAC   HDAC   A: HDAC; B: HDAC   5 + 2 + 2   A:HDAC; B: HDAC + E   5 + 2 + 2  
   Intensification or consolidation therapy 2, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: M + IDAC   E + C   A: HDAC; B: E + C   -   A: HDAC; B: SCT   -  
   Intensification or consolidation therapy 3, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: None   M + D   A: HDAC; B: M + D   -   A: HDAC; B: None   -  
   Intensification or consolidation therapy 4, by arm   A: SDAC; B: IDAC; C: HDAC   A: SDAC; B: None   -   -   -   -   -  
Maintenance therapy
 
Yes
 
No
 
No
 
No
 
Yes
 
Yes
 
Yes
 

SDAC indicates 100 mg/m2 cytarabine by ci every day × 5 days; IDAC, 400 mg/m2 cytarabine by ci every day × 5 days; HDAC, 3 g/m2 cytarabine by intravenous bolus (ivb) over 3 hours every 12 hours on days 1, 3 and 5; HDAC + E, 2 mg/m2 cytarabine by ivb over 2 hours every 12 hours on days 1-4 and 40 mg/kg etoposide by ci every day for 4 days; M + IDAC, 5 mg/m2 mitoxantrone every 12 hours and 500 mg/m2 cytarabine every 12 hours for 6 doses each; E + C, 1800 mg/m2 etoposide by ci day 1 plus 50 mg/kg cyclophosphamide ivb on days 2 and 3; M + D, 12 mg/m2 mitoxantrone ivb plus 24 mg/m2 diaziquone by ci days 1, 2, and 3 plus 5 μg/kg filgrastim subcutaneously days 4 through 28; 5 + 2 + 2, 100 mg/m2 cytarabine by continuous infusion every day × 5 days plus 2 days of daunorubicin and etoposide at doses equivalent to those received in induction 1, ± PSC 833. Maintenance therapy for study 8525 consisted of 45 mg/m2 daunorubicin ivb on day 1 plus 100 mg/m2 cytarabine subcutaneously every 12 hours on days 1 through 5 repeated monthly × 4; for studies 9420, 9621, and 9720, maintenance therapy consisted of interleukin-2 as specified by Farag et al30  and Baer et al.31  ivp indicates intravenous push; SCT, stem cell transplantation; and -, not applicable.

a

Mayer et al.24 

b

Stone et al.25,36 

c

Moore et al.26 

d

Moore et al.27 

e

Lee et al.28 

f

Kolitz et al.29 

g

Baer et al.31 

h

Patient population data are as follows: total, N = 2570; white, n = 2300 (89.5% of total); African American, n = 270 (10.5% of total); and cytogenetics available, n = 1580 (61% of total)

i

50% of enrolled patients received granulocyte-macrophage colony-stimulating factor (GM-CSF) during induction

j

Patients in 9420 received daunorubicin at doses ranging from 30 to 60 mg/m2/d × 3 days and also received the multidrug resistance modulator PSC 833 at a loading dose of 1.5 mg/kg and a continuous infusion of 10 mg/kg/d for 3 days; patients in 9621 received daunorubicin at doses ranging from 40 to 90 mg/m2/d × 3 days depending on their randomization to PSC 833 at a loading dose of 2.8 mg/kg and a continuous infusion of 10 mg/kg/d for 3 days; patients in 9720 received daunorubicin at doses of 40 or 60 mg/m2/d × 3 days depending on their randomization to PSC 833 at a loading dose of 2.8 mg/kg and a continuous infusion of 10 mg/kg/d for 3 days

k

Doses were equivalent to those received in induction 1. Patients receiving PSC 833 for induction 1 received it for induction 2 over 2 days

l

Induction 1 consisted of daunorubicin 45 mg/m2 ivp × 3 days and cytarabine 100 or 200 mg/m2 by continuous infusion (ci) × 7 days. Induction 2, which was administered if needed, consisted of daunorubicin 45 mg/m2 ivp × 2 days and cytarabine 100 or 200 mg/m2 by ci × 5 days

Cytogenetic data

Centrally reviewed cytogenetic data were available on 1580 patients (61%) in the study sample who were enrolled on CALGB 8461, a prospective cytogenetics study initiated in 1984.33  Specimens were obtained at diagnosis from all patients and were processed with the use of unstimulated short-term cultures, a direct method, or both. G-banding was usually done, although Q-banding was also acceptable. At least 20 marrow metaphase cells were analyzed in patients designated as having a normal karyotype.

Cytogenetic risk groups were classified by the schema developed by CALGB for overall survival,33  as follows: favorable risk cytogenetics included t(8;21), inv(16), or t(16;16); intermediate risk cytogenetics included a normal karyotype, del (9q), -Y, del(5q), loss of 7q, t(9;11), +11, del(11q), abn(12p), +13, del(20q), and +21. Unfavorable cytogenetics included complex (3 or more abnormalities) karyotypes, inv(3) or t(3;3), t(6;9), t(6;11), -7, +8, and t(11;19)(q23;p13.1). Of the 1580 patients, 89 individuals with t(15;17) (indicative of APL) or t(9;22) (suggestive of the blastic phase of chronic myelogenous leukemia) were analyzed separately, as these were thought to represent distinct AML subtypes. An additional 108 patients with karyotypes that included single nonrecurring structural abnormalities, or cytogenetic abnormalities that were found in fewer than 5 patients, were also excluded from the cytogenetic risk stratification, leaving 1383 patients stratified into 1 of the 3 cytogenetic risk groups. Immunophenotyping was performed by multiparameter flow cytometry, as previously described.34 

Statistical analysis

Descriptive statistics, including proportions, medians, and 5-year time-to-event probabilities, were used to summarize the distribution of variables within subgroups. The Fisher exact test was used to describe the associations in 2 × 2 and 2 × 3 contingency tables. Kaplan-Meier plots35  and the log-rank test were used to examine difference in overall survival and DFS. The proportional hazards model was used to model both OS and DFS as a function of demographic, clinical, and cytogenetic risk group (ie, the 3-level variable described in Table 4). Likewise, the logistic regression model was used to model CR rate as a function of this same set of variables.

Table 4.

Percentage of whites and African Americans with each cytogenetic abnormality


Risk group
 

Whites, n (%)
 

African Americans, n (%)
 

Total, n (%)
 

P
 
Favorable     
   t(8;21)   72 (5.8)   24 (17.0)   96 (7.0)   < .0001  
   inv(16) or t(16;16)   101 (8.1)   8 (5.7)   109 (7.9)   .40  
Intermediate     
   Normal   644 (51.9)   53 (37.5)   697 (50.6)   .0014  
   del(9q)   34 (2.7)   5 (3.5)   39 (2.8)   .59  
   t(9;11)   31 (2.5)   3 (2.1)   34 (2.5)   1.0  
   del(5q)   51 (4.1)   8 (5.7)   59 (4.3)   .38  
   loss of 7q   23 (1.9)   5 (3.5)   28 (2.0)   .20  
   +11   25 (2.0)   3 (2.1)   28 (2.0)   .76  
   del(11q)   9 (0.7)   1 (0.7)   10 (0.7)   1.0  
   abn(12p)   38 (3.1)   6 (4.3)   44 (3.2)   .44  
   +13   32 (2.6)   5 (3.5)   37 (2.7)   .42  
   del(20q)   14 (1.1)   2 (1.4)   16 (1.2)   .67  
   +21   36 (2.9)   1 (0.7)   37 (2.7)   .17  
   -Y   44 (3.5)   7 (5.0)   51 (3.7)   .35  
Unfavorable     
   Complex, 3 or more abn   131 (10.5)   18 (12.8)   149 (10.8)   .30  
   inv(3) or t(3;3)   18 (1.5)   1 (0.7)   19 (1.4)   .71  
   t(6;9)   7 (0.6)   3 (2.1)   10 (0.7)   .07  
   t(6;11)   7 (0.6)   4 (2.8)   11 (0.8)   .02  
   -7   37 (3.0)   5 (3.6)   42 (3.0)   .61  
   +8   139 (11.2)   22 (15.6)   161 (11.7)   .13  
   t(11;19) (q23;p13.1)
 
9 (0.7)
 
0 (0)
 
9 (0.7)
 
.61
 

Risk group
 

Whites, n (%)
 

African Americans, n (%)
 

Total, n (%)
 

P
 
Favorable     
   t(8;21)   72 (5.8)   24 (17.0)   96 (7.0)   < .0001  
   inv(16) or t(16;16)   101 (8.1)   8 (5.7)   109 (7.9)   .40  
Intermediate     
   Normal   644 (51.9)   53 (37.5)   697 (50.6)   .0014  
   del(9q)   34 (2.7)   5 (3.5)   39 (2.8)   .59  
   t(9;11)   31 (2.5)   3 (2.1)   34 (2.5)   1.0  
   del(5q)   51 (4.1)   8 (5.7)   59 (4.3)   .38  
   loss of 7q   23 (1.9)   5 (3.5)   28 (2.0)   .20  
   +11   25 (2.0)   3 (2.1)   28 (2.0)   .76  
   del(11q)   9 (0.7)   1 (0.7)   10 (0.7)   1.0  
   abn(12p)   38 (3.1)   6 (4.3)   44 (3.2)   .44  
   +13   32 (2.6)   5 (3.5)   37 (2.7)   .42  
   del(20q)   14 (1.1)   2 (1.4)   16 (1.2)   .67  
   +21   36 (2.9)   1 (0.7)   37 (2.7)   .17  
   -Y   44 (3.5)   7 (5.0)   51 (3.7)   .35  
Unfavorable     
   Complex, 3 or more abn   131 (10.5)   18 (12.8)   149 (10.8)   .30  
   inv(3) or t(3;3)   18 (1.5)   1 (0.7)   19 (1.4)   .71  
   t(6;9)   7 (0.6)   3 (2.1)   10 (0.7)   .07  
   t(6;11)   7 (0.6)   4 (2.8)   11 (0.8)   .02  
   -7   37 (3.0)   5 (3.6)   42 (3.0)   .61  
   +8   139 (11.2)   22 (15.6)   161 (11.7)   .13  
   t(11;19) (q23;p13.1)
 
9 (0.7)
 
0 (0)
 
9 (0.7)
 
.61
 

Number of patients tested were as follows: whites, n = 1242; African Americans, n = 141; total, n = 1383. Abnormalities are ordered in this table according to the way in which they were used to form cytogenetic risk groups. Percentages do not sum up to 100% because patients could have more than one abnormality.

Our major interest was race differences in prognostic factors and clinical outcomes; this focus was narrowed when large clinical differences between African American men and others emerged. The covariates used in the tests of African American male effects included age, M3 status, white blood cell (WBC) count, and cytogenetic risk group. As slightly more than 1000 patients did not have cytogenetic information, we first controlled only for age, M3 status, and WBC count. Then cytogenetic risk group was added to the model, and we observed if there was any change in the race or African American male regression coefficient. As the addition of cytogenetic risk group had minimal impact on the regression coefficient, or the regression coefficient became even larger, covariate-adjusted results are reported for the control of only age, M3, and WBC count. Controlling for individual cytogenetic abnormalities had no impact on the association between race/sex and the clinical endpoints. A 2-sided alpha level of 0.05 was used for all tests; as a large number of tests were performed, those of borderline significance should be interpreted with caution. Statistical analyses were performed at the CALGB Statistical Center.

Results

Clinical and biologic characteristics at study entry

Of the 2570 patients included in our analysis, 270 (10.5%) were African American and 2300 (89.5%) were white. The distribution of patients by study is summarized in Table 1. There were no significant differences in the percentage of African American men and women represented in each study.

Overall, baseline characteristics were similar in the 2 groups (Table 2). However, African Americans were younger, with a median age of 48 years compared with 54 years for whites (P < .001), and were more likely to be female (58% versus 46%, P < .001). African Americans also had more leukemic involvement of the central nervous system (CNS) at diagnosis (2% versus 1%, P = .04), but were less likely to have skin involvement (4% versus 8%, P = .02) than whites.

Table 2.

Baseline characteristics


Characteristic
 

Whites, N = 2300
 

African Americans, N = 270
 

P
 
Median age, y  54   48   < .001  
   Minimum   16   17   
   Maximum   86   86   
Sex, n (%)    < .001  
   Men   1233 (54)   114 (42)   
   Women   1067 (46)   156 (58)   
Performance status, n (%)    .21  
   0   673 (30)   67 (25)   
   1   1015 (45)   117 (44)   
   2   431 (19)   59 (22)   
   3   111 (5)   16 (6)   
   4   28 (1)   6 (2)   
Extramedullary leukemia, n (%)    
   Liver     .91  
      No   2041 (90)   239 (91)   
      Yes   215 (10)   24 (9)   
   Spleen     .73  
      No   2051 (91)   244 (92)   
      Yes   203 (9)   22 (8)   
   CNS     .04  
      No   2236 (99)   261 (98)   
      Yes   14 (≤ 1)   5 (2)   
   PNS     .72  
      No   2255 (99)   267 (> 99)   
      Yes   14 (≤ 1)   1 (< 1)   
   Nodes     .44  
      No   1968 (87)   226 (85)   
      Yes   291 (13)   39 (15)   
   Skin     .02  
      No   2086 (92)   258 (96)   
      Yes   170 (8)   10 (4)   
   Gum     .76  
      No   2002 (89)   235 (88)   
      Yes   255 (11)   32 (12)   
   Mass     .73  
      No   2237 (99)   265 (99)   
      Yes   20 (1)   3 (1)   
Median WBC count, × 109/L  13 700   16 300   .39  
   Minimum   100   300   
   Maximum   560 000   301 000   
Median platelet level, × 109/L  54 000   57 000   .52  
   Minimum   4000   2000   
   Maximum   1 200 000   426 000   
Median Hgb level, g/L  92   90   .59  
   Minimum   28   35   
   Maximum   149   150   
Histology, FAB, n (%)    .04  
   M0   49 (2)   9 (3)   
   M1   497 (22)   52 (19)   
   M2   678 (29)   84 (31)   
   M3   144 (6)   31 (11)   
   M4   539 (23)   61 (23)   
   M5   251 (11)   19 (7)   
   M6   70 (3)   6 (2)   
   M7   13 (1)   1 (< 1)   
   Other   24 (1)   3 (1)   
   Missing
 
35 (2)
 
4 (1)
 

 

Characteristic
 

Whites, N = 2300
 

African Americans, N = 270
 

P
 
Median age, y  54   48   < .001  
   Minimum   16   17   
   Maximum   86   86   
Sex, n (%)    < .001  
   Men   1233 (54)   114 (42)   
   Women   1067 (46)   156 (58)   
Performance status, n (%)    .21  
   0   673 (30)   67 (25)   
   1   1015 (45)   117 (44)   
   2   431 (19)   59 (22)   
   3   111 (5)   16 (6)   
   4   28 (1)   6 (2)   
Extramedullary leukemia, n (%)    
   Liver     .91  
      No   2041 (90)   239 (91)   
      Yes   215 (10)   24 (9)   
   Spleen     .73  
      No   2051 (91)   244 (92)   
      Yes   203 (9)   22 (8)   
   CNS     .04  
      No   2236 (99)   261 (98)   
      Yes   14 (≤ 1)   5 (2)   
   PNS     .72  
      No   2255 (99)   267 (> 99)   
      Yes   14 (≤ 1)   1 (< 1)   
   Nodes     .44  
      No   1968 (87)   226 (85)   
      Yes   291 (13)   39 (15)   
   Skin     .02  
      No   2086 (92)   258 (96)   
      Yes   170 (8)   10 (4)   
   Gum     .76  
      No   2002 (89)   235 (88)   
      Yes   255 (11)   32 (12)   
   Mass     .73  
      No   2237 (99)   265 (99)   
      Yes   20 (1)   3 (1)   
Median WBC count, × 109/L  13 700   16 300   .39  
   Minimum   100   300   
   Maximum   560 000   301 000   
Median platelet level, × 109/L  54 000   57 000   .52  
   Minimum   4000   2000   
   Maximum   1 200 000   426 000   
Median Hgb level, g/L  92   90   .59  
   Minimum   28   35   
   Maximum   149   150   
Histology, FAB, n (%)    .04  
   M0   49 (2)   9 (3)   
   M1   497 (22)   52 (19)   
   M2   678 (29)   84 (31)   
   M3   144 (6)   31 (11)   
   M4   539 (23)   61 (23)   
   M5   251 (11)   19 (7)   
   M6   70 (3)   6 (2)   
   M7   13 (1)   1 (< 1)   
   Other   24 (1)   3 (1)   
   Missing
 
35 (2)
 
4 (1)
 

 

CNS indicates central nervous system; PNS, peripheral nervous system; and Hgb, hemoglobin.

The FAB classification at study entry also differed between races (P = .04). African Americans were more likely than whites to have a diagnosis of M3 (acute promyelocytic) leukemia (11% versus 6%, P = .003), but less likely to have a diagnosis of M5 (monocytic) leukemia, with a trend toward significance (7% versus 11%, P = .06). These differences persisted when age was controlled for.

Flow cytometry data were available for 62 African Americans (23%) and 492 whites (21%). Human leukocyte antigen DR (HLA-DR) was expressed on myeloblasts from African Americans less frequently than on blasts from whites (73% versus 85%, P = .02), as would be expected from the FAB classification data. Other cell surface antigen expression was similar in the 2 groups.

Baseline cytogenetic data were available for 168 African Americans (62%) and 1412 whites (61%) (Table 3). African Americans were more likely than whites to have a t(15;17), the translocation associated with APL (8.3% versus 4.7%, respectively, P = .06) and a t(9;22) (1.8% versus 0.4%, P = .06), though numbers were small. There were 1383 patients (141 African Americans and 1242 whites) who were classifiable into favorable, intermediate, or unfavorable cytogenetic risk score groups. African Americans had significantly different cytogenetic risk group distributions than whites (P < .001): they were more commonly classified in the favorable (23% versus 14%) and unfavorable (31% versus 23%) risk groups, and less commonly classified in the intermediate group (47% versus 63%).

Table 3.

Cytogenetic characteristics among 1580 patients with adequate karyotypes


Cytogenetic classification
 

Whites, n (%)
 

African Americans, n (%)
 

Total, n (%)
 
t(15;17)*  66 (4.7)   14 (8.3)   80 (5.1)  
t(9;22)*  6 (0.4)   3 (1.8)   9 (0.6)  
Not included in risk group   98 (7)   10 (6)   108 (6.8)  
Included in risk group   1242 (88.0)   141 (83.9)   1383 (87.5)  
Total   1412 (100)   168 (100)   1580 (100)  
Risk group†    
   Favorable   173 (14)   32 (23)   205 (15)  
   Intermediate   786 (63)   66 (47)   852 (62)  
   Unfavorable   283 (23)   43 (31)   326 (24)  
Total
 
1242 (100)
 
141 (100)
 
1383 (100)
 

Cytogenetic classification
 

Whites, n (%)
 

African Americans, n (%)
 

Total, n (%)
 
t(15;17)*  66 (4.7)   14 (8.3)   80 (5.1)  
t(9;22)*  6 (0.4)   3 (1.8)   9 (0.6)  
Not included in risk group   98 (7)   10 (6)   108 (6.8)  
Included in risk group   1242 (88.0)   141 (83.9)   1383 (87.5)  
Total   1412 (100)   168 (100)   1580 (100)  
Risk group†    
   Favorable   173 (14)   32 (23)   205 (15)  
   Intermediate   786 (63)   66 (47)   852 (62)  
   Unfavorable   283 (23)   43 (31)   326 (24)  
Total
 
1242 (100)
 
141 (100)
 
1383 (100)
 
*

P = .06

P = < .001. Two-degrees-of-freedom test of difference between races in risk group distribution

Table 4 shows cytogenetic abnormalities for the 1383 patients classified into 1 of the 3 risk groups. African Americans were more likely than whites to have the favorable t(8;21) (17.0% versus 5.8%, P < .0001). Whites, on the other hand, were more likely to have a normal karyotype (51.9% versus 37.6%, P = .0014). African Americans were more likely to have t(6;9) (2.1% versus 0.6%, P = .07) and t(6;11) (2.8% versus 0.6%, P = .02), both unfavorable cytogenetic abnormalities. There was no difference in the distribution of cytogenetic abnormalities between African American men and women.

Clinical outcome

African American and white AML patients received a similar number of courses of remission induction therapy (Table 5) and had similar treatment-related mortality rates (18% for whites and 16% for African Americans), which did not differ by sex. Induction toxicity did not differ in the 2 races. Whites were more likely to have grade 3 or 4 anemia, however (P = .03).

Table 5.

Overall clinical outcome


 

Whites
 
  
African Americans
 
  
P unadjusted (adjusted)*
 
 
Characteristic
 
Men
 
Women
 
Total
 
Men
 
Women
 
Total
 
Comparing races
 
For AA men
 
Induction courses, n (%)         
   1   867 (70)   788 (74)   1655 (72)   87 (76)   111 (71)   198 (73)   .67   .34  
   2   366 (30)   279 (26)   645 (28)   27 (24)   45 (29)   72 (27)   (.35)   (.24)  
Response to induction, n (%)         
   CR   783 (64)   698 (65)   1481 (64)   61 (54)   109 (70)   170 (63)   .64   .01  
   NR/death   450 (37)   369 (35)   819 (36)   53 (46)   47 (30)   100 (37)   (.10)   (.001)  
Disease-free survival         
   5-year probability   0.26   0.27   0.26   0.27   0.21   0.21   .09   .21  
   Standard error   0.016   0.107   0.123   0.058   0.041   0.033   (.02)   (.08)  
Overall survival         
   5-year probability   0.24   0.26   0.25   0.16   0.26   0.22   .19   .04  
   Standard error
 
0.013
 
0.014
 
0.009
 
0.036
 
0.036
 
0.026
 
(.009)
 
(.004)
 

 

Whites
 
  
African Americans
 
  
P unadjusted (adjusted)*
 
 
Characteristic
 
Men
 
Women
 
Total
 
Men
 
Women
 
Total
 
Comparing races
 
For AA men
 
Induction courses, n (%)         
   1   867 (70)   788 (74)   1655 (72)   87 (76)   111 (71)   198 (73)   .67   .34  
   2   366 (30)   279 (26)   645 (28)   27 (24)   45 (29)   72 (27)   (.35)   (.24)  
Response to induction, n (%)         
   CR   783 (64)   698 (65)   1481 (64)   61 (54)   109 (70)   170 (63)   .64   .01  
   NR/death   450 (37)   369 (35)   819 (36)   53 (46)   47 (30)   100 (37)   (.10)   (.001)  
Disease-free survival         
   5-year probability   0.26   0.27   0.26   0.27   0.21   0.21   .09   .21  
   Standard error   0.016   0.107   0.123   0.058   0.041   0.033   (.02)   (.08)  
Overall survival         
   5-year probability   0.24   0.26   0.25   0.16   0.26   0.22   .19   .04  
   Standard error
 
0.013
 
0.014
 
0.009
 
0.036
 
0.036
 
0.026
 
(.009)
 
(.004)
 

Patient populations are as follows: white men, N = 1233; white women, N = 1067; total whites, N = 2300; African American men, N = 114; African American women, N = 156; and total African Americans, N = 270.

*

Adjusted P values control for age, M3 status, and white blood cell count

P values for comparison of African Americans to whites

P values for comparison of African American men to others

African American men had a significantly lower CR rate than all other patients when age, M3, and WBC count are controlled for (P = .001). African American men had a CR rate of 54% (n = 114) as compared with the much higher CR rates of 64% (n = 1233) for white men, 65% (n = 1067) for white women, and 70% (n = 156) for African American women. Differences persisted when cytogenetic risk group is controlled for.

While there was a significant difference between the races in OS when age, M3, and WBC count are controlled for (P = .009), this difference was due almost entirely to the poorer survival of African American men compared with all other patients (P = .004). Figure 1 shows Kaplan-Meier curves demonstrating survival by race and sex, and predicted survival curves after age, M3, and WBC count are controlled for. There was also a small, but significant difference between the races in DFS (P = .02). Controlling for cytogenetic risk group had negligible impact on OS or DFS.

Figure 1.

Survival by race and sex. (A) Unadjusted results (Kaplan-Meier plot). P = .04 for unadjusted comparison of survival of African American men with all other groups. (B) Adjusted results (log-rank test). P = .004 for comparison of survival of African American men with all other groups. AAF indicates African American women (n = 156); AAM, African American men (n = 114); WF, white women (n = 1067); and WM, white men (n = 1233).

Figure 1.

Survival by race and sex. (A) Unadjusted results (Kaplan-Meier plot). P = .04 for unadjusted comparison of survival of African American men with all other groups. (B) Adjusted results (log-rank test). P = .004 for comparison of survival of African American men with all other groups. AAF indicates African American women (n = 156); AAM, African American men (n = 114); WF, white women (n = 1067); and WM, white men (n = 1233).

Survival within subgroups favored whites. Within FAB subgroups, this survival difference was statistically significant only within the M4 subtype of AML, for which African Americans had a median survival of 0.8 years, compared with the 1.3 year median survival for whites (P = .004). Within cytogenetic risk groups, African Americans with favorable cytogenetics had a median survival of 2.1 years, compared with 5.6 years for whites (P = .42). Similar patterns were found in those with intermediate (1.0 versus 1.3 years, P = .10) and unfavorable (0.3 versus 0.6 years, P = .96) risk cytogenetic cohorts. Looking at specific cytogenetic abnormalities within cytogenetic subgroups shows that African Americans with a t(15;17) lived a median of 2.1 years, compared with 2.4 years for whites (P = .73), while those with a t(8;21) survived a median of 3.1 years, compared with 5.1 years for whites (P = .89). African Americans with complex karyotypes had a dismal survival (a median of 0.2 years), but survival was also quite poor for whites (a median of 0.5 years, P = .31).

Discussion

Patients with AML receive similar treatment regimens consisting of an anthracycline or anthracenedione and cytarabine, regardless of race. In general, modifications to this therapy are introduced under the following circumstances: (1) patients with an advanced age or poor health or multiple comorbidities may choose nonintensive or palliative therapy; (2) patients with the FAB subtype M3 AML, associated with the t(15;17), now receive additional all-trans retinoic acid; or (3) in patients with a particularly poor prognosis, a hematopoietic stem cell transplantation (SCT) may be considered, age and health permitting, once remission is achieved. The results of our study indicate that African Americans, particularly African American men, are more likely than whites to fall into the latter category and that African Americans have worse overall survival than whites when the 2 groups were given similar initial therapies.

We pooled data from 7 CALGB AML treatment studies conducted over 14 years to compare African American and white patients with respect to prognostic variables and outcome. African Americans represented 10.5% of study patients, a number that approaches the proportion of African Americans 18 years or older in the United States, 11.4%, as determined by US Census Bureau data.37 

Prognostic variables differed in the 2 groups. The percentage of African Americans with the favorable FAB subtype M3 AML (APL) was almost twice that of whites (and correlated to the percentage with a t(15;17)). African Americans also were 3 times as likely to have the favorable-risk t(8;21). Whites, on the other hand, were more likely to have a normal karyotype (51.9% of cytogenetic findings, compared with only 37.5% of findings in African Americans). The explanation for this difference is not apparent. Patients with APL were excluded from the more contemporary studies (as the use of differentiation agents became standard practice) and may have been overrepresented in earlier studies (which excluded patients with antecedent MDS, which rarely precedes APL). Thus, the prevalence of APL in this study (6.8%) cannot be thought of as representative of the population, and rates in each race may have been skewed. It is also possible that African Americans with favorable morphology, such as the FAB subtype M3 AML, were preferentially referred to CALGB study sites for therapy. African Americans with “nonnormal” cytogenetics may have more environmental exposures that predispose them to cancer and bone marrow stem cell disorders compared with whites.38,39  This may account for the increased incidence of unfavorable cytogenetics in this group, which occurs in pediatric ALL.40  There may also be a genetic predisposition to certain favorable chromosomal rearrangements.

Perhaps more importantly, a new prognostic variable emerged. In both unadjusted and adjusted analyses, African American men had lower rates of complete remission and overall survival than any other group. This difference cannot be explained by other prognostic factors, which were controlled for; by treatment-related toxicities, which were similar in both ethnic groups; or by differences in therapies, as all patients were treated on CALGB trials and received a similar number of remission induction courses. While it is possible that African American men did not receive similar postremission therapy (eg, they may not have undergone an SCT owing to lack of a donor, as unrelated donors are less common in this population),41,42  their CR rates also were significantly lower than those in any other group, which would predict for a worse survival regardless of postremission therapy. Information regarding SCT following CR1 or in first relapse was not routinely collected. However, the number of patients who underwent an SCT in CR1 was small, as few patients were removed from these treatment trials to undergo an SCT, and this procedure would have been highly unlikely in studies focusing on AML in older adults (CALGB studies 8923, 9420, and 9720). Moreover, where such SCT information was collected, we would be concerned about systematic information bias. This finding of a worse outcome in African American men with AML is similar to what has been found in studies of men with colon cancer43,44  and may be due to biologic heterogeneity and/or differential drug metabolism and variable efficacy, as would occur with myeloblast expression of MDR1 or an FLT3 internal tandem duplication, and merits further study.

This study has several potential limitations. It is a cooperative group study involving patients who qualified for clinical trials, who were on average younger than the median age at AML diagnosis in the United States, and were less likely to have antecedent MDS or to have therapy-related AML. Thus, these results may not be generalizable to the entire population of patients with AML. One key advantage of this design is the assurance that virtually every patient received identical initial therapy; thus, the study controls for therapy intensity as a potential confounder. In addition, we did not have data regarding socioeconomic status, and thus could not evaluate this known risk factor for poor outcome in patients with cancer.5,45  One future direction would involve performing a population-based study, enabling prospective comparisons of patients of different races, complete follow-up, and testing the generalizability of information about patients enrolled in cooperative group studies. This would allow enhanced examination of racial differences in older patients, and in patients with antecedent stem cell disorders or treatment-related AML.

In conclusion, African Americans and whites with AML differ with respect to some important prognostic factors. African American men have worse CR rates and overall survival than whites and African American women. These findings support more research concerning the specific biologic features as well as the development of novel therapeutic approaches in African American men, who should be considered a poor risk group. In addition, it should be recognized that African Americans are more likely than whites to present with good-risk AML (including APL or AML with a t(8;21)), and appropriate therapy should be initiated early. Future population-based studies should try to define these racial differences further by prospectively focusing on differential environmental exposure rates; differences in drug metabolism and bioavailability; and rates of therapy compliance, toxicities, and access to remission induction and postremission therapy, including SCT.

Prepublished online as Blood First Edition Paper, February 19, 2004; DOI 10.1182/blood-2003-09-3118.

A complete list of the members of the Cancer and Leukemia Group B appears in the “Appendix.”

The research for CALGB 10401 was supported, in part, by grants from the National Cancer institute (CA3946) to the Cancer and Leukemia Group B. The CALGB Statistical Office, Durham, NC, is supported by CA33601. Support for cytogenetics data and for C.D.B. comes from National Institutes of Health grants CA16058, CA101140, CA31946, and CA77658, and from the Coleman Leukemia Research Fund.

Richard K. Dodge died on August 24, 2002.

Presented in part at the 44th annual meeting of the American Society of Hematology, Philadelphia, PA, December 9, 2002.1 

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.

The authors thank the patients, investigators, nurses, and data managers who participated in these clinical trials. The authors also wish to thank Brian J. Bolwell, MD, for critical review of the manuscript, and A. David McCollum, MD, for assistance with study design. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the views of the National Cancer Institute.

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