epidemiology subcommittee
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NCI Workshop on the Biology, Prevention NCI Workshop on the Biology, Prevention and Treatment of Relapse after Allo-HCT and Treatment of Relapse after Allo-HCT Subcommittee III Report: Epidemiology Subcommittee III Report: Epidemiology
and Natural History of Relapseand Natural History of Relapse
Co-Chairs:Co-Chairs: Steven Pavletic, NCI; Daniel Weisdorf, U. MinnesotaSteven Pavletic, NCI; Daniel Weisdorf, U. Minnesota
Committee Members:Committee Members: James M. Foran, U. AlabamaJames M. Foran, U. Alabama
Shaji Kumar, Mayo ClinicShaji Kumar, Mayo ClinicMarcos de Lima, MDACC Marcos de Lima, MDACC
Mohamad Mohty, U.NantesMohamad Mohty, U.NantesMarcelo Pasquini, CIBMTRMarcelo Pasquini, CIBMTR
Mei-Jie Zhang, CIBMTRMei-Jie Zhang, CIBMTR
Update November 2, 2009Update November 2, 2009
Epidemiology Subcommittee
• Committee Charge:• Review available data on relapse after allo-HCT • a) incidence• b) risk factors• c) survival after relapse• d) statistical methods
Too many topics
• AML • MDS• CML• ALL • Myeloma• Lymphoma• CLL• GVHD/GVL• Common Risk Factors for relapse• Statistics
Epidemiology of Relapse
Moderators: Pavletic and Weisdorf
1) Myeloid malignancies and ALL (Mohty, de Lima, Weisdorf)
2) Lymphoma, CLL (Foran, Pavletic)
3) Myeloma (Kumar)
4) GVHD/GVL (Pasquini, Pavletic, Weisdorf,)
5) Statistics (Zhang)
6) Discussion
Epidemiology and Natural History
of Relapse following Allogeneic
Cell Transplantation:
AML, MDS, CML and ALL
Mohamad Mohty, Marcos de Lima
and Daniel Weisdorf
NCI Workshop on Biology, Prevention and Treatment of Relapse After Allogeneic HCT
Subcommittee III: Epidemiology and Natural History of Relapse
Leukemia relapse is the major cause of treatment failure after allo-HCT in AML
AML in CR1: 10-40%Advanced disease stage: >40-50%After RIC allo-HCT: 18-50%
AML: Relapse Incidence post Allo-HCT
Martino et al, Blood 2006
AML: Risk Factors for Relapse post Allo-HCT
- Transplant beyond first CR
- Poor risk cytogenetics, FLT3-ITD mutations
- Secondary AML (prior chemo/radiotherapy; prior MDS)
- Age >60 years and comorbidities
- HLA-matching
- Single CB transplantation
- Reduced intensity and non-myeloablative conditioning
- In vitro and in vivo T cell depletion
- Gender donor/recipient combinations other than FM
- Specific KIR haplotypes
AML: Outcome post Relapse after Allo-HCT
Generally poor long-term survival and limited DLI response
Risk factors influencing outcome
- Patient age
- Remission duration
- Use of DLI
- Favorable cytogenetics
- Presence of comorbidities
- Disease stage at relapse (e.g. lower tumor burden at relapse)
Probability of relapse: 20% - 60%
(outcomes frequently reported ‘mixed’ with AML patients)
Trends that may confound comparisons with historic data:
- new treatments (ie, hypomethylating agents,
lenalidomide )
- treatment of older patients
- use of reduced-intensity regimens
- length of follow-up
MDS: Relapse Incidence post Allo-HCT
Not controversial
- disease stage (driven mostly by blasts and poor prognosis chromosomal abnormalities
- T cell depleted grafts
Controversial
- Secondary MDS
- Preparative regimen intensity
- Development of chronic GVHD
- Mixed chimerism
- Stem cell source
Unlikely/no evidence
- Recipient age / Donor age
- Acute GVHD / Related versus unrelated donor
MDS: Risk Factors for Relapse post Allo-HCT
Poor (0-40% long-term survival)
Major determinants for survival :
- remission duration
- MDS stage at relapse
Covariates that may influence outcome:
- comorbidities, age, patient preference, ongoing GVHD
MDS: Outcome post Relapse after Allo-HCT
Areas needing study
- Impact of novel therapies
- Impact of new molecular
classifications
- Incidence of relapse after
haplo and CBT
- Preferred timing in light of
availability of haplo and
UCB
- Role of maintenance
therapies
- Role of MRD detection in
predicting relapse.
- Relapse rates after hypomet. agents- Impact of new MDS class.- Incidence of relapse after haplo and CBT- Preferred timing in light of availability of haplo and UCB- Hypomethylating agents, angiogenesis inhibitors and other medications as maintenance therapy-Role of MRD detection in predicting relapse
AML MDS
Risk Factors Relapse Incidence
Outcome Risk factors influencing
outcome
- Age
- Disease stage
- Time interval from
diagnosis to transplant
- Donor type
- Unclear if
relapse rate is
higher with
older age
- 20% (CP) to
65% (BP)
- >1-2 years
worse results
Disease stage
= major
determinant of
survival:
CP: 30-60%
AP: 10-40%
BC: 0-10%
- PS
- Presence of
comorbidities
- Disease stage
upon relapse
- Remission
duration
- Sensitivity to
TKIs
Influence of BCR-ABL kinase mutations on HSCT outcomes ?
Impact of new TKI in predicting peri-HCT outcomes ?
Will pts who failed TKI pre-HCT respond following post-HCT relapse ?
Relapse rates after transplants from alternative donors ?
CML: Relapse after Allo-HCT
Leukemia relapse is the major cause of treatment failure after allo-HCT in ALL
25-50% in CR1 40-60% in CR2
ALL: Relapse Incidence post Allo-HCT
Goldstone, Blood, 2008
ALL: Risk Factors and outcome after Relapse
Short survival and limited DLI response
Early relapse worse; no other data
Sib vs URD: ALL Adjusted Multivariate risk of Relapse
Ringden et al, Blood, 2009
ALL RR 95% CI P
URD vs Sib 0.95 0.68-1.33 .78
Acute GVHD 0.78 0.57-1.07 .13
Chronic GVHD
0.69 0.47-1.01 .058
ALL: Areas needing study
Who will relapse?
- Detailed epidemiology
- Age/WBC/cytogenetics/time to HCT
- Duration of CR1
- MAC vs. RIC
Impact of MRD pre-allo-HCT:
- What assay? Does it predict relapse?
- Can intervention prevent relapse?
James Foran & Steven PavleticJames Foran & Steven Pavletic
NCI Workshop on Biology, Prevention and Treatment of Relapse After Allogeneic HCT
Subcommittee III: Epidemiology and Natural History of Relapse
Epidemiology and Natural History of Relapse following Allogeneic Cell
Transplantation for Lymphoma & CLL
Issues in Studying Epidemiology of Lymphoma Relapse After Allo-HCT
• Lymphoma most common hematologic malignancy
• No prospective studies incorporate Allo-HCT into initial treatment planning (*MCL – exception)
• Small retrospective studies with limited power
• Heterogeneous studies
– Divergent histologies
– Mix of refractory & sensitive patients
– Multiple lines of prior therapy including Auto-SCT
– Heterogeneity of transplant regimens
• GVL effect may have variable potency
GVL in NHL
• Similar relapse rate in allogeneic vs. syngeneic HCT CIBMTR/EBMT analysis
• Graft-versus-lymphoma effect in question, particularly for intermediate-grade histology
Bierman, J Clin Oncol 21:3744, 2003
• Emerging evidence of GVL in HL; seen with RIC
• Lower relapse risk for indolent, T-cell, mantle-cell lymphoma
CIR CIR SyngeneicSyngeneicvs. Allo-HCT & vs. Allo-HCT & Auto-SCT (p=ns) Auto-SCT (p=ns) HG
Int. Grade
LG
Relapse Risk & Histology
Corradini, Leukemia 21:2316, 2007
•Greatest relapse risk with aggressive histology (DLBCL)
& Hodgkin Lymphoma•Lower relapse risk with Follicular lymphoma, Mantle-Cell (esp. after RIC/NMA), & PTCL
•RIC/NMA: Relapse rate related to histology & disease status:
Stage n RelapseRate per PY
Low Risk CLL CR 7 0.00 NHL, low grade Not CR 34 0.15 NHL, low grade CR 9 0.18 Waldenström ‘s Advanced 9 0.19 NHL, mantle cell CR 16 0.19 NHL, mantle cell Not CR 25 0.20 NHL, high grade CR 26 0.23
Standard Risk CLL Not CR 75 0.26
High Risk NHL, high grade Not CR 36 0.57 HD CR 13 0.62 HD Not CR 38 0.72
Adapted from: Kahl, Blood 110:2744, 2007
NMA: Relapse Rates by Diagnosis & Disease Stage Groups
Allo-HCT after Auto-SCT
• Very high relapse rate after salvage MA Allo-HCT following prior Auto-SCT (n=114)– Disease progression 45% at 1yr, 70% at 5yrs
• Increase risk of progression if: – no TBI for NHL RR 3.02 (95% CI 1.71-5.32)– Chemoresistant RR 2.90 (95% CI 1.38-6.08) – 10 Induction Failure, untreated RR 3.45 (95% CI 1.74-6.87)
Freytes, Blood 104:3797, 2004
Hodgkin Lymphoma
• Refractory disease and after failure of Auto-SCT • Relapse greatest contributor to treatment failure1,
more common with bulky disease
• 60% disease progression at 3-5 yrs– Disease status at Allo-HCT (presence of CR &
chemosensitivity) only factor significantly associated with relapse after MA2
(n= 167, 42% chemoresistant)
1Peggs, Br J Haematol 143:468, 2008 2Peniket, BMT 31:667, 2003
Hodgkin Lymphoma – EBMT RIC Series (n=285)
• Disease progression: 41% at 1yr, 58% at 5yrs1
• Increase disease progression:Refractory RR 2.1 (95% CI 1.5-2.9)>3 lines prior therapy RR 1.7 (95% CI 1.2-2.5)Donor ♀: recipient ♂ RR 1.5 (95% CI 1.0-2.2)
• Similar rate progression/relapse after URD in CIBMTR2
• Suggestion of lower relapse risk with haploidentical donor3
Related HR 0.35 (95% CI 0.2-0.8), p=0.01Unrelated HR 0.43 (95% CI 0.2-0.9), p=0.03
• DLI for HL (n=64)1
13/41 evaluable achieved CRMedian survival 20 months after DLI
1Robinson, Haematologica 94:230, 2009 2Devetten, BBMT 15:109, 20093Burroughs, BBMT 14:1279, 2008
Hodgkin Lymphoma – RIC vs. MA
• ↑ relapse rate RIC (57%) vs. MA (30%)1
RIC RR 2.48 (95% CI 0.77-2.79)Bulk disease @ Dx RR 3.10 (95% CI 1.32-7.24)Refractory Disease RR 1.51 (95% CI 0.95-2.39)
• Low-dose TBI in RIC RR 3.10 (95% CI 1.32-7.24)• Children: ↑ relapse with RIC vs. MA (RR 4.4, p=0.05)3
• No adverse effect of alemtuzumab in RIC regimens2
1Sureda, J Clin Oncol 26:455, 20082Peggs, Br J Haematol 139:70, 20073Claviez, Blood 114:2060, 2009
•* cGVHD- lower risk relapse1 →
Aggressive NHL
• Disease sensitivity predicts relapse risk• Relapse at 3 yrs: refractory 70% vs. chemosensitive 30%2,8
RR ~3 if progression within 12 months initial therapy>3 prior regimens associated with ↑ relapse risk5
‘Stable’ refractory better than ‘progressive’3
• No clear benefit of rituximab pre-Allo-HCT6
• No clear impact of GVHD on relapse7 • Responses to withdrawal immunosuppression or DLI
reported4
1Doocey, Br J Haematol 131:223, 2005 2Aksentijevich BBMT 12:965, 20063Hamadani, BBMT 15:547, 2009 4Bishop, Ann Oncol 19:1935, 20085Law, BBMT 12:703, 2006 6Ratanatharathorn, Br J Haematol 145:816, 20097Ramadan, BMT 42:601, 20088Corradini, Leukemia 21:2316, 2007
Aggressive NHL – RIC & NMA
• Generally less chemo-resistant patients • Increase relapse rate NMA (36%) vs. MA (11%), p<0.011
NMA RR relapse 3.3 (95% CI 1.2-9.2), p=0.03
• In NMA – risk of relapse2:Age HR ↑ 0.68 (p=0.08) each decadeChemosensitive HR 0.2 (p=0.009)
• In RIC – relapse rate 33%3
• *Lower relapse rate with Mantle-Cell lymphoma & PTCL4-8
– Chemo-refractory AITL ↑ relapse (28% vs. 15% at 3 yrs), p=0.041Tomblyn, BBMT14:538, 2008 2Rezvani, Br J Haematol 143:395, 20083Thomson, J Clin Oncol 27:426, 2009 4Khouri, J Clin Oncol 21:4407, 20035Kyriakou, J Clin Oncol 27:3951, 2009 6Ganti, Ann Oncol 16:618, 20057Kim, Blood 108:382, 2006 8Baron, J Clin Oncol 24:4150, 2006
Indolent Lymphoma
• Less relapse than aggressive NHL or HL, generally <20%• Significantly lower after Allo-HCT than Auto-SCT1-3
(*not compared with syngeneic)
• Increase risk of relapse with MA:Chemo-resistant RR 1.69 (95% CI 1.27-2.23)Abnormal LDH RR 1.51 (95% CI 1.21-1.87)KPS<90% RR 1.31 (95% CI 1.07-1.61)BM+ RR 1.31 (95% CI 1.04-1.65)>2 yrs from dx RR 1.40 (95% CI 1.06-1.84)
1van Besien, Blood 92:1832, 1998 2van Besien, Blood 102:3521, 20023Ingram, Br J Haematol 141:235, 2008
Indolent Lymphoma RIC/NMA
• Relapse risk after NMA1:Transformed disease HR 4.85 (95% CI 1.5-15)Tandem Auto-Allo HR 5.47 (95% CI 1.5-21)Chemo-refractory HR 5.37 (95% CI 1.7-17)
• Increase risk relapse after RIC vs. MA, RR ~3 (p=0.04)2,5
• Impact of mixed chimerism on relapse unclear3
• Increase relapse risk for MRD by PCR (Bcl-2 or IgH) after RIC (40% vs. 0% if PCR-, p=0.010)4
1Rezvani, J Clin Oncol 26:211, 2008 2Vigouroux, Haematologica 92:627, 20073Khouri, Blood 111:5530, 2008 4Corradini, Leukemia 21:2316, 20075Hari, BBMT 14:236, 2008
CLL: Progression after Allo-HCT
Relapse % PFS %
MA1,2 2-32 30-65
RIC3 7-48 34-47
TCD4 68 24
Twins5 50 45
1Delgado, Blood 114:2581, 20092Montserrat, Blood, 107:1276, 20063Ben-Bassat, BMT, 39:441, 20074Gribben, Blood, 106:4389, 20055Pavletic, Leukemia, 21:2452, 2007
-MA data older than RIC-CLL notorious for slow disappearance of malignant clone – kinetics of response! - Late relapses 5%
CLL & Relapse
• Risk factors for relapse or progression • Chemorefractory, >CR/PR (consistently reported)
• Lymphadenopathy > 5 cm• >3 lines of chemotherapy• T-cell depletion in vivo or ex vivo • Slow donor T-cell chimerism• MRD positive post transplant
• No known impact:• 17p deletion or ZAP-70 status• URD versus MSD
CLL: Epidemiology of Relapse after Allo-HCT: Future ResearchFuture Research
• Few data on outcomes after relapse• DLI reported responses 15-50%• No data on risk factors or other interventions
• Other questions• Outcomes of Allo-HCT vs. conventional therapy• Optimal timing of transplant • Role of MRD pre and post alloHCT
• High Priority Studies• Retrospective, single center: CLL relapse index• Retrospective, community based: survival HCT vs. other• Prospective, multicenter cohort study, high detail of data
• Obstacles – lack of funding mechanisms and proposals
Lymphoma Relapse After Allo-HCT –More Data Needed!More Data Needed!
• GVL potency controversial in aggressive lymphoma & HL– more clearly identify GVL (except for MCL & PTCL)– understanding relapse in relation to TCD, T-cell
chimerism & cGVHD requires larger multicenter study
• Standardization of patient population definitions including IPI score, molecular pathology, and disease state
• Focus on chemosensitive, HCT earlier in disease course in pre-determined target patient populations
• Improved strategy for design of RIC regimens: – targeted vs. disease-specific vs. maintenance
• Alternative donors (esp. Haplo in HL)
Epidemiology and Natural History of Relapse following Allogeneic Cell
Transplantation for Myeloma
Shaji KumarShaji Kumar
NCI Workshop on Biology, Prevention and Treatment of Relapse After Allogeneic HCT
Subcommittee III: Epidemiology and Natural History of Relapse
Allo-HCT in myeloma
• Evidence to support graft vs. myeloma effect
• High treatment related mortality, historically
• Relapse along with TRM remains the principal reasons for treatment failure
• Bulk of existing data in the setting of relapsed disease
Trends
Myeloablative conditioning
Reduced intensity conditioning
Auto SCT followed by Reduced intensity conditioning
Decreasing TRM, but increased relapse risk
Auto RIC allo
Bruno et al, Blood (2009). 113 (14), 3375-3382; Rotta et al, Blood (2009). 113 (14), 3383-3391
Risk Factors for relapse• Poor patient performance status• Gender donor/recipient combination• Allo-HCT > 1 year from diagnosis• Durie stage 3 at diagnosis• Chemoresistant disease, advanced disease• Elevated B2 microglobulin, Deletion chromosome
13, deletion 17p• RIC regimens• T-cell depleted grafts, Campath or ATG use• Lack of complete response
How can we decrease risk of relapse?
• Allo-HCT early in disease course: needs better prognostic markers of the right group.
• Novel agents to obtain CR prior to allo-HCT or use of auto allo-HCT?
• Novel agents as maintenance post allo-HCT?
• Immunomodulatory drugs (lenalidomide) in conjunction with DLI?
• Use of bortezomib to separate GVM from GVH?
Outcome after relapse form allo-HCT
• Little data available, need retrospective studies
• Trials needed to explore novel approaches for post-relapse Rx
• Use of novel agents in conjunction with DLI:– To reduce tumor bulk– To enhance GVM effect– To alter GVM/ GVH ratio
• Explore novel drug combinations
GVHD/GVT and Relapse
Marcelo Pasquini, Steven Pavletic & Daniel Weisdorf
NCI Workshop on Biology, Prevention and Treatment of Relapse After Allogeneic HCT
Subcommittee III: Epidemiology and Natural History of Relapse
Donor Recipient Immune Interactions: Donor Recipient Immune Interactions: GVHD/GVT vs. Graft Rejection/RelapseGVHD/GVT vs. Graft Rejection/Relapse
GVHD/GVT
Rejection/Relapse
Donor Cells
Recipient
GVHDprophylaxis
Lower relapse rates in patients with GVHD
Horowitz, M et al. Blood 1990
Ringden, Blood 2009
Chronic, but not acute GVHD reduces relapse in leukemiaafter Sib or URD HCT
Relapse after HCT with non-myeloablative conditioning and importance of full donor chimerism
(N=322)
Baron, JCO 23:1993, 2005
Acute GVHD HR 95% CI PNo 1.0 -Grade 1 0.3 0.1 to 1.1 .07Grade 2 1.0 0.7 to 1.6 .91Grade 3-4 0.7 0.3 to 1.7 .44
Chronic GVHDNo 1.0 -Extensive 0.4 0.2 to 0.8 .006
>95% chimerismNo 1.0 -Yes 0.5 0.3 to 0.8 .002
Chronic GVHD severity does not impact Chronic GVHD severity does not impact leukemia relapseleukemia relapse
Black-no CGVHDBlack-no CGVHD
Blue-good risk CGVHD (50%),Blue-good risk CGVHD (50%), Green-intermediate (30-35%),Green-intermediate (30-35%),
Red-worst risk group (15-20%)Red-worst risk group (15-20%) Lee et al. Blood, 2002
Relapse Non-relapse Mortality DF survival
Similar leukemia relapse comparing HLA-matched BM and PBSC to HLA-
mismatched cord blood in adults
0.00
1.00
2.00
2.50
RELA
TIV
E R
ISK
P=0.006
0.60
0.42
0.86
P=0.003
0.44
0.85
0.61
CB mismatched BM matched PBSC matched
1.04
1.49
0.72
P=0.836 P=0.645
1.08
0.77
1.51
TRM TRMRelapse Relapse
Eapen M. et al, Blood 2008
Ringden, Blood 2009
No significant effect on relapse after 8/8 allele matched URD compared to MSD
Prophylaxis and RelapseMethod N Disease/
DonorRelapse p-value
Tac/Mtx vs CSA/MTX
165/164 Several/ Sibs
25% vs 22% at 2 y NS
Mtx /CSA vs CSA 59/43 AML/ Sibs
44% vs 24% at 4y 0.02
CSA/MMF vs CSA/MTX
26/67 Several/ Sibs
10%vs 21% at 2 y NS
T-cell depletion vs. CSA/Mtx
89/94 CML/URD
20% vs 7% at 2 y 0.01
Tac.Sir.MTX vs Tac/Sir
46/29 Several/Sibs
7%vs 6% at 2 y NS
Weaver C.H.et al, 1994 Ratanatharathorn V. et al, 1998
Wagner J. et al, 2005Neuman F. et al, 2005
Ho V. et al, 2009
Leukemia relapse remains unchanged in the last two decades despite improvements in supportive
care and transplant related mortality
Months
Cu
mu
lati
ve I
ncid
en
ce o
f R
ela
pse,
%
0
100
80
20
40
60
0 4836 6012 24
1995-1999, N=901
1985-1989, N=1124
1990-1994, N=1283
2000-2004, N=460
Cumulative incidence of relapse after HLA-matched Sibling Donor Transplant for AML in CR1, 1985-2004
GVHD Prophylaxis and Relapse: Impact of approaches free from chronic IS
No Chronic Immunesuppression
Luznik et al, 2008
-9 -8 -7 -6 -5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5 +6
TBI
THIO
rATG
Cy
CD34+ Selected PBSC Infusion No Chronic Immunesuppression
Devine S., O’Reilly R. et al, 2009HLA-matched sibling donorsAML in CR1 and CR2
Related and unrelated donorsHigh Risk Heme Malignancies
Epidemiology of GVHD/GVT and Relapse: Open Questions
• GVT/GVHD – Impact of disease-specific phenotypes
• Chronic GVHD– Impact of different cGVHD presentations on relapse– Impact of cGVHD therapy
• Stem cell sources and alternative donors– Impact on disease-specific subsets
• GVHD prophylaxis– Impact of novel agents (sirolimus) and combinations
on relapse.– Relapse rates on approaches free from chronic IS.
Statistical Methods for Analyzing the Relapse After HCT
Mei-Jie Zhang
NCI Workshop on Biology, Prevention and Treatment of Relapse After Allogeneic HCT Subcommittee III: Epidemiology and Natural
History of Relapse
• Relapse and TRM (treatment-related mortality) are two competing risks:
HCT
Relapse
TRM
hR(t)
hTRM(t)
Proper Summary Curve for Competing Risks Data
• In literature, “1 – Kaplan-Meier” has been used to compute relapse rate (treating TRM as censored)
• “1-KM” OVERESTIMATES the relapse incidence rate in the presence of competing risk of TRM
• Cumulative incidence function (CIF) is probability of relapse rate in the presence of competing risk of TRM.
• CIF is a proper summary curve for analyzing competing risks data
• Computing CIF is available in SAS & R
HCT example
• To illustrate, we consider a subset of data from a CIBMTR study (Szydlo et al. JCO, 1997, 15:1767-1777):HLA-identical Sibling (N=1224)Matched Unrelated (N=383)
0 12 24 36 48 60
05
1015
2025
30
Months
Pro
ba
bili
ty (
%)
Relapse
CIF1 - KM
0 12 24 36 48 60
05
1015
2025
30
Months
Pro
ba
bili
ty (
%)
TRM
CIF1 - KM
0 12 24 36 48 60
010
2030
4050
MonthsP
rob
ab
ility
(%
)
'REL+TRM' = '1 - KM (LFS)'
CIF of Relapse
CIF of TRM
1 - KM (LFS)
Cumulative Incidence Function (CIF) versus (1 - Kaplan-Meier (KM))
Compare Cumulative Incidence Functions
• In practice, Log-Rank test is commonly used/reported along with CIF curves by Trt groups
• Log-Rank test compares cause-specific hazards of relapse. BUT, CIF of relapse is determined by both cause-specific hazards of relapse and TRM
• In some studies, Log-Rank test may lead to a different conclusion compared to reported CIFs
Comparing Cumulative Incidence Functions
• Recently, Gray developed a test, which directly compares the cumulative incidence curves.
• Gray’s test should be used when we are interested in comparing the CIF of relapse (not cause-specific hazard of relapse)
• Gray’s test is available in R(R-cmprsk package: R-cuminc function)
0 12 24 36 48 60
01
02
03
0
Months
Pro
ba
bili
ty (
%)
HLA-Identical Sibling (N=1224)
Matched Unrelated (N=383)
Log-Rank Test: P=0.47
Gray's Test: P=0.12
5 Yr Pointwise Test: P=0.0179HLA-Id Sib: At Risk = 113, 25 (22-27)%MUD: At Risk = 10, 18 (13-23)%
Comparing Cumulative Incidence Functions of Relapse
Multivariate Analysis• In medical studies, we need to
assess covariate effect on the relapse rate OR compare relapse rates adjusting other risk factors
• BMT Example: Risk factors are not balanced
• Disease (AML/ALL/CML): SIB: 20/37/43% vs MUD: 16/18/65%; p<0.0001
• Stage (Early/InterMed/Adv): SIB: 66/20/14% vs MUD: 47/33/20%; p<0.0001
• Karnofsky (<90/≥90): SIB: 19/82% vs MUD: 24/76%; p=0.0138
Multivariate Analysis
• Commonly, we use Cox model which models cause-specific hazards of Relapse
• CIF of Relapse is determined by both cause-specific hazards of Relapse and TRM
• We need to directly model CIF: Subdistribution hazards (Fine&Gray R-cmprsk) Inverse Weighting (Scheike&Zhang; R-timereg) Pseudovalues Technique (Klein et al, SAS & R)
Example: Multivariate Analysis
• Adjusting risk factors of Disease, Disease Stage and Karnofsky:
• Cox Model: MUD vs Sib:
β = 0.10 (se=0.15); RR=1.01; (P=0.967)
Not significant and opposite effect direction!• Fine & Gray’s Model: MUD vs Sib:
β = -0.33 (se=0.16); RR=0.72; (P=0.039)
Significant and CORRECT effect direction!
• Other directly modeling approaches gives similar results
Adjusted Cumulative Incidence Curve
• For non-competing risks data, we often plot ADJUSTED SURVIVAL CURVES, which estimate likelihood of outcomes in populations with similar prognostic factors based on regression model
• For RELAPSE, treating TRM as censored event [1- Adjusted Survival Curves] overestimate relapse rate
• Unadjusted CIF curves do not adjust potentially unbalanced treatment cohorts
• One can plot adjusted CIF curves
0 12 24 36 48 60
010
2030
Months
Pro
babi
lity
(%)
1 - Adjusted Survival of Relapse(Treating TRM as Censored)
HLA-Id Sibling (N=1224)Matched Unrelated (N=383)
0 12 24 36 48 60
010
2030
Months
Pro
babi
lity
(%)
Un-Ajdusted CIF of Relapse
HLA-Id Sibling (N=1224)Matched Unrelated (N=383)
Gray's Test: P=0.12
0 12 24 36 48 60
010
2030
Months
Pro
babi
lity
(%)
Ajdusted CIF of Relapse
HLA-Id Sibling (N=1224)Matched Unrelated (N=383)
Fine&Gray's Model:
P=0.039
Adjusted Cumulative Incidence Functions of Relapse
Study GVL (Graft-versus-leukemia) Effect
• At time of TX, it is unknown who will develop GVHD
• GVHD should be treated as time-dependent covariate when analyzing GVL effect of fitting a Cox model
• Directly modeling CIF with time-dependent covariate needs to be developed
Epidemiology of RelapseConclusions
• Relapse a problem, no improvements in decades• AlloHCT can overcome high risk disease biology • Developing strategies to identify best transplant
candidates while malignancy is in more treatable stage – a high priority research
• RIC vs. MAC to be evaluated in concurrent cohorts • Few data on risks and outcomes after relapse• Few data on impact of new targeted therapies• Few data on relapse and management in cGVHD
Epidemiology of RelapseConclusions cont.
• Better understanding of MRD impact pre and post transplant
• Larger data sets needed with higher detail of information, retrospective and prospective multi-center collaboration
• Enhance and refine statistical analyses in application and research
• Publication bias! • Opportunities multiple! – discipline in careful
studying is needed