Prof Gordon Cook
Section of Experimental Haematology
University of Leeds
Frailty, salvage ASCT and AlloSCT:
The 5 slide challenge!
Frailty & Myeloma therapy
Which Bond would you treat?
Age, frailty and survivorship
1
http://myeloma.dk/download.php?f=e2007a29d8ceb162b50f632cbc369127
http://seer.cancer.gov/faststats/
What patient factors effect treatment eligibility and
outcome ?
Patient-related:
− Age
-Sensitivity to toxicity
-Physical reserve
-Efficacy declines with age
− Co-morbidities
-Multiple scoring systems
• Charlson Co-morbidity Index
-Cardiac, respiratory, liver
-Renal impairment (eGFR <30 ml/min)
− Performance Status
-Karnovsky ≤ 70%
Disease-related:
− Disease stage
− Molecular risk stratification
Kleber et al. Blood Cancer J (2011); 1 e35
Rosiñol L et al. Haematologica 2012;97:616-621
Bergsagel P L et al. Blood 2013;121:884-892
2
3
Frailty Assessment
Performance Scores
Comorbidity Assessments
 PS does not differentiate between
those who may be fit for intensive
chemotherapy and those not
 Trials don’t consistently capture comorbidity information
 Needs to be refined to identify
vulnerable patients
 Inter-observer variability in PS
 Standardised measurements of
functional status may help inform us
re treatment
Geriatric Assessment
 2 most commonly used scores are
the Charleston Comorbidity Index
(CCI) and the Haemopoietic Cell
Transplantation Comorbidity Index
(HCT-CI)
 The higher the scores the shorter
the survival
 Screening for co-morbidity should be
routine in older patients
 Registry data used to retrospectively form a GA based on QOL
questionnaire and co-morbidity assessment (HCT-CI)
 Higher co-morbidity, reported difficulty with strenuous activity and pain
were associated with mortality
 Suggests simple targeted questions re physical functioning and specific
symptoms can help id the vulnerable
Frailty scores and outcomes (EMN)
4
Palumbo et al. 2015 Blood: 125 (3) 2068 - 2074.
Myeloma XIV – FITNESSTrial Design
5
Transplant ineligible NDMM
1:1
Frailty Index-adjusted Therapy
INDUCTION
Non-adjusted
1:2
CRDa
IRDa
FIT
UNFIT
FRAIL
1:2
1:2
1:2
CRDa
MAINTENANCE
C – 500mg D1 & D8
R – 25mg D1-21
D – 20mg
I – 4mg weekly
IRDa

CRDa

IRDa
CRDa

IRD

a
FIT: C – 500mg D1 & D8, R – 25mg D1-21, D – 20mg/wk, I – 4mg/wk
UNFIT: C – 350mg D1 & D8, R – 15mg D1-21, D – 10mg/wk, I – 3mg/wk
FRAIL: C – 250mg D1 & D8, R – 10mg D1-21, D – 10mg/wk, I – 3mg/wk
TREAT TO MAXIMUM RESPONSE (6-8 cycles)
1:1
Revlimid
Ixazomib/Revlimid
Questions??
Salvage ASCT
Is it worth it?
Background
 Results to date all retrospective or single-centre with no RCT to assess the
outcome of a second ASCT.
 19 studies of salvage ASCT published form 1996-2013
 Median TRM 4.1% (range 0-22%) with median ORR 64.3% (range 27.3%,
97.4%).
 Median PFS of 12.3 mns with a median OS of 32.4 mns (range 8, 79.1)
1
Vol. 15, No. 8, p874–885.
2
Response Rate to Re-induction & randomized
Treatment (Day+100)
sCR/CR P=0·012 (Fisher’s Exact test)
ORR – 79.2%
SD
PR
VGPR
sCR/CR
50
39.3%
39.3%
kl
C
AS
C
T
y
22.4%
0
PA
D
22.4%
ee
16.5%
-w
% of Recruited patients
100
N=297
N=89
N=85
Post-randomisation:
≥VGPR rate: 59·5% after salvage ASCT vs 47·1% after cyclophosphamide
(OR 0·38, 95%CI 0·2,0·7; ordinal logistic regression P=0·0036)
Cook et al, Lancet Oncology, 2014, Vol. 15, No. 8, p874–885
3
4
Time-to-progression (ITT)
TTP
PFS
ASCT2
ASCT2
NTC
NTC
• PD detected in 64% of ASCT patients & 80% in C-weekly.
• Median TTP (ITT) for ASCT is 19 mns (95% ci 16, 25) vs 11mns (95% ci 9, 12)
for C-weekly (HR 0.36 (95% ci 0.25, 0.53); p<0.0001)
Cook et al, Lancet Oncology, 2014, Vol. 15, No. 8, p874–885
UK Myeloma Research Alliance Myeloma XII (ACCoRD study):
Augmented Conditioning & Consolidation in Relapsed Disease
RE-INDUCTION
Ixazomib, Thalidomide &
Dexamethasone
ASCTAug
ASCTCon
Melphalan 200mg/m2
Melphalan 200mg/m2
+ Ixazomib
ITD x2 cycles
No Consolidation
Ixazomib Maintenance
No Maintenance
Time-to-Progression
5
Questions??
Allogeneic SCT
Is there still a role for consideration?
1
Why consider AlloSCT?
 The lure of GvM raises the prospect of cure
− Response to DLI
− Link with GVHD (esp chronic GVHD)
− Increased relapse with T-cell depletion
 TRM rates decreased significantly in last 10 years
 Deeper responses predict for durable responses, and with novel agents
more patients will achieve deeper responses with limited impact on
physiology
 So who should we consider?
1
0.75
Survival
 So why is use not more widespread?
− Data so varied
− Age at diagnosis
− Comorbidities/PS
− Cultural resistance in myeloma docs
Standard OS
Current PFS
(includes responses
to salvage therapies)
Standard EFS
0.5
0.25
0
0
1
2
3
4
5
6
Years from transplant
Bruno B, et al. Blood. 2009;113:3375-82.
7
8
2
J Clin Oncol. 2011;29:3016-22
PFS
0S
3
AlloSCT in High Risk disease
Krishnan et al, Lancet Oncol. 2011;12(13) 1195-203
Roos-Weil et al Haematologica 2011
Standard Risk
High Risk
The way forward……?
As TRM falls over time, relapse becomes the
biggest reason for treatment failure
Options:
− Use a prior debulking ASCT vs intensity-modulated MAC to
optimize pre-AlloSCT disease status
− Use of anti-myeloma therapy post allograft
− Use of optimized immunotherapy (novel agents + DLI, preemptive DLI)
− limit the procedure to patients with sensitive disease
− use the best conditioning with fludarabine/melphalan or
low-dose TBI with or without fludarabine and with no T-cell
depletion
4
5
The way forward……LenaRIC Trial overview
ASCT
CI: Dr Mark Cook
RIC AlloSCT:
Post-ASCT 120
days & ≥VGPR
CD8 T cells
CD4 comparison
800
400
LenaRIC
Control
LenaRIC
Control
CD4+HLA-DR+
100
p=0.02
400
50
D
+3
60
CD8+HLA-DR+
D
+1
80
D
+9
0
D+
36
0
D+
27
0
D+
18
0
100
p=0.04
Days post graft
Median values (at the time point specified)
50
Days post graft
D
+3
60
D
+1
80
0
D
+9
0
%CD8
Median values (at the time point specified)
>6 cycles
1-6 cycles
0
Ba
se
lin
e
D+
36
0
D+
27
0
0
D+
18
0
0
D+
90
200
Ba
se
lin
e
100
D+
90
cells/ml
200
%CD4
600
300
cells/ml
D+30-365
Lenalidomide 5 mg* D121/month
Flu
ATG (Fresenius)
2Gy TBI
>6 cycles
1-6 cycles
pDLI
Questions??