aml in the elderly, a review

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Acute myeloid leukaemia in the elderly: a review

Daniel A. Pollyea,1,2 Holbrook E. Kohrt1,2 and Bruno C. Medeiros1

1

Divisions of Hematology, and2

Oncology, Department of Internal Medicine, Stanford University School of Medicine, Stanford, CA, USA

Summary

The majority of patients with acute myeloid leukaemia (AML)

are elderly. Advancements in supportive care and regimen

intensification have resulted in improvements in clinical

outcomes for younger AML patients, but analogous improve-

ments in older patients have not been realized. While

outcomes are compromised by increased comorbidities and

susceptibility to toxicity from therapy, it is now recognized

that elderly AML represents a biologically distinct disease that

is more aggressive and less responsive to therapy. Some

patients tolerate and benefit from intensive remission-induc-

tion approaches, while others are best managed with less

aggressive strategies. The challenge is to differentiate these

groups based on host-related and biological features, in order

to maximize the therapeutic benefit and minimize toxicity. As

more is understood about the complicated pathogenesis and

molecular basis of AML, there are more opportunities to

develop and test targeted therapies. Elderly patients, with their

narrow therapeutic window, are well positioned to derive a

benefit from these novel agents, and therefore, despite a

difficult past, there are reasons to be optimistic about thefuture of elderly AML.

Keywords: elderly, acute myeloid leukaemia, gene expression

profiling, stem cell transplantation, prognosis.

Acute myeloid leukaemia (AML) is a clonal disorder charac-

terized by arrest of differentiation in the myeloid lineage

coupled with an accumulation of immature progenitors in the

bone marrow, resulting in hematopoietic failure. AML is the

most common acute leukaemia in adults, affecting roughly

three out of 100 000 people in the UK (Cancer Research UK).

While the prognosis for younger patients with AML has

improved in recent decades, the same cannot be said for older

patients, who continue to have a median overall survival (OS)

on the order of months with few long-term survivors

(Dombret et al, 2008). AML patients are predominantly

elderly, (for the purposes of this review, elderly is defined as

age 60 and older) with a median age at diagnosis of 67

(National Cancer Institute 19752007). With improvements in

life expectancy, by 2031 a 38% increase in elderly cases is

projected (Pinto et al, 2001).

Older age is an independent adverse prognosticator, asso-

ciated with a decreased complete response (CR) rate, disease

free survival (DFS), relapse free survival (RFS) and OS, with

higher rates of treatment related mortality (TRM), resistant

disease and relapse compared to equivalently treated younger

patients (Harousseau, 1998; Milligan et al, 2006; Dohner et al,

2010). Explanations for these poor outcomes are not intuitive.

To review this topic, we conducted a literature search of

publications from 1960 to the present with PubMed and

Google Scholar using combinations of the following search

terms: acute myeloid/myelogenous/myeloblastic leukaemia,

elderly, prognosis, treatment, survival, remission, toxicity,

transplantation, induction and consolidation, and reviewed

relevant works identified in the references sections of these

publications. We analyzed data from clinical trials that were

designed exclusively for the elderly, and where possible,

examined the elderly cohorts of all-inclusive AML trials. Herewe discuss the use of prognostic factors and predictive

modelling to risk stratify elderly AML patients, and how this

information can be applied to manage patients. We also review

treatment options for elderly patients, with an emphasis on

novel therapies.

Prognostic factors

Although age is a risk factor for TRM, disease resistance and

OS, it is not the most important risk factor (Dohner et al,

2010). While predicting outcomes for a population that

universally has poor OS is fraught with difficulty, the

importance of both age-dependent and independent variables

have been noted, and are discussed here.

Biological factors versus host factors

Elderly patients suffer increased toxicity with therapy

(Coebergh et al, 1998), as pharmacokinetic and pharmacody-

namic changes that occur with age inhibit drug clearance and

result in prolonged exposure to chemotherapeutics (Cohen,

1986). Additionally, a worse performance status (PS), seen

Correspondence: Daniel A. Pollyea, MD, Department of Internal

Medicine, Stanford University Cancer Center, 875 Blake Wilbur Dr,

Stanford, CA 94305 5820, USA. E-mail: [email protected]

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doi:10.1111/j.1365-2141.2010.08470.x 2011 Blackwell Publishing Ltd, British Journal of Haematology, 152, 524542


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more commonly in the elderly, predicts poor outcomes

(Appelbaum et al, 2006). Elderly patients are more prone to

bleeding complications, and are less able than younger patients

to tolerate infections (Estey et al, 1982; Harousseau, 1998).

Finally, psychosocial issues such as cognitive decline, the

availability of a caretaker, reluctance of physicians to treat

elderly patients, or the proximity of patients residences to

treatment centers, can all impact outcomes (Gross et al, 2005;

Deschler et al, 2006).

While clinical risk factors do not always differ significantly

between older and younger patients, outcomes typically do,

suggesting a biological basis for differential responses. Elderly

AML more commonly evolves from an antecedent haemato-

logical disorder (AHD) (Heinemann & Jehn, 1991), a feature

that is independently associated with inferior responses,

higher TRM, refractory disease and infectious complications

(Estey et al, 1982; Gajewski et al, 1989; Heinemann & Jehn,

1991). AML from an AHD is also more commonly associated

with adverse cytogenetic profiles, defined as a complex

karyotype (more than three abnormalities), chromosome 5or 7 deletions, 3q abnormalities, and monosomal deletions

(Appelbaum, 2008; Medeiros et al, 2010). Morphologically,

elderly blasts have less granulation and fewer Auer rods

(Hassan & Rees, 1990), and biologically, elderly AML has a

more immature stem cell-like phenotype (Fialkow et al,

1981), resulting in increased cytopenias and toxicity with

treatment (Stephan et al, 1998). Elderly patients have over-

expression of the multidrug resistance 1 (MDR1) gene (Leith

et al, 1997, 1999; Appelbaum et al, 2006; Roboz, 2007;

Sekeres, 2008; Kuendgen & Germing, 2009), which encodes

an efflux pump, permeability glycoprotein (Pgp), that

extrudes chemotherapeutics from the cell and increases

treatment resistance (Leith et al, 1997; van der Kolk et al,

2002; Larson, 2003; Solary et al, 2003; Mahadevan & List,

2004; Burnett & Mohite, 2006). MDR1 over-expression

correlates with a reduced CR rate, OS and DFS, and is

associated with relapsed and refractory disease, secondary

AML and adverse cytogenetics (Wood et al, 1994; Willman,

1996; Leith et al, 1999; Pinto et al, 2001; Baer et al, 2002;

Larson, 2003; van der Holt et al, 2005; Burnett & Mohite,

2006; Estey, 2007; Dombret et al, 2008). Finally, gene

expression profiling in elderly AML has resulted in the

identification of distinct subgroups that vary by outcome,

supporting a molecular basis for poor clinical outcomes in

elderly patients (Wilson et al, 2006; Raponi et al, 2008; deJonge et al, 2009; Rao et al, 2009) (Table I). All of these

observations suggest elderly AML represents a distinct

biological entity.

Parsing out the impact on outcomes from biological versus

host factors is a difficult exercise, especially because, as

exemplified by the relationship between adverse cytogenetics

and poor PS (Burnett et al, 2007), the two are inextricably

linked. Although it is important to recognize the contribution

from both, biological features have a greater impact on

outcomes than host-related risk factors.

Genetic factors

Over 50% of elderly AML patients have a cytogenetic

abnormality (Tiu et al, 2009), and this information is of

utmost importance for risk stratification. Elderly patients with

adverse cytogenetics have poor outcomes (Byrd et al, 2002),

and those with intermediate-risk cytogenetics [defined as

trisomy 8, normal karyotype (NK), and 11q23 abnormalities]

have relatively more favourable outcomes (Grimwade et al,

2001). However, in contrast to younger patients, in this

population the presence of favourable cytogenetics (defined as

translocations involving AML-ETO, CBFB-MYH11 or PML-

RARa) is uncommon (Rowley et al, 1982), and it is unclear

whether these abnormalities are associated with better out-

comes, likely to due to underpowered studies (Frohling et al,

2006; van der Holt et al, 2007). In a large study of the

age-specific incidence of cytogenetic abnormalities, adverse

cytogenetic profiles were disproportionately seen in elderly

patients; furthermore, balanced translocations decreased and

unbalanced aberrations increased with age (Bacher et al, 2005).Cytogenetic data predicts CR rate, relapse and DFS (Estey,

2007) independently of age and other potential confounders

(Hiddemann et al, 1999; Farag et al, 2006), and represents the

most powerful biological outcomes predictor. Elderly patients

with complex karyotypes experience minimal benefit from

induction chemotherapy (Byrd et al, 2002; Knipp et al, 2007;

Medeiros et al, 2010), possibly because the numerous genetic

abnormalities result in increased chemotherapy resistance.

The predictive power of cytogenetics is clear. However, in

clinical practice, metaphase cytogenetic studies take several

days. Practitioners are therefore faced with the dilemma of

whether it is best to delay treatment with the expectation that

the regimen will be tailored to the cytogenetic findings, or to

treat immediately, and use this information purely for post-

induction treatment decisions. Results of several studies report

a negative impact from delayed treatment in elderly AML

patients (Lowenberg et al, 1989; Rowe et al, 2004; Knipp et al,

2007), while others have not shown that delays result in

adverse outcomes (Sekeres et al, 2009). Further study is

necessary to resolve this important question.

The prognostic implications of molecular mutations for risk

stratification in NK AML are not fully understood. In younger

NK patients, nucleophosmin (NPM1) mutations, which confer

a favourable outcome, are common (Becker et al, 2010). In

older patients, NPM1 mutations were equally prevalent andalso associated with improved CR rates (Scholl et al, 2008) and

OS compared to NPM1 wild type (WT) patients (Buchner

et al, 2009; Becker et al, 2010). Furthermore, a gene expression

profiling study in elderly patients confirmed that those with

NPM1 mutations clustered together and had superior out-

comes (Wilson et al, 2006). Up to one-third of younger

patients have an internal tandem duplication (ITD) in the

Fms-like tyrosine kinase 3 (FLT3) gene, which when mutated

confers a worse prognosis regardless of NPM1 status (Kottari-

dis et al, 2001). Older patients have a decreased, but

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significant, incidence of FLT3 ITD mutations (Beran et al,

2004), and although they are less predictive in older patients,

FLT3 mutations are associated with an increased relapse risk

and shorter OS and DFS (Stirewalt et al, 2001).

Other prognostic factors

In elderly patients for whom treatment carries a high risk of

mortality, understanding which patients are most likely to

experience favourable outcomes based on baseline assessments

is essential. Although prognostications based on retrospective

analyses have been published, few have been prospectively

validated, making those large studies that have been of

particular value. A retrospective analysis of over 1000 older

AML patients who were treated with intensive regimens found

cytogenetics, age, white blood cell count (WBC), PS andsecondary AML to be multivariate predictors of OS (Wheatley

et al, 2009). These factors were validated in independent data

sets of 1400 patients, the majority of whom received intensive

regimens (Wheatley et al, 2009). In a large study that has not

been validated, Katarina et aldivided patients into favourable,

intermediate and high risk groups, using age, PS, cytogenetics,

AHD, comorbidities and utilization of strict isolation; the

groups had significantly different CR rates, TRM and OS.

Rollig et al (2010) subdivided patients with intermediate-risk

cytogenetics into two groups, good and adverse, and showed

significant differences in 3-year OS for these cohorts. Other

models have used combinations of cytogenetics, AHD, lactate

dehydrogenase (LDH), leukocytosis, PS and comorbidities to

predict OS in patients who receive induction chemotherapy

(Ferrara & Mirto, 1996; Stasi et al, 1996; Wahlin et al, 2001;

Gupta et al, 2005a; Latagliata et al, 2006; Gardin et al, 2007;

Giles et al, 2007b) (Table II).

Multivariate predictors of TRM include PS, laboratory

abnormalities and the presence of infections (Estey, 2007),

while multivariate predictors for early death include PS, organ

function, comorbidity indices, beta-2 microglobulin, LDH,

leukocytosis and thrombocytopenia (Latagliata et al, 2006;

Tsimberidou et al, 2008; Burnett et al, 2009). Multivariate

predictors for disease resistance include cytogenetics, beta-2

microglobulin and PS (Albitar et al, 2007; Estey, 2008), and for

OS include cytogenetics, age, luekocytosis, LDH, CD34-expression and NPM1 status (Rollig et al, 2010). More blasts

at diagnosis predicted worse outcomes (Baudard et al, 1994),

as did CD34-positive disease (Rollig et al, 2010), the presence

of chromosomal monosomies (Breems et al, 2008; Medeiros

et al, 2010), decreased expression of CD65s (Paietta et al,

2003) and increased expression of CD7 (Stasi et al, 1996).

Interestingly, age is not a multivariate predictor of outcomes in

several models (Chen et al, 2005; Gupta et al, 2005a; Malfuson

et al, 2008), suggesting other risk factors may be more

important for treatment decisions.

Table I. Selected gene expression profiling studies in elderly patients with AML suggest this represents a unique biological entity and provides a

molecular explanation for poor outcomes.

Reference Patients and methods Results Conclusions

Wilson et al

(2006)

N = 170 AML with median age

65 years; predominately

intermediate to poor risk

Unsupervised analysis showed six

clusters with outcome differences

Best prognostic group had 78% NPM1

mutations, high Wilms tumourgene (WT1) over expression

Group with most favourable

cytogenetics did not have best

outcome

Differences between six groups with

respect to refractory disease,

attaining CR and DFS

These differences were notexplained by age, cytogenetics or

other factors

Older patients can be separated into

different groups that vary by

outcome, independent of age and

cytogenetics

Rao et al

(2009)

N = 144 AML 55 years;

compared to 175 AML patients

45 years

Older patients had differential

activation of signalling pathways

compared to younger

Profile in older patients suggests

decreased sensitivity to

anthracyclines

Gene expression profiling data can be

utilized to tailor treatment regimens

de Jonge

et al (2009)

N = 175 AML with median age

59 years compared to 175 AML

with median age 31 years

Older patients with intermediate or

poor risk cytogenetics had decreased

expression of TSG CDKN2A

Distinct gene expression profile noted

for older compared to younger

patients

Raponi

et al (2008)

N = 67 AML 65 years from a

clinical trial of 158 patients who

received tipifarnib

Identified and validated a two-gene

expression ratio that predicted

outcomes for newly diagnosed and

relapsed/refractory patients who

receive tipifarnib

Can use gene expression profiling to

predict patients more likely to

respond to a given therapy

NPM1, nucleophosmin gene; CR, complete remission; DFS, disease free survival; TSG, tumour suppressor gene.

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Table II. Predictive models from elderly AML publications.

Citation Patients and methods

Multivariate poor prognostic factors forIndependent

validation?CR OS

Kantarjian et al

(2006)

N = 998 65 years AML/

high-risk MDS received

induction; retrospectively

evaluated

Age 75 years

Treatment-related AML

AHD 6 months

Treatment outside LAFR

Adverse cytogenetics

Leucocytosis

Anaemia

Renal insufficiency

ECOG PS >2

Age 75 years

AHD 12 months

Treatment outside LAFR


Renal insufficiency

Elevated LDH

ECOG PS >2

No

Rollig et al

(2010)

N = 909 > 60 years AML

received two courses of


evaluated

Age >65 years

Adverse cytogenetic

NPM1-/FLT3 ITD+

Elevated LDH

Leucocytosis

CD34 > 10%

>10% BM blasts by day 15

Age >65 years


NPM1-/FLT3 ITD+

Elevated LDH

Leucocytosis

CD34 > 10%

No

Wheatley et al

(2009)

N = 1071 older AML

received induction;

validated with independent

data sets of N = 1412

(N = 1137 intensively-

treated, N = 275 treated

with low intensity strategy)

Not reported Adverse cytogenetics

Secondary AML

Age > 65 years

Leucocytosis

ECOG PS 2

Yes

Gupta et al

(2005a)

N = 117 60 years AML

received induction;

retrospectively evaluated

ECOG PS >2

Leucocytosis

Elevated LDH


Leucocytosis


AHD

No

Johnson et al

(1993)


received induction;

prospectively evaluated.

65% had cytogenetic data.

Not reported WHO PS 1


Zubrod PS >1

Elevated B2M

Elevated uric acid

Elevated LDH

Yes (in validation

sample)

Wahlin et al

(2001)


most of whom received


evaluated

AHD


Administration of less

intensive induction regimens

Older age




No

Giles et al

(2007a)


received induction; pro

spectively evaluated HCT-CI

score

HCT-CI predicted CR HCT-CI predicted OS Yes

Stasi et al

(1996)


received a variety of

therapies; retrospectively

evaluated

Older age



Decreased CD14 expression

(aggressively-treated group only)

Older age




(aggressively-treated group

only)

No

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Gene expression profiling in older patients has revealed

clusters of patient samples that contain both adverse and

favourable cytogenetics (Wilson et al, 2006), suggesting there

are important biological prognostic factors that have yet to be

discovered. In the future, results from rationally designed

clinical/translational studies will allow clinicians to predictresponders to a given regimen based on molecular data,

maximizing the treatment effect while minimizing toxicity.

Treatment

Treatment of AML in the elderly is challenging; patients have

varying tolerance for toxicity, treatments are rarely curative,

and published studies either exclude the elderly or are limited

by selection bias. Although many treatment options have been

explored for elderly patients with AML, achievement of CR [or

CR with incomplete blood count recovery (CRi)] (Cheson

et al, 2003) remains necessary for long-term disease-free

survival. In a meta-analysis of over 12 000 elderly AML

patients, 50% received intensive therapy and had a median OS

of 30 weeks compared to 12 weeks from lower intensity

treatment, but this observation is limited by the fact that

equivalent patients were not directly compared (Deschler et al,

2006). However, TRM is a significant limitation for intensive

treatment in elderly patients, with 1040% experiencing this

outcome compared to 2

Decreased plateletsIncreased PB blasts

No

CR, complete response; OS, overall survival; MDS, myelodysplastic syndrome, AHD, antecedent haematological disorder, LAFR, laminar airflow

room, ECOG PS, Eastern Cooperative Oncology Group performance status; PB, peripheral blood; LDH, lactate dehydrogenase; BM, bone marrow;

B2M, beta 2 microglobulin; HCT-CI, haematopoietic cell transplantation comorbidity index; WHO PS, World Health Organization performance

status.

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versus 35 mg/m2 of daunorubicin (Burnett et al, 2009). In

contrast, Lowenberg et al(2009) showed that for the subgroup

of patients 6065 with an excellent PS and more indolent

disease, 90 mg/m2 of daunorubicin was superior to 45 mg/m2,

but these results have yet to be independently validated. Very

high doses of cytarabine (1 g/m2) are contraindicated in older

AML patients due to a significantly higher rate of cerebellar

toxicity (Preisler et al, 1987), and there was no benefit from

400 mg/m2 of cytarabine compared to 200 mg/m2 (Burnett

et al, 2009), or 200 mg/m2 compared to 100 mg/m2 (Dillman

et al, 1991).

Conversely, supported by observations that reduced

dosages of chemotherapy in older patients have similar

half-lives to full dosages given to younger patients (Leoni

et al, 1995), attempts have been made to improve the

tolerability to induction by reducing chemotherapeutic

dosages. Yates et al (1982) reported a higher CR rate in

older patients who received 30 mg/m2

of daunorubicincompared to those who received 45 mg/m2, while others did

not observe an advantage from anthracycline dose reduc-

tions (Kahn et al, 1984).

New strategies are necessary to improve induction in elderly

patients. Oral induction regimens are generally well tolerated

but have not resulted in significant improvements in responses

(Ruutu et al, 1994). Substituting fludarabine for an anthracy-

cline (Ferrara et al, 2005) or adding cladrabine (Juliusson et al,

2003) or all-trans retinoic acid (Schlenk et al, 2004) to

standard induction may also be reasonable approaches.

TRM is limiting in older patients treated with induction,

and most deaths are due to infection (Dombret et al, 1995;

Rowe et al, 1995; Stone et al, 1995). Using a growth factor

cytokine to shorten the duration of neutropenia has been

proposed to improve outcomes for elderly AML patients. In

randomized trials, growth factors were found to significantly

decrease the duration of neutropenia by several days (Buchner

et al, 1991; Dombret et al, 1995; Rowe et al, 1995; Lowenberg

et al, 1997; Witz et al, 1998). However, there was no impact on

TRM, infections, time spent in the hospital or most impor-

tantly, OS (Maslaket al, 1996; Lowenberg et al, 1997; Godwin

et al, 1998; Witz et al, 1998; Goldstone et al, 2001; Buchner

et al, 2004; Rowe et al, 2004), although some studies did show

a benefit for CR rate in the absence of OS (Dombret et al,

1995; Rowe et al, 1995). Because reduction in febrile neutro-

penia is an important endpoint, their use has been recom-

mended, typically after demonstration of bone marrow aplasia,

for patients older than 55 (Smith et al, 2006).

Post-remission and stem cell transplantation

Elderly patients who achieve a CR experience a remission

duration of 10 months (Schiller, 1996) and have a >75%

chance of relapse. While these patients may derive benefit from

post-remission therapies, it is often prohibitive due to

comorbidities or residual toxicity from induction. The stan-

dard post-remission regimen includes one to two cycles of

cytarabine with or without an anthracycline. In the elderly, no

Fig 1. Treatment algorithm for elderly AML patients. *Intermediate risk group scoring system. Scoring system adapted from Rollig et al (2010).

Further therapeutic recommendations.

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Table

III.Continued.

Citation

Patientsand

methods

Outcomes

CR

TRM

OS

Comments

Gardinetal(2007)

N

=416AML

65years

randomized

toinductionwith

IDAvs.DN

R

59%

IDAvs.54%

DN

R

(P=0

28)

Inductiondeath9%

IDAvs.10%

DNR(P=0

87)

2-yearforbotharms27%;OS

estimatesweresimilarinboth

DNRandIDArandomization

arms(P=0

37)

Nodifferencesinoutcomesfor

IDA

orDNR

Pautasetal(2010)

N

=468AML5070years

randomized

toARA-Cplus

standarddo

seIDA,

highdose

IDAorDNR80mg/m

2.

Those

whofailedi

nitialinduction

receivedsalvagewithARA-C

andMA

Afterfirstinduction,7

0%

standarddoseIDAvs.67%

highdoseIDAvs.61%

DNR

(P=0

25)

Inductiondeaths:6%

standard

doseIDAvs.3%

highdoseIDA

vs.8%

DNR(P=0

24)

4-year=32%

standarddoseIDA

vs.34%

highdoseIDAvs.23%

DNR(P=0

19)

OverallCRrate(included

patie

ntswhofailedinitial

inductionbutrespondedto

salva

ge)favouredstandard

dose

IDA,

butnoOS

difference

Schlenketal(2004)

N

=242AML

61years

randomized

to

induction

ATRA

52%forATRAvs.39%

forno

ATRA(P=0

05)

Notreported;haematological

andnon-haematological

toxicitysimilarforATRAand

noATRAarms

Median11monthsforATRA

versusmedian7monthsforno

ATRA(P or = 60

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