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Acute myelogenous leukemia (AML) and myelodysplastic syndrome (MDS) primarily afflict older individuals. Hematopoietic cell transplantation (HCT) is generally not offered because of concerns of excess morbidity and mortality. Reduced-intensity conditioning (RIC) regimens allow increased use of allogeneic HCT for older patients. To define prognostic factors impacting long-term outcomes of RIC regimens in patients older than age 40 years with AML in first complete remission or MDS and to determine the impact of age, we analyzed data from the Center for International Blood and Marrow Transplant Research (CIBMTR).
We reviewed data reported to the CIBMTR (1995 to 2005) on 1,080 patients undergoing RIC HCT. Outcomes analyzed included neutrophil recovery, incidence of acute or chronic graft-versus-host disease (GVHD), nonrelapse mortality (NRM), relapse, disease-free survival (DFS), and overall survival (OS).
Univariate analyses demonstrated no age group differences in NRM, grade 2 to 4 acute GVHD, chronic GVHD, or relapse. Patients age 40 to 54, 55 to 59, 60 to 64, and ≥ 65 years had 2-year survival rates as follows: 44% (95% CI, 37% to 52%), 50% (95% CI, 41% to 59%), 34% (95% CI, 25% to 43%), and 36% (95% CI, 24% to 49%), respectively, for patients with AML (P = .06); and 42% (95% CI, 35% to 49%), 35% (95% CI, 27% to 43%), 45% (95% CI, 36% to 54%), and 38% (95% CI, 25% to 51%), respectively, for patients with MDS (P = .37). Multivariate analysis revealed no significant impact of age on NRM, relapse, DFS, or OS (all P > .3). Greater HLA disparity adversely affected 2-year NRM, DFS, and OS. Unfavorable cytogenetics adversely impacted relapse, DFS, and OS. Better pre-HCT performance status predicted improved 2-year OS.
With these similar outcomes observed in older patients, we conclude that older age alone should not be considered a contraindication to HCT.
Allogeneic hematopoietic cell transplantation (HCT) for patients with acute myelogenous leukemia (AML) and myelodysplastic syndrome (MDS) can be curative.1 However, the increased frequency of high-risk disease phenotypes such as adverse cytogenetics and possibly higher rates of peritransplantation mortality have limited the application of HCT in older patients.2–6 These same patients may be considered ineligible for HCT as a result of traditional age limits or other medical comorbidities.7,8
In an effort to explore graft-versus-leukemia effects without major regimen-related toxicity, many investigators have lowered the doses of radiation or alkylating agents used in the conditioning regimen.9,10 In single- and multi-institution analyses, nonmyeloablative (NMA) or reduced-intensity conditioning (RIC) regimens have demonstrated the feasibility and efficacy of these strategies in older patients with hematologic malignancies. However, few reports provide sufficient clinical and disease-related detail to clarify the results of HCT in older patients,11–16 and the limits of these data have compromised clinical decision making for older patients. In this analysis, we examine post-HCT outcomes in older (including age > 65 years) versus younger patients undergoing allografting to evaluate patient, disease, and treatment factors that may modify transplantation outcomes.
The Center for International Blood and Marrow Transplant Research (CIBMTR), a voluntary working group of more than 450 transplantation centers worldwide, contribute data on consecutive allogeneic HCTs to a statistical center housed both at the Medical College of Wisconsin (Milwaukee, WI) and the National Marrow Donor Program (Minneapolis, MN). Patients are observed longitudinally with yearly follow-up. Computerized checks for errors and onsite audits of participating centers ensure data quality. Physician review of data and additional requested data from reporting centers were included. Observational studies conducted by the CIBMTR are done so with a waiver of informed consent and in compliance with Health Insurance Portability and Accountability Act regulations as determined by the Institutional Review Board and the Privacy Officer of the Medical College of Wisconsin.
Patients, age 40 years or older, receiving an RIC or NMA HCT for AML in first complete remission (CR1) or MDS between 1995 and 2005 from a related or unrelated donor (URD) were included in this analysis. AML could have been de novo or progressed from MDS. Patients who received prior cord blood allografts were excluded, but patients receiving prior autografts were not.
A total of 1,080 patients were identified; 545 patients had AML (age 40 to 79 years), and 535 patients had MDS (age 40 to 78 years). The patients were included from 148 centers. Patients were divided into the following four age cohorts for analysis: 40 to 54, 55 to 59, 60 to 64, and ≥ 65 years. Unfavorable-, intermediate-, or favorable-risk cytogenetics were assigned according to Slovak et al17 for AML patients. Cytogenetics for MDS (good, intermediate, or poor risk) were classified based on the International Prognostic Scoring System.18 International Prognostic Scoring System scores could not be reliably calculated as a result of some missing data elements. For analysis, MDS was classified as either early (refractory anemia, acquired idiopathic sideroblastic anemia, or pre-HCT marrow blasts < 5%) or advanced (refractory anemia excess blasts, refractory anemia excess blasts in transformation, chronic myelomonocytic leukemia, or marrow blasts ≥ 5%). CIBMTR classifications of URD matching were used to define well-matched, partially matched, or mismatched categories.19 Preparative regimens were classified as either RIC or NMA. RIC regimens were defined by established CIBMTR functional definitions and included any regimen consisting of the following: ≤ 5 Gy of total-body irradiation as a single fraction or ≤ 8 Gy if fractionated; less than 9 mg/kg of busulfan oral (or intravenous equivalent); less than 140 mg/m2 of melphalan; less than 10 mg/kg of thiotepa; or carmustine, etoposide, cytarabine, and melphalan regimen.20 All other regimens were classified as NMA according to the definition by Champlin et al21 where prompt hematopoietic recovery could reasonably be expected without a transplantation within 28 days, often with mixed chimerism.
Primary outcomes were overall survival (OS), disease-free survival (DFS; defined as survival without death or relapse), nonrelapse (treatment-related) mortality (NRM; defined as any death in the first 28 days after transplantation or any death after day 28 in continuous remission), and hematologic relapse. All data were censored at date of last reported follow-up. Secondary end points included neutrophil recovery (defined as time to absolute neutrophil count of ≥ 500 neutrophils/mL sustained for 3 consecutive days), incidence of grade 2 to 4 acute graft-versus-host disease (GVHD), and presence or absence of chronic GVHD, as defined.22,23
Patient-, disease-, and transplantation-related variables were compared between age cohorts using the χ2 test for categoric variables and the Kruskal-Wallis test for continuous variables. Univariate probabilities of DFS and OS were calculated using the Kaplan-Meier estimator with variance estimated by Greenwood's formula. Probabilities of neutrophil recovery, acute and chronic GVHD, NRM, and relapse were calculated using cumulative incidence curves to accommodate competing risks. Ninety-five percent CIs for all probabilities and P values of pairwise comparisons were derived from pointwise estimates and calculated using standard techniques.
Age groups were compared using Cox proportional hazards regression models for acute and chronic GVHD and neutrophil recovery. The proportional hazards assumption for all the variables was tested. Time-dependent covariate regression coefficients were used to model time-varying effect when the proportionality assumption did not hold. This occurred only in the modeling for neutrophil recovery. The optimal time cut point was determined by the maximum likelihood method. The proportionality assumption was further examined for the Cox model. For OS, DFS, NRM, and relapse, a forward stepwise method was used to build regression models, and analysis was performed using the pseudovalue technique.24 This approach allows one to fit different models for each time point of interest without requirement for the assumption of proportional hazards. For OS and DFS, the pseudovalues were computed based on the Kaplan-Meier estimator of the survival distribution. For NRM and relapse, the pseudovalue analysis was conducted based on cumulative incidence functions because death and relapse are competing risks. Patient variables were considered in the model-building procedure, but because patient age was the main interest of this study, it was included in all steps of model building. Patient-related variables included sex and Karnofsky performance score of less than 80 versus ≥ 80. Disease-related variables included AML CR1; AML with prior MDS versus de novo AML; early MDS versus advanced MDS; time from diagnosis to transplantation (< v ≥ 1 year); and cytogenetics (favorable/intermediate v unfavorable for AML and good/intermediate v poor for MDS). Transplantation-related variables included donor age, donor/recipient cytomegalovirus status (negative/negative v negative/positive v positive/negative v positive/positive), donor match (HLA-matched sibling v well-matched URD v partially matched URD v mismatched URD), graft (bone marrow v peripheral-blood graft), GVHD prophylaxis (cyclosporine/tacrolimus ± methotrexate ± other v other), donor/recipient sex match (male/male v male/female v female/male v female/female), and conditioning regimen intensity (RIC v NMA). Risk factors with P < .05 were included in the model. The potential interaction between the main effect of age and all significant covariates were examined. All computations were performed using the statistical package SAS Version 9.1 (SAS Institute, Cary, NC).
Tables 1 and and22 list patient-, disease-, and transplantation-related variables across age groups for AML and MDS patients, respectively. Of the 545 patients with AML, 195 patients (36%) were older than 60 years of age, and 63 patients (12%) were ≥ 65 years old. The majority of patients underwent transplantation for de novo AML, but this was less common in the older age cohorts (P < .001). Nearly all patients had either unfavorable- or intermediate-risk cytogenetics; ≥ 40% of patients in all groups had normal cytogenetics. Use of HLA-matched siblings and URD donors varied across the four groups, as did donor age. Most patients (86%) received peripheral-blood stem cells versus bone marrow (P < .001). The remaining variables of sex, performance status, interval from diagnosis to transplantation, donor/recipient sex match, donor/recipient cytomegalovirus match, and URD/recipient HLA match were well balanced in the different age groups. Conditioning regimens were primarily fludarabine based (43%; P < .001; data not shown) and most often RIC (48% to 75%) versus NMA (P < .001). GVHD prophylaxis most often included a calcineurin inhibitor with or without methotrexate. Median follow-up time for the four age cohorts ranged from 25 to 37 months.
In the MDS cohort (Table 2), 535 patients were identified; 181 patients (34%) were ≥ 60 years of age, and more males were represented. Most patients presented with intermediate- or poor-risk cytogenetics. Peripheral-blood stem cells (80%) were the most frequent graft type. Donor source varied across the age categories; 60% of all patients received an URD allograft, including 40 patients (73%) older than age 65 years. Most transplantations used a fludarabine-based regimen (52%; P = .001) and RIC (65% to 78%) versus NMA for conditioning. Median follow-up time for the age cohorts ranged from 35 to 40 months.
For patients with AML, neutrophil recovery at day 28 was similar across age cohorts (Table 3). Cumulative incidence of recovery at day 28 was highest in the oldest patients. There was no significant difference in neutrophil recovery for patients with MDS across age groups (Table 4). Multivariate analysis demonstrated that older age favorably impacted recovery (relative risk [RR] = 1.41; 95% CI, 1.14 to 1.76; P = .002), as did use of RIC conditioning regimens (RR = 1.18; 95% CI, 1.02 to 1.35; P = .02). Chimerism data were not available for analysis.
At day 100, the incidence of grade 2 to 4 acute GVHD was similar across all groups for both diseases (AML: 33% to 35%, P = .96; MDS: 31% to 36%, P = .89). Age had no significant effect on the incidence of acute GVHD. Multivariate analysis showed a higher risk of acute GVHD when using a well-matched (RR = 1.67; 95% CI, 1.32 to 2.12; P < .001) or partially matched URD (RR = 1.94; 95% CI, 1.44 to 2.62; P < .001) compared with an HLA-identical sibling donor. Multivariate analysis showed that age was associated with a borderline higher risk of chronic GVHD, although only in the oldest age cohort (RR = 1.39; 95% CI, 1.01 to 1.91; P = .05).
Cumulative incidences of NRM did not differ between the age cohorts either at day 100 (6% to 13%; P = .16) or 1 year (18% to 30%; P = .29) for AML (Table 3). In patients with AML, NRM at 1 year was 30% for patients ≥ 65 years of age compared with 21% for patients between 40 and 54 years old. In patients with MDS, NRM at 1 year was 29% for the youngest cohort compared with 35% for the oldest cohort (Table 4). In combined multivariate analysis for both diseases, lower KPS, worsening HLA disparity, MDS (whether cytogenetically good, intermediate, or poor risk), unfavorable-risk AML, and increasing donor age each adversely affected 1-year NRM, whereas use of an NMA conditioning regimen was associated with a borderline lower risk (odds ratio [OR] = 0.75; 95% CI, 0.57 to 1.0; P = .05). At 2 years, only HLA disparity, cytogenetic risk group, and increasing donor age retained prognostic significance. Recipient age did not significantly impact NRM (Fig 1A). The most common primary causes of death in both the AML and MDS groups were relapse (33%), infection (21%), GVHD (14%), and organ failure (14%).
Relapse rates at 2 years were similar across age groups for both AML (P = .87) and MDS (P = .95). In patients with early MDS, 2-year relapse rates ranged from a low of 15% (95% CI, 4% to 31%) in the oldest age group to a high of 27% (95% CI, 16% to 40%) in patients age 55 to 59 years (P = .57). Relapse rates in patients with advanced MDS were slightly higher (30% to 35%) overall, but again showed no differences between the age groups (P = .95). Combined multivariate analysis demonstrated significantly more relapse at 2 years in patients receiving NMA conditioning regimens (OR = 1.46; 95% CI, 1.15 to 1.85; P = .002) and in patients with unfavorable-/poor-risk cytogenetics in both AML and MDS (OR = 2.01; 95% CI, 1.42 to 2.85; P < .001; and OR = 1.57; 95% CI, 1.04 to 2.35; P < .03, respectively). Early MDS was associated with less disease relapse at 2 years (OR = 0.43; 95% CI, 0.26 to 0.71; P < .001). Age had no significant impact on relapse (Fig 1B).
In univariate analysis, DFS at 2 years for patients with AML (P = .15) and MDS (P = .68) was similar across all age cohorts. Multivariate analysis (Table 5) showed worse DFS with older donor age, greater HLA disparity, and unfavorable-/poor-risk cytogenetics in both disease groups but confirmed no effect of recipient age (P = .81).
Two-year survival for patients with AML and MDS showed only modest differences across the four age groups (AML: 34% to 50%, P = .06; MDS: 35% to 45%, P = .37). In multivariate analysis (Table 5), age had no significant effect on OS (P = .74). However, KPS less than 80, mismatched URD, and unfavorable-risk cytogenetics all negatively impacted OS at 2 years. Kaplan-Meier estimates of DFS and OS are shown in Figure 2.
Data from the CIBMTR and the European Group for Blood and Marrow Transplantation have shown a dramatic increase in the number of allografts that are being performed using RIC regimens for a variety of hematologic conditions.25,26 The advent of RIC has allowed for increased use of allografting in older and less fit patients.27,28 Although the median age of the patients undergoing HCT has increased, the proportion of patients older than age 60 years, and particularly older than age 65 years, remains relatively small.29 This analysis from the CIBMTR is one of the largest series of older patients with AML or MDS treated with allogeneic HCT, yet still the population of patients older than age 65 years is only 12% of the AML cohort and 10% of the MDS cohort over a 10-year period as a result of uncertainty regarding outcomes in the older patient and hesitance of providers for referral to transplantation centers.
We observed that transplantation toxicity, relapse, and survival for older adults are not significantly different than those for younger adults undergoing a similar NMA or RIC allogeneic HCT. Previous nontransplantation studies have shown uniformly poor survival in patients older than age 60 years, with little improvement over the last 30 years.4,30 Our data indicate that allogeneic HCT offers a treatment option able to provide long-term disease control in almost one third of patients older than age 40 years, which was similar even in the oldest cohort of patients ≥ 65 years old.
HCT for these older patients did not result in excess NRM, as many clinicians might fear. NRM was similar across all four age cohorts, ranging from 18% to 35% at 1 year. The incidence of acute and chronic GVHD was also similar across all age cohorts, although a trend toward more chronic GVHD was noted in the oldest age population in which more URDs were used. This is not surprising because use of URD is often reported to be associated with a higher risk of chronic GVHD.31,32 We recognize that small patient numbers may confound recognition of small differences in outcomes; however, these encouraging data help confirm the overall safety and tolerability of the procedure, even in the oldest group.
Older age was not associated with higher relapse rates despite the high-risk disease represented in this population. However, regimen intensity may still be important because NMA regimens were associated with higher relapse rates. Other series have shown that greater regimen intensity leads to less relapse, although possibly at the expense of higher NRM.33–35 Analysis of the various RIC regimens used for transplantation was beyond the scope of this article. No formal comparison with published series of patients undergoing myeloablative transplantation was made because most exclude patients older than age 60 years and this would confound the analysis of age and its impact. Because the best preparative regimen for allogeneic HCT is still uncertain, carefully designed prospective trials are essential to determine the contribution of a specific conditioning regimen to successful disease control.
In this large series, OS and DFS were not significantly worse in the older patient groups. Donor age did show an association with worse DFS; however, because sibling donors are generally similar in age to their recipients, whereas URDs are often younger, analysis of this variable is confounded by donor type and HLA matching, so no further analysis was appropriate. The older patients undergoing transplantation were judged by their physicians to be fit for the rigors and risks of allotransplantation. The somewhat younger group assigned to receive NMA or RIC conditioning may have had comorbidities, making this choice clinically appropriate, but such details were not available for this analysis. Efforts to adjust for potential bias were performed using performance status at time of transplantation, and no age-associated differences were noted. It is evident from this and other studies36,37 that transplantation physicians can identify patients older than age 40 years who are able to undergo this procedure with reasonable safety using KPS, perhaps augmented with other comorbidity indices.
Although we are encouraged by our observations that older patients shared similar risks of NRM, relapse, and GVHD as their younger counterparts, much work remains. Novel therapies such as monoclonal antibodies, FLT3 kinase inhibitors, and vaccination studies using leukemia antigens and dendritic cells may further complement or replace current treatments, allowing more individually targeted approaches for remission induction.38–40 This may increase the number of patients achieving complete remission using less toxic therapies and increase the number of candidates for allogeneic HCT. Additionally, quality-of-life studies in older individuals will become important as more patients use transplantion options as a form of therapy.
In this study, HCT resulted in 2-year survival rates of greater than 30% in all age groups, whereas conventional chemotherapy offers almost no chance of extended survival for older patients with AML or MDS. As recently reported, only a minority of patients with AML or MDS achieving complete remission after induction chemotherapy are able to undergo HCT in CR1.29 Our data support active consideration of HCT in older patients. We recommend and encourage referral to a transplantation center for all potential candidate patients. We also advocate expanded insurance coverage for MDS transplantation and suggest the continued enrollment of older patients onto prospective trials of allogeneic HCT designed to test improvements in the safety and efficacy of allografting for these older patients, who need it the most.
The following are contributors from the Writing Committee: M. Arellano, A. Artz, M. Bishop, J.Y. Cahn, M. Cairo, R. Champlin, E. Copelan, H. Fernandez, J. Finke, J. Gajewski, G. Hale, W. Hogan, D. Howard, A. Langston, S. Lugar, J. McCarty, A. Miller, S. Richard, O. Ringden, J.M. Rowe, S. Santarone, M.L. Savoie, W. Scyhroyens, G. Schiller, R. Soiffer, W. Vaughn.
The CIBMTR is supported by Public Health Service Grant/Cooperative Agreement No. U24-CA76518 from the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI), and the National Institute of Allergy and Infectious Diseases; Grant/Cooperative Agreement No. 5U01HL069294 from NHLBI and NCI; Contract No. HHSH234200637015C from the Health Resources and Services Administration/Department of Health and Human Services; Contract No. HHSH234200637020C from the Health Resources and Services Administration to the National Marrow Donor Program; Grants No. N00014-06-1-0704 and N00014-08-1-0058 from the Office of Naval Research; and grants from the American Association of Blood Banks; Aetna; American Society for Blood and Marrow Transplantation; Amgen; anonymous donation to the Medical College of Wisconsin; Association of Medical Microbiology and Infectious Disease Canada; Astellas Pharma US; Baxter International; Bayer HealthCare Pharmaceuticals; Blood Center of Wisconsin; Blue Cross and Blue Shield Association; Bone Marrow Foundation; Canadian Blood and Marrow Transplant Group; Celgene; CellGenix; Centers for Disease Control and Prevention; ClinImmune Labs; CTI Clinical Trial and Consulting Services; Cubist Pharmaceuticals; Cylex; CytoTherm; DOR BioPharma; Dynal Biotech, an Invitrogen Company; Enzon Pharmaceuticals; European Group for Blood and Marrow Transplantation; Gambro BCT; Gamida Cell; Genzyme; Histogenetics; HKS Medical Information Systems; Hospira; Infectious Diseases Society of America; Kiadis Pharma; Kirin Brewery; Merck; Medical College of Wisconsin; MGI Pharma; Michigan Community Blood Centers; Millennium Pharmaceuticals; Miller Pharmacal Group; Milliman USA; Miltenyi Biotec; National Marrow Donor Program; Nature Publishing Group; New York Blood Center; Novartis Oncology; Oncology Nursing Society; Osiris Therapeutics; Otsuka Pharmaceutical Development & Commercialization; Pall Life Sciences; PDL BioPharma; Pfizer; Pharmion; Saladax Biomedical; Schering-Plough; Society for Healthcare Epidemiology of America; StemCyte; StemSoft Software; Sysmex; Teva Pharmaceutical Industries; The Marrow Foundation; THERAKOS; Vidacare; Vion Pharmaceuticals; ViraCor Laboratories; ViroPharma; and Wellpoint; and Grant No. 2007/02823-3 from the Fundação de Amparo a Pesquisa do Estado de São Paulo (G.T.d.S.).
Written on behalf of the Acute Leukemia Working Committee from the Center for International Blood and Marrow Transplantation Research (CIBMTR).
The views expressed in this article do not reflect the official policy or position of the National Institutes of Health, Department of the Navy, Department of Defense, Health Resources and Services Administration, National Marrow Donor Program, or any other agency of the US Government.
Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a “U” are those for which no compensation was received; those relationships marked with a “C” were compensated. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.
Employment or Leadership Position: Armand Keating, Leukemia Lymphoma Society (U) Consultant or Advisory Role: None Stock Ownership: None Honoraria: John DiPersio, Genzyme Research Funding: None Expert Testimony: None Other Remuneration: None
Conception and design: Brian L. McClune, Daniel J. Weisdorf, Sergio Giralt
Provision of study materials or patients: Brian L. McClune, Jorge Sierra, Biju George, Vikas Gupta, Luis Isola, Madan Jagasia, Hillard Lazarus, Richard Maziarz, Edmund K. Waller, Chris Bredeson, Sergio Giralt
Collection and assembly of data: Daniel J. Weisdorf, Tanya L. Pedersen
Data analysis and interpretation: Brian L. McClune, Daniel J. Weisdorf, Tanya L. Pedersen, Gisela Tunes de Silva, Martin S. Tallman, Jorge Sierra, John DiPersio, Armand Keating, Biju George, Vikas Gupta, Theresa Hahn, Luis Isola, Madan Jagasia, Hillard Lazarus, David Marks, Richard Maziarz, Edmund K. Waller, Chris Bredeson, Sergio Giralt
Manuscript writing: Brian L. McClune, Daniel J. Weisdorf, Tanya L. Pedersen, Sergio Giralt
Final approval of manuscript: Brian L. McClune, Daniel J. Weisdorf, Tanya L. Pedersen, Martin S. Tallman, Jorge Sierra, John DiPersio, Armand Keating, Robert P. Gale, Biju George, Vikas Gupta, Theresa Hahn, Luis Isola, Madan Jagasia, Hillard Lazarus, David Marks, Richard Maziarz, Edmund K. Waller, Chris Bredeson, Sergio Giralt