Classifying Cytogenetics in Patients with Acute Myelogenous Leukemia in Complete Remission...

Classifying Cytogenetics in Patients with AML in CompleteRemission Undergoing Allogeneic Transplantation: A CIBMTRStudy

Philippe Armand, MD, PhD1, Haesook T. Kim, PhD1, Mei-Jie Zhang, PhD2, Waleska S.Perez, MPH2, Paola S. Dal Cin, PhD1, Thomas R. Klumpp, MD3, Edmund K. Waller, MD,PhD4, Mark R. Litzow, MD5, Jane L. Liesveld, MD6, Hillard M. Lazarus, MD7, Andrew S. Artz,MD, MS8, Vikas Gupta, MD9, Bipin N. Savani, MD10, Philip L. McCarthy, MD11, Jean-YvesCahn, MD12, Harry C. Schouten, MD, PhD13, Jürgen Finke, MD14, Edward D. Ball, MD15,Mahmoud D. Aljurf, MD, MPH16, Corey S. Cutler, MD, MPH1, Jacob M. Rowe, MD17, JosephH. Antin, MD1, Luis M. Isola, MD18, Paolo Di Bartolomeo, MD19, Bruce M. Camitta, MD20,Alan M. Miller, MD, PhD21, Mitchell S. Cairo, MD22, Keith Stockerl-Goldstein, MD23, JorgeSierra, MD24, M. Lynn Savoie, MD25, Joerg Halter, MD26, Patrick J. Stiff, MD27, ChadiNabhan, MD28, Ann A. Jakubowski, MD, PhD29, Donald W. Bunjes, MD30, Effie W.Petersdorf, MD31, Steven M. Devine, MD32, Richard T. Maziarz, MD33, Martin Bornhauser,MD34, Victor A. Lewis, MD35, David I. Marks, MD, PhD36, Christopher N. Bredeson, MD,MSc37, Robert J. Soiffer, MD1, and Daniel J. Weisdorf, MD38

1Dana-Farber Cancer Institute, Boston, MA2Center for International Blood and Marrow Transplant Research, Milwaukee, WI3Temple University Bone Marrow Transplant Program, Philadelphia, PA4Emory University Hospital, Atlanta, GA5Mayo Clinic, Rochester, MN6Strong Memorial Hospital – University of Rochester Medical Center, Rochester, NY7University Hospitals Case Medical Center, Cleveland, OH8University of Chicago Hospitals, Chicago, IL9Princess Margaret Hospital, Toronto, CANADA10Vanderbilt University Medical Center, Nashville, TN11Roswell Park Cancer Institute, Buffalo, NY12Hospital A. Michallon, CHU de Grenoble, Grenoble, FRANCE13Academische Ziekenhuis Mastricht, Maastricht, NETHERLANDS14Universitatsklinikum Freiburg, Freiburg, GERMANY15University of California, San Diego Medical Center, La Jolla, CA

© 2011 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.Corresponding Author: Philippe Armand, MD, PhD, Dana-Farber Cancer Institute, 44 Binney Street, Boston MA 02115; Phone:617-632-2305; Fax: 617-632-4422; [email protected]'s Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to ourcustomers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review ofthe resulting proof before it is published in its final citable form. Please note that during the production process errors may bediscovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

NIH Public AccessAuthor ManuscriptBiol Blood Marrow Transplant. Author manuscript; available in PMC 2013 February 1.

Published in final edited form as:Biol Blood Marrow Transplant. 2012 February ; 18(2): 280–288. doi:10.1016/j.bbmt.2011.07.024.

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16King Faisal Specialist Hospital & Research Center, Riyadh, SAUDI ARABIA17Rambam Medical Center, Haifa, ISRAEL18Mount Sinai Medical Center, New York, NY19Ospedale Civile BMT Center Pescara, Pescara, ITALY20MACC Fund Center for Cancer and Blood Disorders, Children’s Hospital and Medical College ofWisconsin, Milwaukee WI21Baylor University Medical Center, Dallas, TX22Morgan Stanley Children’s Hospital of New York- Presbyterian, Columbia University MedicalCenter, New York, NY23Washington University School of Medicine, St. Louis, MO24Hospital de la Santa Creu I Sant Pau, Barcelona, SPAIN25Tom Baker Cancer Center, Calgary, CANADA26University Hospital Basel, Basel, SWITZERLAND27Loyola University Medical Center, Maywood, IL28Advocate Lutheran General Hospital, Park Ridge, IL29Memorial Sloan-Kettering Cancer Center, New York, NY30Universitatsklinikum Ulm, Ulm, GERMANY31Fred Hutchinson Cancer Research Center, Seattle, WA32Ohio State Medical Center, James Cancer Center, Columbus, OH33Oregon Health and Science University, Portland, OR34Universitatsklinikum Carl Gustav Carus, Dresden, GERMANY35Alberta Children’s Hospital, Calgary, CANADA36Bristol Children’s Hospital, Bristol, UK37Froedert Memorial Lutheran Hospital, Milwaukee, WI38University of Minnesota Medical Center, Minneapolis, MN

AbstractCytogenetics play a major role in determining the prognosis of patients with AML. However, theexisting cytogenetics classifications were developed on chemotherapy-treated patients and maynot be optimal for patients undergoing allogeneic hematopoietic cell transplantation (HCT). Westudied 821 adult patients reported to the CIBMTR who underwent HCT for AML in first orsecond CR between 1999 and 2004. We compared the ability of the 6 existing classifications tostratify patients by overall survival (OS). We then defined a new schema specifically applicable toHCT patients using this patient cohort. Under this CIBMTR schema, inv(16) is favorable,complex karyotype (4+ abnormalities) is adverse, and all other classified abnormalities areintermediate in predicting survival after HCT (5y OS 64%, 18%, and 50%, respectively,p=0.0001). This schema stratified patients into 3 groups with similar non-relapse mortality, butsignificantly different incidences of relapse, overall and leukemia-free survival. It applied topatients regardless of their disease status (CR1 or CR2), donor type (MRD or URD), orconditioning intensity (myeloablative or reduced intensity). This transplantation-specific

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Biol Blood Marrow Transplant. Author manuscript; available in PMC 2013 February 1.

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classification could be adopted for prognostication purposes and to stratify patients with AML andkaryotypic abnormalities entering HCT clinical trials.

KeywordsAML; cytogenetics; stem cell transplantation

INTRODUCTIONThe importance of cytogenetics in determining the outcome of patients with acute myeloidleukemia (AML) is well established(1, 2). Several collaborative groups have proposedclassification schemata to stratify patients by leukemia karyotype, based on retrospectivestudies of large independent patient cohorts. The most commonly used groupings are thoseof the MRC(3, 4) (now the National Cancer Research Institute (NCRI)), the CALGB(5), theSWOG/ECOG groups(6), and the EORTC/GIMEMA groups(7). More recently, Breems andcolleagues have shown that a monosomal karyotype (MK) is a predictor of very pooroutcome in AML(8). However, most patients in the above studies were treated withconventional chemotherapy rather than allogeneic hematopoietic cell transplantation (HCT).HCT is an important treatment modality for selected patients with AML, which underscoresthe necessity of understanding the role of cytogenetics in determining HCT outcome. Whileit appears that cytogenetics retain their prognostic relevance in the setting of HCT(6, 7, 9–11), there is no validated HCT-specific cytogenetics classification schema. Since a large partof the benefit of HCT depends on an immunologic graft-versus-tumor effect, it isconceivable that a given karyotypic subtype of AML might behave differently after HCTthan after conventional chemotherapy. Therefore, classifications based on series of patientstreated with chemotherapy may not apply optimally to transplanted patients. An HCT-specific cytogenetics grouping schema would be useful for prognostication, to help guidetreatment decisions, to stratify patients entering clinical trials, and to compare reported HCToutcomes across studies or centers. We have previously proposed such a classificationschema based on a cohort of patients transplanted at Dana-Farber Cancer Institute/Brighamand Women’s Hospital (henceforth referred to as the DFCI schema)(11), but this schema hasnot been validated on an independent cohort. We therefore performed a retrospective studythrough the Center for International Blood and Marrow Transplant Research (CIBMTR)with two aims: to validate the previous report by comparing the performance of the 6existing classifications on an independent cohort of HCT patients; and to derive a newgrouping schema based on this multicenter cohort.

METHODSData Source

The CIBMTR is a research organization comprising more than 500 transplant centersworldwide that contribute detailed data on consecutive allogeneic HCT. Patients arefollowed longitudinally, with yearly follow-up. Computerized checks for errors, physicianreviews of submitted data, and on-site audits of participating centers ensure data quality. Allpatients registered with the National Marrow Donor Program (NMDP) were retrospectivelycontacted, and informed consent was obtained from surviving patients in accordance withthe Declaration of Helsinki for participation in the NMDP research program. Informedconsent was waived by the NMDP Institutional Review Board for all deceased patients.Surviving patients who did not provide signed informed consent to allow analysis of theirclinical data were excluded. To adjust for the potential bias introduced by exclusion of non-consenting surviving patients, a corrective action plan (CAP) modeling process randomly

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excluded the same percentage of deceased patients using a biased coin randomization withexclusion probabilities based on characteristics associated with not providing consent for useof the data in survivors.

Patient SelectionWe included all patients 18 years and older transplanted for AML in 1st or 2nd completeremission (CR1 or CR2) between 1999 and 2004 at CIBMTR centers that treated more than20 eligible patients during this period. CR was defined as absence of blasts in peripheralblood, <5% blasts in marrow, with cellular marrow and normal CBC. No information wasavailable on CRp or CRi status. Patients with acute promyelocytic leukemia or pre-existingmyelodysplastic syndromes (MDS) were excluded (since cytogenetics for these patients maybe better grouped according to an MDS-specific classification(11, 12)), as were patientswith t(9;22) AML (given the difficulty of distinguishing this disease from blast crisischronic myelogenous leukemia in a registry setting). Patients who had received a previousautologous progenitor cell transplantation for AML were excluded, as were patientstransplanted from syngeneic or cord blood donors. Patients transplanted at Dana-Farber/Brigham and Women’s Hospital were ineligible (since they were used to derive the DFCIschema). Finally, we excluded all patients on whom cytogenetic information was missing ornot obtainable.

CytogeneticsWe reviewed all available primary cytogenetics reports for patients with abnormalkaryotypes (available for 92% of patients), with the help of an expert cytogeneticist(P.D.C.). Patients who were reported as having a normal karyotype were not reviewed. Weused for this analysis the latest available tumor karyotype (i.e., at diagnosis for patients inCR1 and at relapse for patients in CR2 when available). Cytogenetics were classifiedaccording to each of the existing schemata (Supplementary Table 1), with the followingmodification: patients with t(8;21) or inv(16) were classified as favorable under the MKschema, even though this schema does not specifically define a favorable subgroup.

Study End points, Definitions and Statistical AnalysisThe primary endpoint for this analysis was overall survival (OS) after HCT, defined as thetime from transplantation to death, with surviving patients censored at the last time reportedalive. Leukemia-free survival (LFS) was defined as the time from transplantation to death orrelapse, with surviving patients censored at last time reported alive and leukemia-free. Non-relapse mortality (NRM) was defined as death without evidence of leukemia recurrence. OSand LFS were calculated using the Kaplan-Meier method. The log-rank test was used forcomparisons of Kaplan-Meier curves. Cumulative incidence curves for non-relapse deathand relapse were constructed reflecting time to relapse and time to NRM as competing risks.The difference between cumulative incidence curves in the presence of a competing risk wastested using the Gray method(13). Potential prognostic factors for OS, LFS, relapse, andNRM were examined in the proportional hazards model as well as in the competing risksregression model(14). Proportional hazards assumption for each variable of interest wastested. Interaction terms including interaction with time were examined in the proportionalhazards regression model. In order to compare the performance of classification systems, wecalculated the difference in Akaike Information Criterion (AIC) between the full model anda model that did not include cytogenetics. We also calculated the c-index(15) for censoredOS data and Integrated Brier Score (IBS)(16) for models using each of the various groupingschemata. The analyses were conducted using Matlab v6.5 (Mathworks, Natick, MA), SASversion 9.2 (SAS Institute, Cary, NC) and R version 2.18.1.

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RESULTSPatient Characteristics and Cytogenetics

The baseline characteristics of the 821 patients are shown in Table 1. The median age was41 years (range, 18–74). Four percent of patients had therapy-related leukemia. Sixty-onepercent were transplanted in CR1 and 39% in CR2; 48% had a matched related donor(MRD), and 24% a well-matched unrelated donor (URD)(17); nearly two thirds receivedperipheral blood stem cells, and three quarters received a myeloablative conditioningregimen. Graft-versus-host disease (GVHD) prophylaxis regimens for the most part (94%)consisted of a calcineurin inhibitor-based regimen. Median follow-up was 61 months forsurvivors. Cytogenetics are shown in Table 2. Fifty-six percent of patients transplanted inCR1 and 67% of patients transplanted in CR2 had a normal karyotype. Six percent of CR1and 16% of CR2 patients had core-binding factor (CBF) AML; 13% of CR1 and 9% of CR2patients had a complex karyotype with at least 3 abnormalities.

Model Comparison for Overall SurvivalFive-year OS for the entire cohort was 48% (95% confidence interval 44–51%). We builtCox models for OS using cytogenetics (grouped according to the MRC schema), consideringthe following covariates: year of transplant, age, patient and donor gender, disease status atHCT, CR1 duration (for patients in CR2), therapy-related disease, white blood cell count atdiagnosis, Karnofsky performance score (KPS) at HCT, donor category(17),cytomegalovirus (CMV) serostatus, conditioning intensity, GVHD prophylaxis regimen,graft source, and CD34 cell dose. Among these factors, cytogenetics, therapy-relateddisease, KPS (above or below 90%), duration of CR1, donor category, donor gender andgraft source were significant for OS (not shown). The results did not change significantly ifcytogenetics were categorized using another of the existing schemata. We compared theability of the 6 existing cytogenetics grouping schemata to stratify patients for OS, using 3different metrics for this comparison: the Akaike Information Criterion (AIC) difference,which measures the improvement in model fit by the addition of the covariate of interest (inthis case, cytogenetics risk group), with a better fit indicated by a higher difference; the c-index, which is a generalization of the area under the curve (AUC) for censored survivaldata, using the cytogenetics risk assignment as a predictor, with a better predictor indicatedby a higher proportion (and an expected value of 0.5 for random prediction); and theIntegrated Brier Score (IBS), which is a measure of prediction error with a better predictorindicated by a lower score. The results are shown in Table 3. The DFCI schema provided thehighest AIC difference, c-index and lowest IBS (although the differences were small andlikely insignificant). Of note, in the Cox model, cytogenetics were the most influential factor(highest HR for mortality) for OS.

Derivation of a CIBMTR SchemaWe then used the present cohort to derive a new grouping schema. For this, we excluded 13patients with 2 abnormalities (to avoid making assumptions about the hierarchy of differentabnormalities) and only included karyotypic abnormalities present in at least 20 patients,thus restricting the analysis to 787 patients. We determined the hazard ratio for mortality foreach cytogenetic abnormality relative to normal karyotype, in the same Cox model usedabove for model comparison. In order to better define the outcome of patients with complexkaryotype, we split them into those with 3, 4, and 5 or more abnormalities. The results,shown in Table 4, allowed us to define 3 distinct risk groups: a favorable group with inv(16)(5% of patients), an adverse group with complex karyotype (with 4 or more abnormalities)(9% of patients), and an intermediate group comprising normal karyotype and all otherclassified abnormalities (86% of patients). Even though the p value associated with 4abnormalities did not reach statistical significance for OS, the hazard ratio for mortality was

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1.5, and the LFS of those patients was significantly worse than those with normal karyotype(HR=1.6, p=0.046), justifying its place in the adverse group. The OS of patients with t(6;9)was significantly worse than that of patients with normal karyotype (HR=2.7, p=0.049), butwe did not include this in the final classification given the small number of patients with thisabnormality. In this analysis, neither isolated t(8;21) nor t(8;21) in conjunction with otherabnormalities was significantly different from normal karyotype. In addition, within thecomplex karyotype group, no specific abnormality appeared to affect outcome with theexception of inv(16), which in the presence of a complex karyotype (4+ abnormalities)behaved like an intermediate-risk abnormality (HR relative to normal karyotype 1.0, p=1.0).Finally, within the adverse group, an MK genotype was not associated with significantlyworse outcome (HR=1.2, p=0.5). Using the same method to derive a grouping schema forLFS yielded the same results.

Performance of the CIBMTR SchemaWe then tested the performance of the new CIBMTR cytogenetics grouping schema incomparison with the existing schemata, again restricting the comparison to patientsclassifiable under all schemata (727 patients). The new schema overall outperformed allothers (AIC difference 67.6, compared to next best score of 61.5 for DFCI schema, IBS0.151 compared to 0.153 for DFCI, c-index 0.54, compared to 0.54 for DFCI). Becausethere were too few patients in this dataset to perform internal validation studies, we used ourprevious (and entirely independent) DFCI cohort(11) as a validation group, restricting it tothe 189 patients who met eligibility criteria for the present study. The CIBMTR schemacould stratify patients into three groups with significantly different OS (5y OS 76%, 41%and 23% for favorable, intermediate and adverse cytogenetics, respectively; p=0.019).

The OS, LFS, cumulative incidence of relapse and NRM for all classifiable patients basedon this new CIBMTR schema are shown in Figure 1. The 5-year (5y) OS for patients in thefavorable group was 64% (95% confidence interval [95CI], 47–77%), compared to 50%(95CI, 46–54%) in the intermediate group and 18% (95CI, 9–28%) in the adverse group(p=0.0001). In the multivariable model, the HR for mortality of the favorable group,compared to the intermediate one, was 0.7 (p=0.03), while the HR of the adverse groupcompared to intermediate was 1.9 (p<0.0001). Abnormal karyotypes included in theintermediate group had a similar outcome to normal karyotype (5y OS 46% versus 51%,p=0.5). The 5-year LFS for patients in the 3 groups were 58% (95CI, 40–72%), 45% (95CI,41–49%) and 16% (95CI, 8–26%) (p<0.0001). The cumulative incidence of relapse (CIR)was also significantly different (19%, 29% and 51%, p=0.0003), while NRM was notsignificantly different (23%, 25%, and 33%, p=0.30). The significant association ofcytogenetic risk group with LFS and CIR was confirmed in multivariable models: the HRfor death or relapse of favorable compared to intermediate was 0.6 (p=0.055), and of adversecompared to intermediate 1.9 (p<0.0001). The HR for relapse of favorable compared tointermediate was 0.5 (p=0.067), and of adverse compared to intermediate 2.0 (p<0.0001).Conversely, cytogenetics risk group did not significantly affect NRM (HR of favorablecompared to intermediate 0.9, p=0.8; of adverse compared to intermediate 1.2, p=0.4).

As shown in Figures 2–4, the CIBMTR schema applied to patients regardless of diseasestatus (CR1 versus CR2, see Figure 2), donor category (MRD versus URD, see Figure 3),and conditioning intensity (ablative versus reduced intensity (RIC), see Figure 4). The log-rank p value in the RIC subgroup did not reach statistical significance (p=0.063), but this islikely because of small patient numbers, and the differences in LFS remained significant(log-rank p=0.025).

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DISCUSSIONWe propose a new cytogenetics grouping schema specifically applicable to patients withAML undergoing HCT in 1st or 2nd CR. This schema separates patients with abnormalkaryotypes into 3 groups: a favorable group (inv(16)), an adverse group (complexkaryotype, which may be optimally defined in the HCT context as 4 or more abnormalities),and an intermediate group comprising all other classified abnormalities, which has anoutcome similar to normal karyotype.

Several limitations of this work must be considered. This is a retrospective study subject toselection bias of patients chosen to receive a HCT. This is particularly relevant for patientswith CBF AML, for whom HCT is not commonly performed in 1st CR. There were notsignificantly more patients with WBC > 20 × 109/l at diagnosis in the t(8;21) or inv(16)subgroups (compared to normal karyotype); but it is quite possible that the patients in ourstudy had other undefined adverse features associated with the decision for transplantation(e.g., leukemia cutis, number of regimens needed to reach CR, etc). It is nonethelessreassuring that a favorable subgroup could still be identified, and that the classification isapplicable to both patients in CR1 and in CR2 (see Figure 2), since HCT may be consideredstandard therapy for CBF AML in CR2. Moreover, the retrospective nature of this study hasthe advantage that the observational database of the CIBMTR provides realistic datareflecting current practice and allows for a variety of heterogeneous factors to be potentiallyneutralized(18).

We stress that this schema should not be interpreted as a direct comparison of HCT andconventional chemotherapy outcomes. While it is tempting to conclude from this study thatpatients with abnormal karyotypes that are considered adverse under most conventionalschemata, but intermediate under the CIBMTR schema (such as abnormal 5 or 7) should beconsidered for HCT in CR1, our data cannot directly address this inference. In this respect itshould be remembered that the survival curves shown here depict the outcomes oftransplanted patients, and are not comparable to intent-to-treat curves for cohorts of patientswith newly diagnosed AML.

This work could not incorporate any molecular information, such as c-Kit, FLT3, NPM-1status, etc, minimal residual disease (MRD) status, or cytogenetic remission information,which was not available in our dataset. The relevance of karyotypically silent mutations isnow beyond dispute(19), although their relevance in the HCT setting is not well understood.Certainly the present schema could be refined in the future by the incorporation of mutationstatus, which would be a very important step forward in defining prognostic subgroups forpatients with AML undergoing HCT. Gene-gene interactions involving both mutations andkaryotype may also be important in the biology of leukemia(20); their relevance in the HCTsetting may be addressed when a large transplant population with complete karyotypic andmolecular information is available.

The present cohort was not large enough to allow an independent validation cohort.However, the CIBMTR schema performed well in the (independent) cohort that we usedpreviously to establish the DFCI schema. It is also worth noting the very close similarity ofthe CIBMTR and the DFCI schemata (weighted Kappa statistic 0.73). The only differencesare the assignment of isolated t(8;21) (intermediate here and favorable in DFCI), and thedefinition of complex karyotype (4+ abnormalities here versus 3+ in DFCI schema; but itshould be noted that the optimal definition of complex karyotype was not studied in theDFCI schema). Those schemata (CIBMTR and DFCI) were derived on 2 entirelyindependent patient cohorts and yielded essentially the same results. This provides anexternal validation of the CIBMTR schema, with the exception of isolated t(8;21), whose

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exact place will have to be confirmed in further studies. There is at least one studysuggesting that t(8;21) is not as favorable as inv(16) after HCT, similar to the presentresults(21).

Finally, it is possible that a 3-group cytogenetics classification underestimates thecomplexity of the problem, and that a much larger study could subdivide karyotypes further,as well as elucidate the prognostic importance of rare karyotypic abnormalities that wereunder-represented in our dataset. For example, it appears that a complex karyotype with 4abnormalities is less adverse than 5 or more. However, given the challenges associated withreviewing primary cytogenetics data in a registry study, a much larger study may not bepractical. It may also be of interest in the future to examine the prognostic impact ofcytogenetic evolution. There were not sufficient data in our cohort to assess this rigorously.We therefore chose the abnormal karyotype closest to the time of transplant for analysis,since this is likely to be the best determinant of outcome.

An HCT-specific cytogenetics grouping schema, such as the one proposed here, may haveseveral uses. First, it may help clinicians and patients better estimate the prognosis afterHCT, which is often a critical part of the decision to pursue HCT. Second, it provides asystem for stratifying adult patients entering clinical trials of HCT for AML. Indeed, in ourcohort (as in a previous one(11)), cytogenetics was the single most important determinant ofpatient outcome, highlighting the importance of cytogenetics stratification in clinical trials.This highlights the need to stratify patients in clinical trials, and provides a means for doingso. Similarly, this schema could help to compare outcomes across different HCT studies oracross institutions, which has become essential in the era of mandatory outcome reporting.

Supplementary MaterialRefer to Web version on PubMed Central for supplementary material.

AcknowledgmentsP.A. is supported by an ASH Scholar Award and an ASCO Career Development Award. This work was alsosupported by NIAID U19 AI 29530 and NHLBI PO1 HL 070149.

The CIBMTR is supported by Public Health Service Grant/Cooperative Agreement U24-CA76518 from theNational Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI) and the National Instituteof Allergy and Infectious Diseases (NIAID); a Grant/Cooperative Agreement 5U01HL069294 from NHLBI andNCI; a contract HHSH234200637015C with Health Resources and Services Administration (HRSA/DHHS); twoGrants N00014-06-1-0704 and N00014-08-1-0058 from the Office of Naval Research; and grants from Allos, Inc.;Amgen, Inc.; Angioblast; Anonymous donation to the Medical College of Wisconsin; Ariad; Be the MatchFoundation; Blue Cross and Blue Shield Association; Buchanan Family Foundation; CaridianBCT; CelgeneCorporation; CellGenix, GmbH; Children’s Leukemia Research Association; Fresenius-Biotech North America,Inc.; Gamida Cell Teva Joint Venture Ltd.; Genentech, Inc.; Genzyme Corporation; GlaxoSmithKline; KiadisPharma; The Leukemia & Lymphoma Society; The Medical College of Wisconsin; Millennium Pharmaceuticals,Inc.; Milliman USA, Inc.; Miltenyi Biotec, Inc.; National Marrow Donor Program; Optum Healthcare Solutions,Inc.; Otsuka America Pharmaceutical, Inc.; Seattle Genetics; Sigma-Tau Pharmaceuticals; Soligenix, Inc.; SwedishOrphan Biovitrum; THERAKOS, Inc.; and Wellpoint, Inc. The views expressed in this article do not reflect theofficial policy or position of the National Institute of Health, the Department of the Navy, the Department ofDefense, or any other agency of the U.S. Government.

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21. Kuwatsuka Y, Miyamura K, Suzuki R, et al. Hematopoietic stem cell transplantation for corebinding factor acute myeloid leukemia: t(8;21) and inv(16) represent different clinical outcomes.Blood. 2009; 113:2096–2103. [PubMed: 19126873]

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Figure 1. Transplantation outcomes for patients classified by the CIBMTR grouping schema(A) Overall survival; (B) Leukemia-free survival; (C) Cumulative incidence of relapse; (D)Cumulative incidence of non-relapse mortality.

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Figure 2. Overall survival of patients classified according to the CIBMTR schema, stratified bydisease status(A) Patients transplanted in CR1; (B) Patients transplanted in CR2.

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Figure 3. Overall survival of patients classified according to the CIBMTR schema, stratified bydonor type(A) Patients transplanted from a matched sibling donor; (B) Patients transplanted from anunrelated donor.

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Figure 4. Overall survival of patients classified according to the CIBMTR schema, stratified byconditioning intensity(A) Patients transplanted with myeloablative conditioning; (B) Patients transplanted withreduced intensity conditioning.

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Table 1

Baseline patient characteristics

Variable N. (%)a

Number of patients 821

Number of centers 49

Age (years) (median, range) 41 (18–74)

<40 366 (45)

40–49 220 (27)

50–59 167 (20)

60–64 48 (6)

65+ 20 (2)

Gender

Male 457 (56)

Female 364 (44)

Therapy-related diseaseb 36 (4)

WBC at diagnosisc

<20 411 (50)

20–50 138 (17)

>50 174 (21)

Data missing 98 (12)

Disease Status at HCT

CR1 498 (61)

CR2 322 (39)

Duration of 1st CRd

<6 months 67 (21)

6–12 months 93 (29)

>12 months 110 (34)

Data missing 52 (16)

Karnofsky performance score at SCT

≥90% 597 (73)

<90% 171 (21)

Data missing 53 (6)

Donor categorye

MRD 390 (48)

Non-MRD 431 (52)

Well-matched URD 194 (24)

Partially matched URD 110 (13)


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Variable N. (%)a

Mismatched URD 110 (13)

URD matching unknown 50 (6)

Mismatched relative 40 (5)

Graft source

PB 537 (65)

BM 284 (35)

Conditioning

Myeloablative 612 (75)

Non-myeloablative/Reduced intensity 209 (25)

GVHD prophylaxis

Calcineurin inhibitor-based 768 (94)

T-cell depletion 32 (4)

Other 21 (3)

CMV serostatusf

Recipient or donor + 619 (75)

Gender matchingg

Female to male 180 (22)

Male to female 202 (25)

Female to female 161 (20)

Male to male 277 (34)

Year of HCT (median, range) 2002 (1999–2004)

Months of follow-up (median, range) 61 (3–122)

aPercentages may not add to 100 because of rounding

bData missing on 4 patients.

cUnits are x109/l.

dFor patients in CR2.

eClassified according to reference (17).

fData missing on 21 patients.

gData missing on 3 patients.

WBC, white blood cell count; HCT, allogeneic hematopoietic stem cell transplantation; CR, complete remission; MRD, matched related donor;URD, unrelated donor; PB, peripheral blood; BM, bone marrow; GVHD, graft-versus-host disease; CMV, cytomegalovirus.


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Table 2

Cytogenetics

AbnormalityCR1 patients

N. (%)aCR2 patients

N. (%)a

Number of patients 499 322

Normal 281 (56) 215 (67)

t(8;21) 17 (3) 24 (7)

Isolated 11 12

With del(9q) or complex karyotype 2 8

With other abnormalities 4 4

inv(16)-related (inv(16) or t(16;16)) 15 (3) 29 (9)

Isolated 7 20

With complex karyotype 6 4

With other abnormalities 2 5

Abnormal 7b 33 (7) 12 (4)

−7 17 5

del(7q) 10 5

der(1;7)(q10;p10) 2 0

Other 7q abnormality 4 2

Abnormal 5c 28 (6) 3 (1)

−5 7 0

del(5q) 17 3


11q23 abnormality 37 (7) 10 (3)

t(6;11) 6 3

t(9;11) 14 2

t(10;11) 2 0

t(11;19) 5 1

Other 11q23 abnormality 10 4

3q abnormality 11 (2) 3 (1)

t(3;3) 1 0

inv(3q) 2 0

t(3;5) 0 1


Trisomy/Tetrasomy

trisomy 8 31 (6) 13 (4)

trisomy 21 6 (1) 4 (1)

Other trisomy 24 (5) 9 (3)


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AbnormalityCR1 patients

N. (%)aCR2 patients

N. (%)a

tetrasomy 8 2 (0) 2 (1)

tetrasomy 21 1 (0) 0 (0)

Monosomy

Autosomal (except 5, 7 or 17) 29 (6) 7 (2)

-X 3 (1) 1 (0)

-Y 5 (1) 7 (2)

17p abnormality 18 (4) 3 (1)

del(17p) 1 0 (0)

Other 17p abnormality (including monosomy 17) 17 3 (1)

12p abnormality 10 (2) 4 (1)

del(12p) 2 2

add(12p) 2 1

t(4;12) 0 1

t(5;12) 1 0

Other 12p abnormality 5 0

Other

t(1;19) 1 (0) 0 (0)

t(6;9) 7 (1) 2 (1)

inv(6) 1 (0) 1 (0)

t(8;16) 3 (1) 0 (0)

del(9q) 4 (1) 8 (2)

dup(11q) 0 (0) 0 (0)

del(11q23) 8 (2) 0 (0)

del(16q22) 1 (0) 0 (0)

del(20q) 2 (0) 2 (1)

del(21q) 1 (0) 0 (0)

Tetraploid 0 (0) 1 (0)

Monosomal karyotyped 31 (6) 6 (2)

Complex karyotype (≥3 abnormalities) 67 (13) 29 (9)

3 abnormalities 16 (3) 9 (3)



# of abnormalities (median, range) 5 (3–15) 4 (3–9)

aPercentages may not add to 100 because of rounding and because some patients have more than one abnormality (see Methods).

bOf the patients with monosomy 7, 4 had no other abnormalities, 4 had 1 other abnormality, and the remainder had a complex karyotype (3–15

abnormalities).


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cOther than for 2 patients who had isolated del(5q), abnormalities of chromosome 5 were in all case associated with other abnormalities; patients

with monosomy 5 all had complex karyotypes (5–15 abnormalities).

ddefined as ≥2 autosomal monosomies or 1 single autosomal monosomy with ≥1 structural abnormality (clonal deletion, addition, inversion or

translocation).


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Tabl

e 3

Com

paris

on o

f exi

stin

g cy

toge

netic

sche

mat

a on

ent

ire c

ohor

t

Gro

upin

g sc

hem

aN

umbe

r of

pat

ient

s not

cla

ssifi

able

(%)

Mod

el fi

t sco

rea

c-in

dexb

IBSc

HR

for

favo

rabl

e (p

val

ue)d

HR

for

adve

rse

(p v

alue

)d

MR

Ce

0 (0

)56

.30.

530.

154

0.8

(0.1

3)1.

8 (0

.000

1)

CA

LGB

68 (8

)58

.50.

520.

155

0.6

(0.0

2)1.

5 (0

.001

)

SWO

G/E

CO

G51

(6)

49.0

0.53

0.15

40.

7 (0

.19)

1.4

(0.0

10)

EOR

TC/G

IMEM

A0

(0)

50.0

0.53

0.15

30.

8 (0

.4)

1.5

(0.0

03)f

DFC

I5

(1)

60.0

0.55

0.15

30.

7 (0

.080

)1.

8 (<

0.00

01)

MK

0 (0

)51

.30.

520.

155

0.8

(0.2

)1.

9 (0

.001

)

Com

paris

ons w

ere

perf

orm

ed o

n th

e su

bset

of 7

49 p

atie

nts c

lass

ifiab

le u

nder

all

sche

mat

a, in

a m

ultiv

aria

ble

mod

el th

at in

clud

ed p

atie

nt a

ge, g

ende

r, th

erap

y-re

late

d di

seas

e, W

BC

at d

iagn

osis

, dis

ease

stat

us, d

urat

ion

of 1

st C

R, c

ondi

tioni

ng in

tens

ity, G

VH

D p

roph

ylax

is re

gim

en, K

arno

fsky

scor

e, g

raft

sour

ce, d

onor

cat

egor

y, a

nd C

MV

sero

stat

us.

a Def

ined

as t

he d

iffer

ence

in A

kaik

e In

form

atio

n C

riter

ion

betw

een

mod

el w

ithou

t cov

aria

tes a

nd m

odel

with

cov

aria

tes (

the

high

er th

e di

ffer

ence

, the

bet

ter t

he m

odel

fit.

b Def

ined

as t

he g

ener

aliz

atio

n of

the

area

und

er th

e cu

rve

for c

enso

red

surv

ival

dat

a us

ing

as a

pre

dict

r the

cyt

ogen

etic

s ris

k gr

oup

assi

gnm

ent,

with

a b

ette

r fit

indi

cate

d by

a h

ighe

r pro

porti

on.

c Inte

grat

ed B

rier S

core

, whi

ch m

easu

res p

redi

ctio

n er

ror;

the

low

er th

e sc

ore,

the

bette

r the

pre

dict

ion

abili

ty.

d Inte

rmed

iate

risk

is th

e re

fere

nce

grou

p fo

r bot

h co

mpa

rison

s. H

R d

enot

es h

azar

d ra

tio fo

r mor

talit

y.

e The

mod

el fi

t usi

ng th

e re

vise

d M

RC

cla

ssifi

catio

n(4)

was

infe

rior t

o th

e on

e us

ing

the

orig

inal

cla

ssifi

catio

n(3)

(not

show

n).

f For t

he v

ery

adve

rse

grou

p. A

dver

se g

roup

in th

is sc

hem

a w

as c

ompa

rabl

e to

the

inte

rmed

iate

gro

up (H

R=1

.1, p

=0.6

).

HR

den

otes

haz

ard

ratio

for m

orta

lity;

oth

er a

bbre

viat

ions

are

as i

n Ta

bles

1–3

.


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Table 4

CIBMTR Cytogenetics Grouping Schema

Group Abnormality HRb p value

Favorable Inv(16) (without complex karyotype) 0.5 0.030

Normal 1.0 Reference

t(8;21) 1.1 0.8

11q23 abnormality 1.1 0.7

Intermediate Trisomy/tetrasomy 8 1.2 0.5

Abnormal 5 or 7 1.3 0.3

Complex (3 abnormalities) 1.1 0.7

Inv(16) with complex karyotype 1.0 1.0

Other abnormalitiesa 1.1 0.7

Adverse Complex (4 abnormalities) 1.5 0.10

Complex (5+ abnormalities) 2.3 <0.0001

aExcept for abn12p, abn3q, del(9q), t(1;19), t(9;22), t(6;9), which are not classified in this schema

bCompared to normal karyotype


Classifying Cytogenetics in Patients with Acute Myelogenous Leukemia in Complete Remission...

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