To study the characteristics and clinical impact of therapy-related acute myeloid leukemia (t-AML). 200 patients (7.0%) had t-AML and 2653 de novo AML (93%). Patients with t-AML were older (P < .0001) and they had lower white blood counts (P = .003) compared with de novo AML patients; t-AML patients had abnormal cytogenetics more frequently, with overrepresentation of 11q23 translocations as well as adverse cytogenetics, including complex and monosomal karyotypes, and with underrepresentation of intermediate-risk karyotypes (P < .0001); t-AML patients had NPM1 mutations (P < .0001) and FLT3 internal tandem duplications (P = .0005) less frequently. Younger age at diagnosis of primary malignancy and treatment with intercalating agents as well as topoisomerase II inhibitors were associated with shorter latency periods to the occurrence of t-AML. In multivariable analyses, t-AML was an adverse prognostic factor for death in complete remission but not relapse in younger intensively treated patients (P < .0001 and P = .39, respectively), relapse but not death in complete remission in older, less intensively treated patients (P = .02 and P = .22, respectively) and overall survival in younger intensively treated patients (P = .01). In more intensively treated younger adults, treatment-related toxicity had a major negative impact on outcome, possibly reflecting cumulative toxicity of cancer treatment.

Therapy-related acute myeloid leukemia (t-AML) is a recognized clinical syndrome occurring as a complication after cytotoxic and/or radiation therapy.1-3  At present, approximately 10% of all AMLs arise after a patient's exposure to chemotherapy and/or radiation for a primary malignancy or autoimmune disease.4,5  Patients with t-AML are considered to have an inferior outcome compared with de novo AML.2,3,5  The latency period between diagnosis of the primary disease and occurrence of t-AML ranges between several months to several years and may depend on the cumulative dose, dose intensity, and type of preceding chemotherapy and/or radiation therapy.2,3 

With respect to cytogenetics, t-AML more frequently have abnormal cytogenetics; in particular, they have an increased prevalence of adverse-risk karyotypes.5-7  At present, few data exist regarding the frequency of gene mutations.7  Chromosomal aberrations in t-AML are thought to be the consequence of mutational events induced by previous therapy.8  Hematopoietic progenitor cells, that survive with acquired mutations caused by non- or misrepair, are at risk for leukemic transformation and finally result in overt AML. Some patients may have an inherited susceptibility for the development of t-AML.8-10 

Depending on the chemotherapeutic agent and/or radiation, 2 subtypes of t-AML can be distinguished. The most common subtype, occurring after exposure to alkylating agents and/or radiation with a latency period of 5-10 years, is frequently accompanied by unbalanced cytogenetic abnormalities, such as loss of all or parts of chromosomes 5 and/or 7.5,11-14  The second less common subtype, arising after treatment with agents targeting topoisomerase II, has shorter latency period of 1-5 years and frequently exhibits balanced chromosomal rearrangements involving MLL, RUNX1, and PML-RARA.5,7,15,16  However, because in recent years most patients have received treatment with both alkylating agents and drugs that target topoisomerase II for previous malignancy, a discrimination according to the type of previous therapy is often not feasible. Therefore, in the current World Health Organization (WHO) classification therapy-related myeloid neoplasms are no longer subcategorized.

Because pretreatment cytogenetic and molecular aberrations are the most powerful prognostic parameters for clinical outcome in de novo AML,17,18  the question arises whether the diagnosis of t-AML itself indicates a poor prognosis or whether the inferior outcome results from the association with an adverse genetic risk profile. So far, only a few authors have evaluated the characteristics and clinical impact of t-AML, in particular in the context of other clinical and biologic prognostic markers. The objective of our study was to evaluate the characteristics and clinical impact of t-AML in a large cohort of adult AML patients treated within prospective multicenter treatment trials.

Patients

Patients were enrolled on 6 prospective multicenter treatment trials of the German-Austrian AML Study Group (AMLSG) between 1993 and September 2008. All patients received age-adapted intensive induction and consolidation therapy as previously described (AML HD9319 ; APL9520 ; AML HD98A21 ; AML HD98B22 ; AMLSG 06-04, NCT00151255; AMLSG 07-04; NCT00151242). Treatments were significantly less intensive in trials for patients older than 60 years of age. In all trials patients with t-AML were eligible if they had completed therapy for the previous malignancy, had no active disease, and were considered by their physician to be at low risk of relapse. The studies were approved by the institutional review boards of all the participating centers. All patients gave informed consent for treatment and for cytogenetic and molecular genetic analyses according to the Declaration of Helsinki. The diagnosis of AML was based on French-American-British Cooperative Group criteria23  for the trials AML HD93, AML HD98A, and AML HD98B and after 2004 on WHO 2001 criteria24  for the trials AMLSG 07-04 and AMLSG 06-04.

Cytogenetic and molecular genetic analysis

All leukemia samples were studied centrally in the reference laboratories of the AMLSG at the University of Ulm and at Hannover Medical School. Chromosome banding was performed by the use of standard techniques, and karyotypes were described according to the International System for Human Cytogenetic Nomenclature.25 

Leukemia samples were analyzed for mutations in the FLT3 (FLT3 internal tandem duplication [ITD], n = 2355; FLT3 tyrosine kinase domain mutations at codons D835 and I836, n = 2145), NPM1 (n = 2300), MLL (partial tandem duplication, n = 1804), as well as CEBPA (n = 1091; analysis restricted to cytogenetically normal AML), as previously described.26 

Statistical analyses

The definition of complete remission (CR) or therapeutic failures followed recommended criteria.27  Overall survival (OS), relapse-free survival (RFS), cumulative incidence of relapse (CIR), and cumulative incidence of death in CR (CID) were defined as recommended.27  Cytogenetic categorization into favorable-, intermediate-, and adverse-risk group followed recommended criteria.28  Pairwise comparisons between patient characteristics (covariates) were performed by Mann-Whitney or Kruskal Wallis test for continuous variables and by Fisher exact test for categorical variables.

A multivariable log-normalized linear regression model was used to identify factors that influenced the duration of the latency period, including the covariates type of primary malignancy (solid vs hematologic), sex, type of chemotherapeutic agent (alkylating agent, antimetabolite, antitubulin, intercalating agent, or topoisomerase II inhibitor; Table 1),29-33  and radiation.

Table 1

Classification of chemotherapeutic agents by mechanism of action modified according to Smith et al6 

Mechanism of action/substance groupAgent
Alkylating agents  
    Nitrogen mustard Chlorambucil, cyclophosphamide, ifosfamide, melphalan 
    Nitrosourea Carmustine, lomustine 
    Platinum-based Carboplatin, cisplatin, oxaliplatin 
    Alkylsulfonate Busulfan, treosulfan 
    Hydrazine Procarbazine 
    Triazene Dacarbazine 
    Aziridine Thiotepa 
Antimetabolites  
    Folic acid Methotrexate 
    Purine antagonist Cladribine, clofarabine, fludarabine, mercaptopurine 
    Pyrimidine antagonist Cytarabine, decitabine, azacitidine, fluorouracil, gemcitabine 
Antitubulin  
    Taxane Docetaxel, paclitaxel 
    Vinca alkaloid Vinblastine, vincristine, vindesine, vinorelbine 
Topoisomerase II inhibitors  
    Epipodophyllotoxin Etoposide, teniposide 
Intercalating agents  
    Anthracycline29,30  Daunorubicin, doxorubicin, epirubicin, idarubicin 
    Anthracenedione31,32  Mitoxantrone 
    Streptomyces33  Actinomycin, bleomycin, mitomycin 
Mechanism of action/substance groupAgent
Alkylating agents  
    Nitrogen mustard Chlorambucil, cyclophosphamide, ifosfamide, melphalan 
    Nitrosourea Carmustine, lomustine 
    Platinum-based Carboplatin, cisplatin, oxaliplatin 
    Alkylsulfonate Busulfan, treosulfan 
    Hydrazine Procarbazine 
    Triazene Dacarbazine 
    Aziridine Thiotepa 
Antimetabolites  
    Folic acid Methotrexate 
    Purine antagonist Cladribine, clofarabine, fludarabine, mercaptopurine 
    Pyrimidine antagonist Cytarabine, decitabine, azacitidine, fluorouracil, gemcitabine 
Antitubulin  
    Taxane Docetaxel, paclitaxel 
    Vinca alkaloid Vinblastine, vincristine, vindesine, vinorelbine 
Topoisomerase II inhibitors  
    Epipodophyllotoxin Etoposide, teniposide 
Intercalating agents  
    Anthracycline29,30  Daunorubicin, doxorubicin, epirubicin, idarubicin 
    Anthracenedione31,32  Mitoxantrone 
    Streptomyces33  Actinomycin, bleomycin, mitomycin 

The Kaplan-Meier method was used to estimate the distribution of RFS and OS.34  Confidence interval estimation for the survival curves was determined by the cumulative hazard function with the use of the Greenwood formula for the standard error estimation. A Cox model was used to identify prognostic variables.35  CIR and CID and their standard errors (SEs) were analyzed according to the method described by Gray36  and included only patients attaining CR, with time calculated from the date of CR to the occurrence of an event (relapse or death). Prognostic Cox regression models were used for the end points of relapse and death in CR as well as for OS. All models included a variable accounting for different treatment intensities in younger (age 18-60 years) versus older patients (age > 60 years). In all multivariable models no variable selection was performed, and full models were presented. We estimated missing data for covariates by using 50 multiple imputations in chained equations incorporating predictive mean matching.37  There was no difference in clinical outcome (CR, CIR, CID, and OS) between patients with missing data and those with complete datasets (P = .13, P = .12, P = .17, and P = .51, respectively). All statistical analyses were performed with the statistical software environment R Version 2.10.1, by use of the R packages rms Version 2.1-0, and cmprsk Version 2.2-0.38 

Patient cohort

In total, 3177 adult AML patients (median age, 54.5 years) were enrolled on 6 prospective treatment trials. In 3026 (95.2%) patients information on type of AML was available: 200 t-AML, 2653 de novo AML, and 173 AML with a history of a myelodysplastic syndrome (MDS) or myeloproliferative neoplasm at least 3 months before diagnosis of AML.39  The subgroup of de novo AML patients included 77 patients with a history of a neoplasm but without previous chemotherapy or radiation. Patients with missing data on type of AML and patients with a history of MDS/myeloproliferative neoplasm without chemotherapy were excluded from this study.

Presenting clinical, cytogenetic, and molecular genetic features

Compared with patients with de novo AML, patients with t-AML were older (57.8 vs 53.2 years; P < .0001), and women were more frequently affected than men (P < .0001), mainly because of the high frequency of t-AML after treatment of breast cancer. t-AML was associated with lower median white blood counts (P = .003), lower platelet counts (P = .02), greater hemoglobin levels (P = .04), and lower percentages of blasts in peripheral blood (P = .002) and bone marrow (P = .03; Table 2).

Table 2

Comparison of presenting clinical and laboratory findings between patients with therapy-related (t-AML) and de novo AML

Characteristict-AMLde novo AMLP
Patients, no. (%) 200 (7.0) 2653 (93.0)  
Sex, male/female, no. (%) 64 (32)/136 (68) 1409 (53)/1244 (47) < .0001 
Median age, y (range) 57.8 (18.6-79.4) 53.2 (16.2-85.0) < .0001 
WBC, × 109/L   .003 
    Median 7.4 12.5  
    Range 0.4-258 0.1-527  
    Missing 51 58  
Hemoglobin, g/dL   .04 
    Median 9.4 9.1  
    Range 4.2-13.7 2.5-20.6  
    Missing 60  
Platelet count, × 109/L   .02 
    Median 50.5 55  
    Range 2-595 4-933  
    Missing 60  
PB blasts, %   .002 
    Median 22 35  
    Range 0-100 0-100  
    Missing 20 244  
BM blasts, %   .03 
    Median 65 75  
    Range 2-100 0-100  
    Missing 17 246  
LDH value, U/L   .09 
    Median 372 413  
    Range 90-15 098 40-7627  
    Missing 108  
Characteristict-AMLde novo AMLP
Patients, no. (%) 200 (7.0) 2653 (93.0)  
Sex, male/female, no. (%) 64 (32)/136 (68) 1409 (53)/1244 (47) < .0001 
Median age, y (range) 57.8 (18.6-79.4) 53.2 (16.2-85.0) < .0001 
WBC, × 109/L   .003 
    Median 7.4 12.5  
    Range 0.4-258 0.1-527  
    Missing 51 58  
Hemoglobin, g/dL   .04 
    Median 9.4 9.1  
    Range 4.2-13.7 2.5-20.6  
    Missing 60  
Platelet count, × 109/L   .02 
    Median 50.5 55  
    Range 2-595 4-933  
    Missing 60  
PB blasts, %   .002 
    Median 22 35  
    Range 0-100 0-100  
    Missing 20 244  
BM blasts, %   .03 
    Median 65 75  
    Range 2-100 0-100  
    Missing 17 246  
LDH value, U/L   .09 
    Median 372 413  
    Range 90-15 098 40-7627  
    Missing 108  

Percentages may not add to 100 because of rounding.

AML indicates acute myeloid leukemia; BM, bone marrow; LDH, serum lactate dehydrogenase; PB, peripheral blood; and WBC, white blood count.

Compared with de novo AML, t-AML more frequently had abnormal karyotypes (75% vs 51%, P < .0001; Table 3, Figure 1). The distribution among cytogenetic risk categories differed significantly between t-AML and de novo AML. Whereas there was no difference in the frequency of favorable-risk abnormalities, t-AML was underrepresented in intermediate-risk cases but more frequently exhibited adverse-risk karyotypes. t-AML more frequently had -5 or 5q− (P = .005), -7 (P = .008), 7q− (P = .001), t(9;11) (P = .0001), t(v;11)(v;q23) (P = .07, in trend), abnl(17p) (P < .0001), complex karyotypes (P < .0001), and monosomal karyotypes (P < .0001; defined according to Breems et al40 ); in contrast, t-AML less frequently had normal karyotype (P < .0001), and in trend (P = .06) trisomy 8 within a noncomplex karyotype (Table 3). Figure 2 shows the comparison of t-AML and de novo AML patients exhibiting at least one cytogenetic abnormality, with the exclusion of the WHO category “AML with recurrent genetic abnormalities.”1  Trisomy 8 in t-AML was frequently associated with a complex karyotype, whereas in de novo AML, trisomy 8 was the most frequent abnormality within a noncomplex karyotype. Regarding molecular aberrations, both NPM1 mutations and FLT3-ITD were significantly less frequent in t-AML (P < .0001 and P = .0005, respectively; Table 3).

Table 3

Comparison of cytogenetic and molecular genetic abnormalities between patients with therapy-related (t-AML) and de novo AML

Genetic groupt-AML
de novo AML
P
No.%No.%
Abnormal 136 75 1207 51 < .0001 
Normal 46 25 1174 49 < .0001 
Missing 18  272   
Risk category*      
    Favorable 28 15 369 16 > .999 
    Intermediate 83 46 1552 65 < .0001 
    Adverse 71 39 460 19 < .0001 
Cytogenetic abnormalities      
    t(15;17) 99 .24 
    t(8;21) 128 > .999 
    inv(16) or t(16;16) 15 142 .20 
    t(9;11) 20 11 35 < .0001 
    t(v;11)(v;q23) 52 .07 
    t(6;9) 19 .39 
    inv(3) or t(3;3) 39 > .999 
    −5 or 5q− 26 14 187 .005 
    −7 20 11 134 .008 
    7q− 18 10 96 .001 
    abnl(17p) 25 14 117 < .0001 
    trisomy 8 109 .06 
    Complex karyotype* 47 26 273 11 < .0001 
    Monosomal karyotype 43 24 246 10 < .0001 
Molecular genetic abnormalities      
    NPM1 mutation 24 16 654 30 < .0001 
    Missing 47  467   
    FLT3-ITD 17 12 521 24 .0005 
    Missing 53  444   
    FLT3-TKD mutation 12 158 .62 
    Missing 69  638   
Genetic groupt-AML
de novo AML
P
No.%No.%
Abnormal 136 75 1207 51 < .0001 
Normal 46 25 1174 49 < .0001 
Missing 18  272   
Risk category*      
    Favorable 28 15 369 16 > .999 
    Intermediate 83 46 1552 65 < .0001 
    Adverse 71 39 460 19 < .0001 
Cytogenetic abnormalities      
    t(15;17) 99 .24 
    t(8;21) 128 > .999 
    inv(16) or t(16;16) 15 142 .20 
    t(9;11) 20 11 35 < .0001 
    t(v;11)(v;q23) 52 .07 
    t(6;9) 19 .39 
    inv(3) or t(3;3) 39 > .999 
    −5 or 5q− 26 14 187 .005 
    −7 20 11 134 .008 
    7q− 18 10 96 .001 
    abnl(17p) 25 14 117 < .0001 
    trisomy 8 109 .06 
    Complex karyotype* 47 26 273 11 < .0001 
    Monosomal karyotype 43 24 246 10 < .0001 
Molecular genetic abnormalities      
    NPM1 mutation 24 16 654 30 < .0001 
    Missing 47  467   
    FLT3-ITD 17 12 521 24 .0005 
    Missing 53  444   
    FLT3-TKD mutation 12 158 .62 
    Missing 69  638   

Percentages may not add to 100 because of rounding.

AML indicates acute myeloid leukemia; ITD, internal tandem duplication; and TKD, tyrosine kinase domain.

*

According to Döhner et al.28 

Outside a complex karyotype.

According to Breems et al.40 

Figure 1

Distribution of cytogenetic abnormalities. Therapy-related AML (n = 179, A) and de novo AML (n = 2363, B; MDS-related cytogenetic abnormalities according to Swerdlow et al1 ).

Figure 1

Distribution of cytogenetic abnormalities. Therapy-related AML (n = 179, A) and de novo AML (n = 2363, B; MDS-related cytogenetic abnormalities according to Swerdlow et al1 ).

Close modal
Figure 2

Frequency and distribution of cytogenetic abnormalities in patients exhibiting at least one abnormality. Excluding the WHO category “AML with recurrent genetic abnormalities”1  (A, t-AML n = 78, B, de novo AML, n = 698; definition “complex” according to Döhner et al28  and of “monosomal karyotype” according to Breems et al40 ).

Figure 2

Frequency and distribution of cytogenetic abnormalities in patients exhibiting at least one abnormality. Excluding the WHO category “AML with recurrent genetic abnormalities”1  (A, t-AML n = 78, B, de novo AML, n = 698; definition “complex” according to Döhner et al28  and of “monosomal karyotype” according to Breems et al40 ).

Close modal

Primary diseases, previous therapy, and latency period to the occurrence of t-AML

The median latency period between diagnosis of primary malignancy and the occurrence of t-AML was 4.04 years (range, 0.33-44.14 years). One hundred forty-two (71%) patients with t-AML had a previous solid cancer (Table 4). Breast cancer was the most common neoplasm (n = 74; 52%), followed by thyroid (n = 12; 8%; all patients had received radioiodine therapy), gastrointestinal (n = 10 patients; 7%), prostate (n = 9; 6%), and testicular cancer (n = 9, 6%). Twenty-eight of 142 (20%) patients had various other neoplasms. Fifty-two (27.5%) patients had a primary hematologic malignancy, with non-Hodgkin lymphoma (n = 25; 46%) and Hodgkin lymphoma (n = 20; 36%) being the most common ones. A total of 10 of the 55 (18%) patients had various other hematologic malignancies (Table 4). Three patients had undergone cytotoxic therapy for the treatment of an autoimmune disease, 2 with multiple sclerosis and 1 with a rheumatologic disorder (Table 4).

Table 4

Primary diseases in t-AML patients

Primary diseaseNo. of patients%
Solid cancers 142 71 
Cancers of females   
    Breast 74 52 
    Cervix 
    Uterus 
    Ovary 
Cancers affecting men   
    Prostate 
    Testis 
Cerebral cancers   
    Glioma 
Head and neck cancers   
    Thyroid 12 
    Larynx 
    Hypopharynx 
    Vocal cord 
Thoracic cancers   
    Lung 
    Mediastinal 
Abdominal cancers   
    Gastrointestinal 10 
    Kidney 
    Bladder 
Skin cancers   
    Melanoma 
    Others 
Bone cancers   
    Ewing sarcoma 
Soft-tissue tumors   
    Histiocytoma 
Hematologic malignancies 55 27.5 
    NHL 25 46 
    Hodgkin lymphoma 20 36 
    MDS* 11 
    ALL 
    AML 1.5 
    MPN 1.5 
Autoimmune diseases 1.5 
    Multiple sclerosis 67 
    Rheumatologic 33 
Primary diseaseNo. of patients%
Solid cancers 142 71 
Cancers of females   
    Breast 74 52 
    Cervix 
    Uterus 
    Ovary 
Cancers affecting men   
    Prostate 
    Testis 
Cerebral cancers   
    Glioma 
Head and neck cancers   
    Thyroid 12 
    Larynx 
    Hypopharynx 
    Vocal cord 
Thoracic cancers   
    Lung 
    Mediastinal 
Abdominal cancers   
    Gastrointestinal 10 
    Kidney 
    Bladder 
Skin cancers   
    Melanoma 
    Others 
Bone cancers   
    Ewing sarcoma 
Soft-tissue tumors   
    Histiocytoma 
Hematologic malignancies 55 27.5 
    NHL 25 46 
    Hodgkin lymphoma 20 36 
    MDS* 11 
    ALL 
    AML 1.5 
    MPN 1.5 
Autoimmune diseases 1.5 
    Multiple sclerosis 67 
    Rheumatologic 33 

ALL indicates acute lymphoblastic leukemia; AML, acute myeloid leukemia; MDS, myelodysplastic syndrome; MPN, myeloproliferative neoplasm; and NHL, non-Hodgkin lymphoma.

*

MDS treated with decitabine, cyclophosphamid, azacitidine, or chemotherapy (unspecified).

t-AML after 9 years of treatment of de novo AML.

In 180 (90%) of the 200 t-AML patients, the treatment records were complete with respect to the treatment modality of primary disease; detailed information on type of chemotherapeutic agents and dosages were available in 148 (74%) of the 200 patients. Sixty-nine patients had previous chemotherapy only, 56 radiation only, and 55 patients had both chemotherapy and radiation. Only 7 patients received single-agent chemotherapy.

Chemotherapeutic agents were classified by mechanism of action (Table 1). In a multivariable log-normalized linear regression model, younger age at diagnosis of primary malignancy (P = .006) as well as administration of intercalating agents (P = .01) and topoisomerase II inhibitors (P = .009) were associated with a shorter latency period between diagnosis of primary malignancy and the occurrence of t-AML. In addition, we were interested in the association of latency period and subsequent cytogenetic abnormality categorized into (1) t(15;17); (2) t(8;21); (3) inv(16) or t(16;16); (4) t(9;11); (5) t(v;11)(v;q23); (6) -7; (7) 7q−; (8) -5 or 5q−; (9) abnl(17p); (10) complex karyotype ≥ 3 abnormalities, and (11) monosomal karyotype. The log-normalized linear regression model revealed that t(9;11) (P = .0006, median, 1.9 years) was associated with a shorter and -5 or 5q− (P = .009; median, 9.3 years) with a prolonged latency period.

To identify an association between different chemotherapeutic agents and induction of specific cytogenetic abnormalities, we performed a multinomial regression analysis in which the outcome variable was categorized as follows: (1) t(15;17); (2) t(8;21); inv(16) or t(16;16); (3) t(9;11) or t(v;11)(v;q23); (4) NPM1; (5) normal karyotype excluding NPM1; (6) -5 or 5q−; -7; 7q−; abnl(17p); and (7) all other abnormalities. This model revealed that treatment with intercalating agents was significantly associated with the induction of cytogenetic abnormalities (P = .01), particularly t(9;11) or t(v;11)(v;q23) (P = .02), and the group all other abnormalities (P = .05).

Latency period and cytogenetic abnormalities in patients with de novo AML and previous malignancy without chemotherapy or radiation

Seventy-seven (3%) of the 2653 de novo AML patients had a history of previous neoplasm who did not receive chemotherapy and/or radiation. These patients were significantly older compared with all other patients with de novo AML (60 vs 53 years; P < .0001). All patients had previous solid cancer, commonly prostate cancer (n = 18, 23%), breast cancer (n = 8, 10%), gastrointestinal cancer (n = 8, 10%), as well as bladder cancer, renal cell carcinoma, and malignant melanoma (n = 7 each, 9%). The latency period to the occurrence of AML was 5.0 years (range, 1 day to 43.9 years). The cytogenetic profile of these cases showed in trend a greater frequency of adverse-risk abnormalities (19/67 [28%] vs 441/2314 [19%]; P = .06), in particular -5 or 5q− abnormalities (10/67 [15%] vs 177/2314 [8%], P = .04). OS of these patients was comparable with that of de novo AML patients (hazard ratio 1.04; P = .87).

Response to induction therapy

Response to induction therapy for t-AML and de novo AML was as follows: CR 63% and 67% (P = .21), refractory disease 25% and 22% (P = .38), and early/hypoplastic death 12% and 9% (P = .20), respectively. In univariate as well as in multivariable analysis, type of AML did not impact the achievement of CR (P = .13, P = .62, respectively).

Survival analysis

The median follow-up for survival in the entire cohort was 4.12 years (95% confidence interval [95%-CI] 3.97-4.28); the estimated 4-year RFS and OS were 38.5% (95%-CI 36.3%-40.9%) and 37.1% (95%-CI 35.2%-39.1%), respectively.

Outcome of patients with t-AML was significantly inferior: the 4-year RFS rates were 24.5% (95%-CI 17.7%-33.9%) and 39.5% (95%-CI 37.2%-42.0%; age-stratified log-rank test P < .0001) and the 4-year OS rates were 25.5% (95%-CI 19.6%-33.1%) and 37.9% (95%-CI 36.0%-40.0%; age-stratified log-rank test P = .001) for t-AML and de novo AML patients, respectively (Figure 3). Both greater CIR (age-stratified test, P = .01) and CID (age-stratified test, P = .002) contributed to the inferior outcome of t-AML patients. In t-AML patients previous therapy (radiation, chemotherapy, or both treatment modalities) and latency period had no impact on outcome.

Figure 3

Kaplan-Meier estimates. OS (A) and RFS (B) comparing t-AML with de novo AML.

Figure 3

Kaplan-Meier estimates. OS (A) and RFS (B) comparing t-AML with de novo AML.

Close modal

Allogeneic hematopoietic stem cell transplantation (HSCT) in first CR was performed in 487 of 2064 (24%) patients ≤ 60 years and in 30 of 789 (4%) patients > 60 years of age. There was a significant greater proportion of younger patients receiving an allogeneic HSCT in first CR 40/89 (45%) in t-AML compared with de novo AML 410/1445 (28%; P = .002). Because dose intensity in postremission therapy and proportion of patients receiving allogeneic HSCT differed markedly between trials for patients ≤ 60 years versus those > 60 years, we performed subset analyses in these 2 age cohorts. Of note, in patients ≤ 60 years there was no statistically significant difference in CIR between t-AML and de novo AML (4-year CIR, 45.1% vs 46.3%; P = .63), whereas a marked difference was found in CID (4-year CID, 22.9% vs 8.6%; P < .0001; Figure 4A). The significantly greater CID rates were present in this age cohort regardless of the type of postremission therapy but were pronounced in patients who received allogeneic HSCT (Figure 5A-B). The 4-year CID rates in younger patients with t-AML and de novo AML after intensive chemotherapy were 12.3% (SE 5.4%) and 5.3% (SE 0.7%) and after allogeneic HSCT 35.8% (SE 8.3%) and 17.2% (SE 2.0%), respectively. Again no difference was present in CIR (Figure 5C-D). The distribution of causes of deaths in CR was comparable between t-AML and de novo AML and deaths mainly were caused by infections. The 4-year OS rates in patients, receiving allogeneic HSCT or other intensive consolidation therapy in first CR were 42.6% (95%-CI 29.0%-62.7%) and 37.5% (95%-CI 25.2%-55.8%) for t-AML as well as 58.0% (95%-CI 53.0%-63.6%) and 56.6% (95%-CI 53.5%-59.9%) for de novo AML, respectively. In contrast, t-AML patients > 60 years showed a significantly greater CIR (P < .0001), whereas there was no difference in CID (P = .44; Figure 4B).

Figure 4

Influence of type of acute myeloid leukemia. CIR and CID in patients 60 years and younger (A) as well as in patients older than 60 years (B).

Figure 4

Influence of type of acute myeloid leukemia. CIR and CID in patients 60 years and younger (A) as well as in patients older than 60 years (B).

Close modal
Figure 5

Influence of type of AML on CID and CIR. CID (A-B) and CIR (C-D) in patients 60 years and younger according to type of postremission therapy (chemotherapy and autologous HSCT; A,C) allogeneic HSCT in first CR (B,D).

Figure 5

Influence of type of AML on CID and CIR. CID (A-B) and CIR (C-D) in patients 60 years and younger according to type of postremission therapy (chemotherapy and autologous HSCT; A,C) allogeneic HSCT in first CR (B,D).

Close modal

Multivariable cause-specific Cox regression analyses on relapse and death in CR showed again a significant adverse impact of t-AML in younger patients for death in CR (P < .0001) but not for relapse (P = .39), whereas the contrary was the case in older patients with a significant adverse impact of t-AML on relapse (P = .02), but not on death in CR (P = .22). The Cox regression model on OS revealed t-AML as a poor prognostic factor in younger intensively treated patients (P = .01), but not in older less intensively treated patients (P = .34; Table 5).

Table 5

Multivariable analyses of relapse, death in complete remission, and overall survival

Relapse
Death in CR
OS
HRPHRPHRP
t-AML       
    intensively treated (age 16-60 y) 1.16 .39 2.74 < .0001 1.35 .01 
    less intensively treated (age > 60 y) 2.13 .02 1.23 .22 1.14 .34 
Age (difference of 10 y) 1.11 .003 1.34 .0001 1.34 < .0001 
Male sex 1.03 .62 1.23 .18 1.10 .06 
Cytogenetic favorable-risk* 0.59 < .0001 0.38 < .0001 0.50 < .0001 
Cytogenetic adverse-risk* 1.55 < .0001 1.49 .07 2.07 < .0001 
NPM1 mutation 0.69 < .0001 0.67 .04 0.78 < .0001 
FLT3-ITD 1.42 < .0001 1.61 .01 1.51 < .0001 
Logarithm of WBC 1.14 < .0001 1.01 .82 1.09 < .0001 
Logarithm of platelets 0.99 .80 0.93 .37 0.94 .02 
BM blasts (difference of 10%) 1.00 .11 1.00 .78 1.00 .51 
PB blasts (difference of 10%) 1.00 .17 1.01 .54 1.02 .04 
Relapse
Death in CR
OS
HRPHRPHRP
t-AML       
    intensively treated (age 16-60 y) 1.16 .39 2.74 < .0001 1.35 .01 
    less intensively treated (age > 60 y) 2.13 .02 1.23 .22 1.14 .34 
Age (difference of 10 y) 1.11 .003 1.34 .0001 1.34 < .0001 
Male sex 1.03 .62 1.23 .18 1.10 .06 
Cytogenetic favorable-risk* 0.59 < .0001 0.38 < .0001 0.50 < .0001 
Cytogenetic adverse-risk* 1.55 < .0001 1.49 .07 2.07 < .0001 
NPM1 mutation 0.69 < .0001 0.67 .04 0.78 < .0001 
FLT3-ITD 1.42 < .0001 1.61 .01 1.51 < .0001 
Logarithm of WBC 1.14 < .0001 1.01 .82 1.09 < .0001 
Logarithm of platelets 0.99 .80 0.93 .37 0.94 .02 
BM blasts (difference of 10%) 1.00 .11 1.00 .78 1.00 .51 
PB blasts (difference of 10%) 1.00 .17 1.01 .54 1.02 .04 

BM indicates bone marrow; CR, complete remission; HR, hazard ratio; ITD, internal tandem duplication; OS, overall survival; PB, peripheral blood; and WBC, white blood count.

*

According to Döhner et al28 ; models were stratified for the 6 different treatment trials.

Furthermore, we were interested in the effect of t-AML in specific genetically defined subsets: t(15;17); t(8;21); inv(16) or t(16;16); t(9;11); NPM1. In multivariable models adjusted for WBC, in patients exhibiting an inv(16) or t(16;16) t-AML was a significant adverse prognostic factor for OS (hazard ratio 2.35; P = .04).

Therapy-related AML is increasing in prevalence with greater life expectancy and improved survival of patients treated with chemotherapy and/or radiation for previous malignancies and other disorders. However, there is a paucity of prospective treatment data because these patients have often been excluded from clinical trials. The frequency of t-AML in our large cohort was 7%, which is comparable with previously reported data.4,5 

Consistent with previous studies,5,6,13  patients with t-AML more frequently had abnormal karyotypes compared with de novo AML (75% vs 51%); in particular, there was a high prevalence of adverse-risk cytogenetics. Among specific abnormalities, t(9;11), -5 or 5q−, -7, 7q−, abnl(17p), complex karyotypes, and the recently described monosomal karyotype category40  were significantly overrepresented among t-AML (Table 3; Figures 12). For a large proportion of our cases, data on the mutational status of the NPM1 and FLT3 genes were available. Of note, the frequency of both NPM1 mutations and FLT3-ITD was significantly lower in t-AML, indicating that t-AML leukemogenesis in most cases follows mechanisms different from those seen in de novo AML. However, when we focused on patients with cytogenetically normal AML, no difference in the incidence and distribution of mutated NPM1 and FLT3-ITD between t-AML and de novo AML was evident (Table 6), which is consistent with previous reports.7,41 

Table 6

Distribution of molecular abnormalities in patients with therapy-related (t-AML) and de novo AML exhibiting a normal karyotype

t-AML, n (%)de novo AML, n (%)P
NPM1 mutation 16/40 (40) 537/1067 (50) .26 
FLT3-ITD 10/39 (26) 348/1054 (33) .39 
CEBPA mutation 2/29 (7) 98/894 (11) .76 
FLT3-TKD mutation 3/33 (9) 87/982 (9) > .999 
MLL-PTD 2/27 (7) 57/848 (7) .70 
t-AML, n (%)de novo AML, n (%)P
NPM1 mutation 16/40 (40) 537/1067 (50) .26 
FLT3-ITD 10/39 (26) 348/1054 (33) .39 
CEBPA mutation 2/29 (7) 98/894 (11) .76 
FLT3-TKD mutation 3/33 (9) 87/982 (9) > .999 
MLL-PTD 2/27 (7) 57/848 (7) .70 

AML indicates acute myeloid leukemia; ITD, internal tandem duplication; PTD, partial tandem duplication; and TKD, tyrosine kinase domain.

The median latency period between diagnosis of primary malignancy and occurrence of t-AML was 4 years, which is in line with published data.4-6  Beyond the known association between treatment with anthracyclines, as the major compound of intercalating agents (Table 1), or the application of topoisomerase II inhibitors and a short latency period for the development of t-AML, we were able to show that younger age at diagnosis of primary malignancy also was associated with a shorter latency period. With respect to molecular markers, we did not detect an association of previous radiation to FLT3 mutations, which is in contrast to data from Christiansen et al.42 

To evaluate whether the inferior prognosis of t-AML was attributable to an unfavorable genetic profile, or whether the variable “t-AML” itself predicted an inferior outcome, we performed multivariable analyses on the clinical end points response to induction therapy, RFS and OS. In these analyses, t-AML proved to be an adverse prognostic factor for RFS and OS but not for response to induction therapy. Of note, t-AML patients ≤ 60 years had a greater CID regardless of the applied therapy, whereas CIR was not different compared with de novo AML patients, likely reflecting cumulative toxicity of primary and secondary cancer therapy.43,44  The 4-year transplant-related mortality of 38.5% in our study compares even favorably to the 48% mortality rate at 5 years reported by the Center for International Bone Marrow Transplant Research.44 

Intriguingly, results after induction therapy were not different between t-AML and de novo AML patients, pointing to the fact that dosage and modality of treatment during postremission therapy had a marked impact on the cumulative toxicity of cancer therapy. Therefore, intensive induction therapy should not be withheld for t-AML patients, and dose-reduced regimes for allogeneic HSCT should be considered.

In contrast, t-AML patients > 60 years showed a significantly greater CIR and no difference in CID. One reason for the greater CIR in older AML patients might be the lower dosage of applied chemotherapy during postremission therapy compared with younger patients.

In summary, our results add to previous knowledge that t-AML proves to be an adverse prognostic factor for RFS and OS, independent of other clinical and biologic variables. The inferior outcome, especially in intensively treated younger adult patients, was mainly attributable to an increased risk of death in CR, possibly reflecting cumulative toxicity of cancer treatment.

Presented in part at the 51st Annual Meeting of the American Society of Hematology, New Orleans, LA, December 7, 2009.

The online version of this article contains a data supplement.

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

We are grateful to all members of the German-Austrian AML Study Group (AMLSG) for providing leukemia specimens and clinical data.

This work was supported in part by grants 01GI9981 (Network of Competence Acute and Chronic Leukemias) and 01KG0605 (IPD-Meta-Analysis: A model-based hierarchical prognostic system for adult patients with acute myeloid leukemia [AML]) from the Bundesministerium für Bildung und Forschung (BMBF), Germany.

Contribution: S.K. collected data, designed research, analyzed and interpreted data, and wrote the paper; K.D., J.K., C.-H.K., H.A.H., G.H., M.v.L.T., S.W., A.K., K.G., M.R., D.N., and A.G. provided study materials or patients and collected data; B.S., G.G., D.S., and C.M. collected data; M.Z. analyzed and interpreted data; H.D. and R.F.S. provided study materials or patients, collected data, designed research, analyzed and interpreted data, and wrote the paper; and all authors approved the manuscript.

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

A list of AMLSG institutions and investigators participating in this study appears in the supplemental Appendix (available on the Blood Web site; see the Supplemental Materials link at the top of the online article).

Correspondence: Richard F. Schlenk, MD, Department of Internal Medicine III, University Hospital of Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany; e-mail: richard.schlenk@niklinik-ulm.de.

1
Swerdlow
 
SH
Campo
 
E
Harris
 
NL
et al. 
WHO Classification of Tumours of the Haematopoietic and Lymphoid Tissues
2008
4th ed
Geneva, Switzerland
WHO Press
2
Godley
 
LA
Larson
 
RA
Therapy-related myeloid leukemia.
Semin Oncol
2008
, vol. 
35
 
4
(pg. 
418
-
429
)
3
Borthakur
 
G
Estey
 
EE
Therapy-related acute myelogenous leukemia and myelodysplastic syndrome.
Curr Oncol Rep
2007
, vol. 
9
 
5
(pg. 
373
-
377
)
4
Leone
 
G
Mele
 
L
Pulsoni
 
A
et al. 
The incidence of secondary leukemias.
Haematologica
1999
, vol. 
84
 
10
(pg. 
937
-
945
)
5
Schoch
 
C
Kern
 
W
Schnittger
 
S
et al. 
Karyotype is an independent prognostic parameter in therapy-related acute myeloid leukemia (t-AML): an analysis of 93 patients with t-AML in comparison to 1091 patients with de novo AML.
Leukemia
2004
, vol. 
18
 
1
(pg. 
120
-
125
)
6
Smith
 
SM
Le Beau
 
MM
Huo
 
D
et al. 
Clinical-cytogenetic associations in 306 patients with therapy-related myelodysplasia and myeloid leukemia: the University of Chicago series.
Blood
2003
, vol. 
102
 
1
(pg. 
43
-
52
)
7
Pedersen-Bjergaard
 
J
Andersen
 
MK
Andersen
 
MT
et al. 
Genetics of therapy-related myelodysplasia and acute myeloid leukemia.
Leukemia
2008
, vol. 
22
 
2
(pg. 
240
-
248
)
8
Allan
 
JM
Travis
 
LB
Mechanisms of therapy-related carcinogenesis.
Nat Rev Cancer
2005
, vol. 
5
 
12
(pg. 
943
-
955
)
9
Knight
 
JA
Skol
 
AD
Shinde
 
A
et al. 
A genome-wide association study to identify novel loci associated with therapy-related myeloid leukemia susceptibility.
Blood
2009
, vol. 
113
 
22
(pg. 
5575
-
5582
)
10
Seedhouse
 
C
Russell
 
N
Advances in the understanding of susceptibility to treatment-related acute myeloid leukaemia.
Br J Haematol
2007
, vol. 
137
 
6
(pg. 
513
-
529
)
11
Le Beau
 
MM
Albain
 
KS
Larson
 
RA
et al. 
Clinical and cytogenetic correlations in 63 patients with therapy-related myelodysplastic syndromes and acute nonlymphocytic leukemia: further evidence for characteristic abnormalities of chromosomes no. 5 and 7.
J Clin Oncol
1986
, vol. 
4
 
3
(pg. 
325
-
345
)
12
Rowley
 
JD
Golomb
 
HM
Vardiman
 
JW
Nonrandom chromosome abnormalities in acute leukemia and dysmyelopoietic syndromes in patients with previously treated malignant disease.
Blood
1981
, vol. 
58
 
4
(pg. 
759
-
767
)
13
Mauritzson
 
N
Albin
 
M
Rylander
 
L
et al. 
Pooled analysis of clinical and cytogenetic features in treatment-related and de novo adult acute myeloid leukemia and myelodysplastic syndromes based on a consecutive series of 761 patients analyzed 1976-1993 and on 5098 unselected cases reported in the literature 1974-2001.
Leukemia
2002
, vol. 
16
 
12
(pg. 
2366
-
2378
)
14
Pedersen-Bjergaard
 
J
Rowley
 
JD
The balanced and the unbalanced chromosome aberrations of acute myeloid leukemia may develop in different ways and may contribute differently to malignant transformation.
Blood
1994
, vol. 
83
 
10
(pg. 
2780
-
2786
)
15
Felix
 
CA
Secondary leukemias induced by topoisomerase-targeted drugs.
Biochim Biophys Acta
1998
, vol. 
1400
 
1–3
(pg. 
233
-
255
)
16
Mistry
 
AR
Felix
 
CA
Whitmarsh
 
RJ
et al. 
DNA topoisomerase II in therapy-related acute promyelocytic leukemia.
N Engl J Med
2005
, vol. 
352
 
15
(pg. 
1529
-
1538
)
17
Mrozek
 
K
Heerema
 
NA
Bloomfield
 
CD
Cytogenetics in acute leukemia.
Blood Rev
2004
, vol. 
18
 
2
(pg. 
115
-
136
)
18
Schlenk
 
RF
Döhner
 
K
Impact of new prognostic markers in treatment decisions in acute myeloid leukemia.
Curr Opin Hematol
2009
, vol. 
16
 
2
(pg. 
98
-
104
)
19
Schlenk
 
RF
Benner
 
A
Hartmann
 
F
et al. 
Risk-adapted postremission therapy in acute myeloid leukemia: results of the German multicenter AML HD93 treatment trial.
Leukemia
2003
, vol. 
17
 
8
(pg. 
1521
-
1528
)
20
Schlenk
 
RF
Germing
 
U
Hartmann
 
F
et al. 
High-dose cytarabine and mitoxantrone in consolidation therapy for acute promyelocytic leukemia.
Leukemia
2005
, vol. 
19
 
6
(pg. 
978
-
983
)
21
Schlenk
 
RF
Döhner
 
K
Mack
 
S
et al. 
Prospective evaluation of allogeneic hematopoietic stem cell transplantation from matched related and matched unrelated donors in younger adults with high-risk acute myeloid leukemia: Results of German-Austrian AMLSG treatment trial AMLHD98A.
J Clin Oncol
2010
, vol. 
28
 
30
(pg. 
4642
-
4648
)
22
Schlenk
 
RF
Fröhling
 
S
Hartmann
 
F
et al. 
Phase III study of all-trans retinoic acid in previously untreated patients 61 years or older with acute myeloid leukemia.
Leukemia
2004
, vol. 
18
 
11
(pg. 
1798
-
1803
)
23
Bennett
 
JM
Catovsky
 
D
Daniel
 
MT
et al. 
Proposed revised criteria for the classification of acute myeloid leukemia. A report of the French-American-British Cooperative Group.
Ann Intern Med
1985
, vol. 
103
 
4
(pg. 
620
-
625
)
24
Jaffe
 
ES
Harris
 
NL
Stein
 
H
et al. 
Pathology and Genetics of Tumours of Haematopoietic and Lymphoid Tissues
2001
3rd ed
Lyon, France
IARC Press
25
Mitelman
 
F
ISCN: An International System for Human Cytogenetic Nomenclature
1995
Basel, Switzerland
S. Karger
26
Schlenk
 
RF
Döhner
 
K
Krauter
 
J
et al. 
Mutations and treatment outcome in cytogenetically normal acute myeloid leukaemia.
N Engl J Med
2008
, vol. 
358
 
18
(pg. 
1909
-
1918
)
27
Cheson
 
BD
Bennett
 
JM
Kopecky
 
KJ
et al. 
Revised recommendations of the International Working Group for Diagnosis, Standardization of Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in Acute Myeloid Leukemia.
J Clin Oncol
2003
, vol. 
21
 
24
(pg. 
4642
-
4649
)
28
Döhner
 
H
Estey
 
EH
Amadori
 
S
et al. 
Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet.
Blood
2010
, vol. 
115
 
3
(pg. 
453
-
474
)
29
Roaten
 
JB
Kazanietz
 
MG
Caloca
 
MJ
et al. 
Interaction of the novel anthracycline antitumor agent N-benzyladriamycin-14-valerate with the C1-regulatory domain of protein kinase C: structural requirements, isoform specificity, and correlation with drug cytotoxicity.
Mol Cancer Ther
2002
, vol. 
1
 
7
(pg. 
483
-
492
)
30
Gewirtz
 
DA
A critical evaluation of the mechanisms of action proposed for the antitumor effects of the anthracycline antibiotics adriamycin and daunorubicin.
Biochem Pharmacol
1999
, vol. 
57
 
7
(pg. 
727
-
741
)
31
Smart
 
DJ
Halicka
 
HD
Schmuck
 
G
et al. 
Assessment of DNA double-strand breaks and gammaH2AX induced by the topoisomerase II poisons etoposide and mitoxantrone.
Mutat Res
2008
, vol. 
641
 
1–2
(pg. 
43
-
47
)
32
Shenkenberg
 
TD
Von Hoff
 
DD
Mitoxantrone: a new anticancer drug with significant clinical activity.
Ann Intern Med
1986
, vol. 
105
 
1
(pg. 
67
-
81
)
33
Hou
 
MH
Robinson
 
H
Gao
 
YG
et al. 
Crystal structure of actinomycin D bound to the CTG triplet repeat sequences linked to neurological diseases.
Nucleic Acids Res
2002
, vol. 
30
 
22
(pg. 
4910
-
4917
)
34
Kaplan
 
E
Meier
 
P
Nonparametric estimation from incomplete observations.
J Am Stat Assoc
1958
, vol. 
53
 
282
(pg. 
457
-
481
)
35
Cox
 
DR
Regression models and life tables (with discussion).
J R Stat Soc
1972
, vol. 
34
 
2
(pg. 
187
-
220
)
36
Gray
 
RJ
A class of k-sample tests for comparing the cumulative incidence of a competing risk.
Ann Stat
1988
, vol. 
16
 
3
(pg. 
1141
-
1154
)
37
Harrell
 
FE
Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis.
2001
New York, NY
Springer Verlag
pg. 
2001
 
38
R Development Core Team
R: A Language and Environment for Statistical Computing
2009
Vienna, Austria
R Foundation for Statistical Computing
39
Cheson
 
BD
Cassileth
 
PA
Head
 
DR
et al. 
Report of the National Cancer Institute-sponsored workshop on definitions of diagnosis and response in acute myeloid leukemia.
J Clin Oncol
1990
, vol. 
8
 
5
(pg. 
813
-
819
)
40
Breems
 
DA
Van Putten
 
WL
De Greef
 
GE
et al. 
Monosomal karyotype in acute myeloid leukemia: a better indicator of poor prognosis than a complex karyotype.
J Clin Oncol
2008
, vol. 
26
 
29
(pg. 
4791
-
4797
)
41
Andersen
 
MT
Andersen
 
MK
Christiansen
 
DH
et al. 
NPM1 mutations in therapy-related acute myeloid leukemia with uncharacteristic features.
Leukemia
2008
, vol. 
22
 
5
(pg. 
951
-
955
)
42
Christiansen
 
DH
Andersen
 
MK
Desta
 
F
et al. 
Mutations of genes in the receptor tyrosine kinase (RTK)/RAS-BRAF signal transduction pathway in therapy-related myelodysplasia and acute myeloid leukemia.
Leukemia
2005
, vol. 
19
 
12
(pg. 
2232
-
2240
)
43
Sorror
 
ML
Maris
 
MB
Storb
 
R
et al. 
Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT.
Blood
2005
, vol. 
106
 
8
(pg. 
2912
-
2919
)
44
Litzow
 
MR
Tarima
 
S
Pérez
 
WS
et al. 
Allogeneic transplantation for therapy-related myelodysplastic syndrome and acute myeloid leukemia.
Blood
2010
, vol. 
115
 
9
(pg. 
1850
-
1857
)
Sign in via your Institution