Title: Patient profiling and predictors of response and non-response to RA therapies
1Patient profiling and predictors of response and
non-response to RA therapies
- Workshop 3 Chairs
- Edward Keystone Professor of Medicine,
University of Toronto, Toronto, Canada - John IsaacsProfessor of Clinical Rheumatology,
Newcastle University, UK
2Overview of Workshop 3
- We will explore the use of biomarkers in patient
profiling and prediction of response/non-response
to RA therapies - How far have we come in the use of biomarkers for
clinical diagnosis and prognosis of RA? - Is there any evidence that biomarkers can predict
responsiveness to biologic therapies? - Can registry data identify prognostic factors for
clinical remission? - How close are we to personalised medicine in
RA? - Talk-show format with the Chairman as host
and a panel of expert guests who will present
their evidence - Discussion using question cards or microphones
Please note that there will be a time limitation
for the question session in order to finish each
workshop on time for the live-link summary
transmission
3Patient profiling and predictors of response and
non-response to RA therapies
- Introduction Session Chair Edward Keystone
- Use of biomarkers in clinical diagnosis and
prognosis in RA Eugen Feist - Biomarkers and predictors of responsiveness to
biologics in RA John Isaacs - Registry evidence the Italian experience
Gianfranco Ferraccioli - The demand for personalised healthcare
Identifying theB-cell patient Philippe
Dieudé - Summary Session Chair John Isaacs
4Patient profiling and predictors of response and
non-response to RA therapies
- Dr Edward Keystone
- Professor of MedicineUniversity of
TorontoToronto, Canada
5Patient RB
- 41 years old
- School teacher
- No background medical problems
- Family history
- Mother had osteoarthritis
6History of joint symptoms
- Left knee intermittent pain and swelling for
the past 3 years - Swelling of the wrists and finger joints
- EMS x 4.5 hours
- Rx Diclofenac 50 mg tid
7Rheumatology specialist unit referral _at_ 3 years
- On examination
- Mild generalised hypermobility
- Finger joint tenderness, but no swelling
- Left knee tenderness (medial colateral ligament)
- Bilateral pes planus
8Investigations and management
- X-rays no erosions on hands and feet
- Rheumatoid factor negative
- ANA negative
9Pre-rheumatoid arthritis clinic referral
- Anti-CCP antibody
- Using CCP2 lt7 normal 710 equivocal gt10
abnormal - This patient's result was equivocal on two
occasions (9) - Later, when she developed definite synovitis the
result was 14 - Ultrasound power Doppler
10Summary
- Potentially inflammatory symptoms
- Subsequent synovitis on physical examination
confirmed by - Equivocal and then positive CCP
- Power Doppler signal MCPs on ultrasound
11Whats the evidence?
- When asked how confident I am about this
patients diagnosis
12 VERY
13Whats the evidence?
- When asked how confident I am about this
patients prognosis
14 I HAVE NO IDEA!
15Use of biomarkers in clinical diagnosis and
prognosis of RA
- Dr Eugen Feist
- Department of Rheumatology and Clinical
Immunology Charité Universitätsmedizin,
Berlin, Germany
16Goal Early diagnosis and stratification
Clinical Examination
Novel Markers
Improved Imaging
ACPA
Ubiquitous
Profiling
Nienhuis et al., ARD 1964 Young et al., Br Med.
J 1979 Schellekens et al., JCI 1998
17Anti-CCP antibodies precede disease onset
Half of patients were IgM-RF and/or anti-CCP 4.5
years (median) before the onset of disease
(0.113.8 years)
50
IgM-RF Anti-CCP IgM-RF or anti-CCP
40
30
Sensitivity (percentage positivity)
20
10
0
Years before symptoms 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1
Number of samples 3 14 25 27 40 51 67 79 89 99 115 99 120 120 130
Nielen et al. Arthritis Rheum 200450380-86
Anti-CCP, anti-cyclic citrullinated peptide
18Half of patients with undifferentiated arthritis
develop confirmed RA at 1 year
Test Anti-CCP 1 Anti-CCP 2
Patients (n) 1327 2017
Mean disease duration at baseline, months 16 5
Median duration of follow-up, months 12 (1224) 12 (1236)
Patient anti-CCP at baseline, 23 23
Patients with confirmed RA at end of follow-up, 45 51
Patient anti-CCP at diagnosis, 46 51
Odds ratio 20 25
Avouac et al. Ann Rheum Dis 200665845851
19Structural comparison of CCP and mutated
citrullinated vimentin (MCV)
CCP synthetic peptides of app. 20 AA (1 - 2
potential epitopes)
Human Vimentin recombinant protein of 54 kD and
app. 45 arginins modified by enzymatic
deimination and mutation e.g. STRSVSSSSYXXMFR TYS
LGSALRPSTSXSLYASSPXR GPGTASRPSSSR
X Citrullination (Arg--gtCitr) R
g/c-Transversion (Gly--gtArg) X
g/c-Transversion (Gly--gtArg) and citrullination
(Arg--gtCitr) G,T New tryptic cleavage site
caused by g/c-Transversion
Bang et al., Arthritis Rheum 2007
20Comparison of autoantibodies against
citrullinated antigens
Anti-MCV ELISA Anti-CCP ELISA
RA (n 1151) positive 950 831
Healthy (n232) positive 4 8
Specificity () 98 96
Sensitivity () 82 72
Correlation to DAS28 (ESR) 0.4038 (P lt0.0001) 0.0968 (P 0.1873)
Bang et al., Arthritis Rheum 2007
21Anti-MCV in early RA Higher sensitivity and
extended prognostic value
- 273 patients with early RA
- Anti-MCV Sensitivity 70.7 Specificity 95
- Anti-CCP Sensitivity 57.9 Specificity 96
- Anti-MCV predictive for high disease activity
10
7.5
SJC
5
p lt 0.01 p lt 0.001
2.5
0
0
3 months
1 year
2 years
3 years
5 years
Mathsson et al., Arthritis Rheum 2008
22Anti-MCV in early RA Higher sensitivity and
extended prognostic value
TJC
DAS28
10
8
6
6
5
4
4
3
2
2
0
1
0
3 months
1 year
2 years
3 years
5 years
3 months
1 year
2 years
3 years
5 years
0
P lt 0.05 P lt 0.01
Mathsson et al. Arthritis Rheum 200858(1)3645.
23Anti-MCV appears to perform better than anti-CCP
in identifying poor radiological prognosis in
early RA
Increase in Larsen score (2 years) p-value
RF 7.25 0.0258
RF- 6.25 0.0258
Anti-CCP 7.375 0.0126
Anti-CCP- 6.25 0.0126
Anti-MCV 7.5 0.0034
Anti-MCV- 5.25 0.0034
Mann-Whitney U test
Mathsson et al., Arthritis Rheum 2008
24Decrease in anti-CCP titres reported to be
associated with treatment efficacy
Evolution of anti-CCP titres in
adalimumab-treated patients
NS
ND
P0.001
NS
Anti-CCP titre
Atzeni, et al. Arthritis Res Ther. 20068(1)R3.
25Analytic precision and diagnostic performance of
different anti-CCP assays
Manufacturer Cut-off (units) Sensitivity (95 CI) Sensitivity (95 CI) Specificity (95 CI) Specificity (95 CI)
Aesku 68 60 0.4970.696 89.1 0.8390.930
Astra 11 61 0.5070.706 92.6 0.8800.957
Axis-Shield 5 71 0.6000.787 97 0.9570.996
Eurodiagnostica 25 75 0.6530.831 97 0.9360.989
Euroimmun 5 73 0.6320.813 98.5 0.9570.997
Genesis 6.2 61 0.5070.706 94.6 0.9040.972
Inova 2 20 66 0.5580.751 97 0.9360.989
Inova 3.0 20 73 0.6320.813 96 0.9130.982
Inova 3.1 50 74 0.6420.822 89.6 0.8450.934
Orgentec 20 72 0.6210.805 93.1 0.8860.961
Phadia 10 74 0.6420.822 98.5 0.9570.996
Bizzaro et al., Clin Chem 2007
26Novel rapid point of care tests
- Comparison of CCPoint and standard CCP2-ELISA in
109 RA, 351 non-RA, 420 HD - CCPoint test was fast, valid and reliable
(sensitivity specificity 95) - Comparison of RheumaChec and standard MCV-ELISA
in 80 RA, 83 non-RA and 200 HD - Sensitivity of MCV patients in whole blood 70.2
(serum 94.7) and specificity 98.9
Snijders GF et al., Scand J Rheumatol 2008
27Autoantibodies as prognostic markers in RA
RF
CCP/MCV
App. 70
Erosive manifestation
Seropositive
App. 30
Mild manifestation
Seronegative
28Summary
- Anti-CCP antibodies precede RA occurrence
- Citrullination modifies potential autoantigens
and likely plays an important role in the
pathogenesis of RA - Detection of anti-CCP significantly improves the
diagnosis of early RA - Anti-CCP and anti-MCV immunoassays provide a
comparable diagnostic sensitivity and specificity
29What does this mean for Eds patient?
- Anti-CCP provides a high diagnostic probability
in an RF-negative patient with undifferentiated
arthritis
30(No Transcript)
31Biomarkers and predictors of responsiveness to
biologics in RA
- Professor John Isaacs
- Professor of Clinical RheumatologyNewcastle
UniversityNewcastle, UK
32What evidence is available that response to
therapy can be predicted?
33Predictors of responsiveness to TNF inhibitors
- Clinical factors
- Serological biomarkers
- Genetic biomarkers
34Clinical factors that predict responsiveness to
TNF inhibitors
- n2879 (1267 ETA, 1612 INF)
- Poorer response
- higher baseline HAQ
- current smoker (INF, OR 0.77 CI 0.600.99)
- Better response
- current use of NSAIDs
- current use of MTX (ETA, OR 1.82 CI 1.382.40)
35RF, anti-CCP and genetic variants Association
with response to TNF inhibitors
- n642 (278 ETA, 296 INF, 68 ADA)
- RF and anti-CCP negativity associated with better
response - SE, PTPN22 status not associated with response
- Females less likely to achieve remission
Potter C et al. Ann Rheum Dis. 20096869-74.
Epub 2008 Mar 28
36Autoantibodies in TNF inhibitor treated RA
patients
Predictor n () Mean DAS score (SD) Mean DAS score (SD) Association
Predictor n () Baseline Improvement Association
RF -ve 59 (11) 6.72 (1) 3.03 (1.7) p0.02
RF ve 462 (89) 6.59 (1) 2.43 (1.5) p0.02
Anti-CCP -ve 96 (18) 6.61 (1) 2.90 (1.6) p0.02
Anti-CCP ve 425 (82) 6.61 (1) 2.40 (1.5) p0.02
Analyses were performed in 521 patients for whom
serum samples were available. p-values stated are
for linear regression, adjusted for concurrent
DMARD, gender, baseline HAQ and DAS28 score.
Potter C et al. Ann Rheum Dis. 20096869-74.
Epub 2008 Mar 28
37Response to TNF inhibitors may decline with
increasing anti-CCP titre
- 236 etanercept patients
- CCP ve lt50 u/mL CCP ve gt50 u/mL lt1600
u/mL CCP high ve gt1600 u/mL - CCP high 27 of population
Etanercept EULAR responses according to CCP status
90
80
70
60
Patients ()
EULAR no response
50
EULAR response
40
30
20
10
0
CCP -ve
CCP ve
CCP high ve
Drynda S et al. ACR 2008
38Genetic factors in anti-TNF treatment response
Candidate genes Studies
TNF 15 studies mostly -308 SNP
SE and extended MHC 6 studies
TNFR2 5 studies exon 6 Met196Arg SNP
TNFR1 1 study exon 1 Pro12Pro SNP
Fc?R3a 2 studies Val158Phe SNP
Other cytokines/receptors 1 or 2 studies each
- Results are inconsistent and inconclusive
- Small sample sizes and limited power (n50300)
- Varied designs (e.g. TNF inhibitor, disease,
outcome) - Investigate individual polymorphisms
39Example TNF-308 promoter SNP
Study Samples Drug Outcome (month(s)) Association
Miceli-Richard et al 2008 354 French ADA ACR (3) Haplotype
Ongaro et al 2008 105 Italian All 3 ACR (3, 6, 12) No
Pinto et al 2008 113 Spanish INF DAS28 (8) No
Guis et al 2007 86 French ETA DAS28 (6, 12) Yes
Cuchacovich et al 2006 70 Chilean ADA Both (2, 4, 6) No
Lee et al 2006 311 Mixed All 3 Both (mixed) Yes
Seitz et al 2006 86 Swiss All 3 DAS28 (6) Yes
Marotte et al 2006 198 French INF ACR (8) No
Maxwell et al 2008 1041 British INF, ETA DAS28 (6) Yes
Performed multivariate and haplotype analyses
Meta-analysis incorporating 6 additional
studies Study involved RA, PsA and AS
40Predictors of responsiveness to rituximab
- Serological biomarkers learnings from
- The DANCER study
- The REFLEX study
41Dose-ranging Assessment iNternational Clinical
Evaluation of Rituximab in RA (DANCER)
Emery et al 2006. Arth Rheum 2005541390-400
42DANCER study ACR responses at 6 months RF
ve vs RF -ve patients, ITT
Roche, data on file
43DANCER study Placebo-adjusted ACR responses at
6 months RF ve vs RF -ve patients
RF positive
RF negative
Roche, data on file
44A Randomised Evaluation oF Long-term Efficacy of
rituXimab in RA (REFLEX)
Cohen S et al. Arthritis Rheum 2006542793-806
45REFLEX study ACR responses at Week 24 in RFve
vs RF-ve patients (ITT)
RF positive (ITT) RF negative (ITT)
plt0.0001
54
plt0.0009
41
plt0.0001
29
NS
19
plt0.0001
17
p0.045
13
12
9
6
5
2
0
ACR20 ACR50 ACR70
ACR20 ACR50 ACR70
ACR20 ACR50 ACR70
ACR20 ACR50 ACR70
Placebo (n160)
Rituximab 1000 mg x 2 (n160)
Rituximab 1000 mg x 2 (n64)
Placebo (n41)
Cohen et al, 2006 Smolen et al. 2006
46REFLEX study Placebo-adjusted ACR responses at
Week 24 in RFve vs RF-ve patients (ITT)
RF positive (ITT) RF negative (ITT)
Patients ()
Rituximab 1000 mg x 2 (n234)
Rituximab 1000 mg x 2 (n64)
Cohen et al, 2006 Smolen et al. 2006
47REFLEX study ACR responses at Week 24 according
to RF and anti-CCP status
RF and/or anti-CCP positive
RF negative and anti-CCP negative
Patients ()
ACR20 ACR50 ACR70
ACR20 ACR50 ACR70
ACR20 ACR50 ACR70
ACR20 ACR50 ACR70
Placebo (n107)
Rituximab (n157)
Rituximab (n29)
Placebo (n16)
Tak et al, ACR 2006
48REFLEX study Placebo-adjusted ACR responses at
Week 24 according to RF and anti-CCP status
RF and/or anti-CCP positive
RF negative and anti-CCP negative
Patients ()
Rituximab (n157)
Rituximab (n29)
Cohen et al, 2006 Smolen et al. 2006
49REFLEX Study 56 week radiographic outcomes
seropositive subgroups
RF and/or anti-CCP positive
RF negative and anti-CCP negative
P0.0085
P0.0225
P 0.0018
Roche, data on file
50Summary
- Conflicting reports of association between TNF
polymorphisms and clinical response to TNF
inhibitors - Rituximab shows consistent association with RF
and/or anti-CCP as the biomarkers predictive of
clinical response - RA patients who are seropositive (RF and/or
anti-CCP) appear to have an enriched response to
rituximab
51The FUTURE
- Data from SERENE, MIRROR and IMAGE studies of
rituximab will provide an additional opportunity
to assess serological biomarker association with
clinical response - Further studies of biomarkers with the range of
biological therapies are warranted to fully
assess their potential role in predicting response
52What does this mean for Eds patient?
- Seropositivity suggests a better outcome with
rituximab
53(No Transcript)
54Registry evidence the Italian experience
- Professor Gianfranco Ferraccioli
- Professor of RheumatologyDirector Division of
RheumatologySchool of MedicineCatholic
University of the Sacred HeartRome, Italy
55Evidence for prognostic factors for clinical
remission
- This presentation will review
- Remission data across countries
- Evidence from databases
- The Italian experience GISEA and other studies
GISEA,Gruppo Italiano per lo Studio delle Early
Arthritis
56Treatment of RA aims at
REMISSION
What are the clinical predictors of response to
therapy and remission?
- Baseline patient characteristics
57Remission and RA Data for patients receiving
usual care (conventional DMARDs) in 24 countries
5,848 patients receiving usual care at 67 sites
in 24 countries
25
ACR
19.6
DAS28
20
Remission ()
CDAI
13.8
15
8.6
10
5
0
Sokka T et al. Arthritis Rheum 2008582642-51
58Prognostic factors of clinical remission on
DMARDs The Quest-RA study
No. patients 5848 Clinical evidence in database No. patients 5848 Clinical evidence in database No. patients 5848 Clinical evidence in database
Baseline variables OR (95 CI)
Sex, female 0.47 (0.390.55)
Disease duration 0.98 (0.970.99)
No. comorbidities 0.76 (0.700.82)
Sokka T et al. Arthritis Rheum 2008582642-51
59Treatment of RA aims at
REMISSION
What are the clinical predictors of response to
rescue therapy for DMARDs failure, and remission?
- Baseline patient characteristics
- Biomarkers
60Prognostic factors for clinical remission with
TNF inhibitors The GISEA study
Mancarella L et al. J Rheumatol 2007341670-73
GISEA,Gruppo Italiano per lo Studio delle Early
Arthritis
61Characteristics of 591 patients with RA at
baseline
Variables Variables
Women () 404 (67)
Age (years) 53.3 12.7
Age at diagnosis (years) 41.5 13.7
Duration of disease (years) 11.6 7.6
Swollen joints (n) 10.4 7.1
Tender joints (n) 17.1 9.4
HAQ score 1.63 0.6
DAS28 5.9 1.2
ESR (mm/h) 41.2 25.0
Patients taking steroids 49
(median mg, range) 5 (17.5)
CRP positivity 72.4
RF positivity ( patients) 79
CRPgt5 mg/L RFgt20 IU/ml. DAS, Disease Activity Score ESR, erythrocyte sedimentation rate HAQ, Health Assessment Questionnaire RF rheumatoid factor. CRPgt5 mg/L RFgt20 IU/ml. DAS, Disease Activity Score ESR, erythrocyte sedimentation rate HAQ, Health Assessment Questionnaire RF rheumatoid factor.
Mancarella L et al. J Rheumatol 2007341670-73
62Characteristics of patients at baseline
according to RF status
Variables RF positivity RF negativity p-value
(n467) (n124)
Sex, women 66 70
Age (years) 53.6 12.9 53.1 12.8 0.63
Age at diagnosis (years) 41.8 13.5 41.1 15.0 0.73
Duration of disease (years) 11.8 7.5 12.0 8.1 0.87
Swollen joints (n) 10.6 7.4 9.3 6.1 0.15
Tender joints (n) 17.4 9.5 15.4 8.8 0.05
HAQ score 1.7 0.7 1.5 0.6 0.04
DAS28 6.0 1.2 5.7 1.1 0.02
ESR (mm/h) 41.5 4.5 39.9 7.2 0.40
CRP (mg/L) 22.6 24.8 19.6 22.9 0.06
C-reactive protein positivity CRPgt5 mg/L
Mancarella L et al. J Rheumatol 2007341670-73
63Prognostic factors for clinical remission with
TNF inhibitors
No. patients 591 Clinical evidence in database No. patients 591 Clinical evidence in database No. patients 591 Clinical evidence in database
Baseline variables OR (95 CI)
Age (53 years) 0.64 (0.440.94)
HAQ score (1.63) 0.56 (0.380.83)
RF (positivity) 0.61 (0.390.96)
Sex (female/male) 24 vs 36 p0.03
- Hosmer-Lemeshow test p0.935. Hosmer-Lemeshow
test p0.554.
Mancarella L et al. J Rheumatol 2007341670-73
64Significantly better EULAR responses on
follow-up in RF-negative patients
EULAR response RF-positive patients RF-negative patients p-value
n () n ()
Good 164 (37) 60 (50) 0.01
Moderate 241 (37) 45 (54) 0.001
Remission 112 (24) 43 (36) 0.03
Mancarella L et al J Rheumatol 2007341670-73
65Is there a correlation between RF isotype and
clinical response to TNF inhibitors?
Bobbio-Pallavicini F et al. Ann Rheum Dis
200766302-7
66Investigation of a correlation between RF
isotype and clinical response to TNF inhibitors
- 132 patients
- Advanced RA, DMARD-IR
- Treated with
- infliximab (n63)
- etanercept (n35)
- adalimumab (n34)
- 1 year follow-up
- 126 evaluable for clinical response
- IgM, IgA and IgG rheumatoid factors and anti-CCP
antibodies assessed
Bobbio-Pallavicini F et al. Ann Rheum Dis
200766302-7
67Trend for higher levels of RF and anti-CCP
titres in non-responders to TNF inhibitors
Responders (n83) Non-responders (n43) p-value
RF (nephelometry), positive 83.13 (69/83) 83.72 (36/43) 1
Level 86 (15268.4) 97 (28338) 0.769
IgM RF, positive 78.31 (65/83) 83.72 (36/43) 0.638
Level 41.5 (22.1120) 67.6 (32.9295) 0.035
IgA RF, positive 61.44 (51/83) 69.76 (30/43) 0.434
Level 24.8 (10.290.8) 130.4 (13.8276.7) 0.003
IgG RF, positive 57.83 (48/83) 69.76 (30/43) 0.246
Level 24.3 (7.294.9) 46.1 (13.2210.6) 0.057
Anti-CCP, positive 72.28 (60/83) 81.39 (35/43) 0.285
Level 25.27 (2.9374.27) 35.28 (7.32114.99) 0.233
The negative RF samples were included and
counted with the measured values.
Bobbio-Pallavicini F et al. Ann Rheum Dis
200766302-7
68High IgA RF levels are associated with poor
clinical response to TNF inhibitors
Percentage of responders
Bobbio-Pallavicini F et al. Ann Rheum Dis
200766302-7
69Take home messages
- Prognostic factors and predictive factors for
clinical response and remission have been
identified - Predictive factors have been delineated both in
RCTs and in real world patients treated with TNF
inhibitors - Baseline predictors HAQ, gender
- Biomarker predictors RF, RF/CCP and high IgA
RF levels predict a poor response to TNF
inhibitors
Mancarella L et al J Rheumatol 2007
3416701673 Bobbio-Pallavicini et al. Ann
Rheum Dis 200766302-307 Potter C, et al Ann
Rheum Dis. 2009 Jan68(1)69-74. Epub 2008 Mar 28.
70What does the future hold?
- Biomarkers that can predict clinical response to
TNF inhibitors still remain to be defined in well
controlled, prospectively assessed cohorts of
patients - Greater knowledge of predictive factors in our
patients will enable us to develop better
personalised treatment strategies - Appropriate tailored treatment will reduce
treatment failure and stop disease progression
more quickly
71Conclusions
- Biomarkers and clinical markers should be studied
more and more to help the clinicians to tailor
their therapeutic strategy in daily practice - Clinical scores and possibly some biomarkers
could be adopted to target the therapeutic
intervention - The therapeutic algorithm still needs to be fully
defined according to the targets to treat in
subsets of RA patients
72Acknowledgements
- Bari
- Ferrara
- Modena
- Padova
- Perugia
- Ancona
- Roma
- Brescia
- Milano 1
- Milano 2
- Verona
- Pavia
- LAquila
- Palermo
- Genova
- Siena
73What does this mean for Eds patient?
- Seropositivity suggests a lower probability of a
response to a TNF inhibitor
74(No Transcript)
75The demand for personalised healthcare
Identifying the B cell patient
- Dr Philippe Dieudé
- Rheumatology Department, University Bichat
Hospital, Paris, France
76Background
- CTDs and autoimmune diseases (AIDs) share a
common genetic background - HLA II
- Non-HLA genes PTPN22, IRF5, STAT4, BANK1and
more - A common genetic background could lead to an
overlap of different autoimmune phenotypes - Frequency of overlap syndrome in other AIDs
- Sjögren 25
- Type 1 diabetes 5-20
- SSc 23
Alarcon Segovia M. Curr Rheumatol Rep
20046(3)171-4 Hemminki K Arthritis Rheum 2009
(3)661-668 Garcia-Carrasco M. Medicine
(Baltimore) 2002 81 (4)270-280 Somers EC.
Epidemiology 200617(2)202-217 Liao KP.
Arthritis Rheumatism 2009 60(3)653-660 Avouac
J. Arthritis Rheumatism 2008 58
(9-suppl) S826
77Objectives
- To determine
- Frequency of overlap syndrome in the RA
population - Whether overlap syndromes are restricted to a
particular RA subset
78Study 1 Frequency of an enriched
immunological phenotype in the RA population
- Prospective study
- 6 months /114 patients with RA (ACR 1987
criteria) - Screening of all RA patients for an enriched
immunological phenotype - Anti-CCP, RF
- Anti-SSA,anti-SSB
- AI Thyroiditis
- Anti-parietal cells
- Anti-smooth muscle
- Anti-DNAn
- ACA, anti-Topo I, anti-RNP
Non-RA specific autoantibodies
79Frequency of non-RA specific autoantibodies in
the RA population
80Characteristics of the 55 patients with RA with
enriched immunological phenotype
Characteristic Value
Female, 82
Mean (SD) age, years 53.8 (12.3)
Mean (SD) disease duration, years 10.4 (8.2)
Erosive disease, 78
Anti-CCP, 100
RF, 85
81Immunological phenotypes in RA patients
80.8
30.7
15.4
11.5
82RA phenotype according to non-RA- specific
autoantibody status
83Frequency of overlapping autoimmune diseases
38
Frequency of overlapping AID in the global RA
sample 18
84Study 2 Screening patients with RA for
overlapping autoimmune diseases
- Prospective study (18 months)
- 334 patients with RA
- 2 Rheumatology Departments (Cochin Bichat
University Hospital, Paris) - 117 patients included (35)
- RA ACR 1987 criteria
- Diagnosis criteria for another AID
- 21 currently treated with rituximab
85Characteristics of the 117 patients with RA with
overlapping AID
Characteristic Value
Female, 88
Mean (SD) age, years 56.7 (11.3)
Mean (SD) disease duration, years 14.3 (9.7)
Erosive disease, 78
Anti-CCP, 92
RF, 88
86Distribution of overlapping AID in the RA
population
87Distribution of overlapping AID in the RA
population
88RA phenotype according to the overlap syndrome
Plt0.001
Plt0.004
89Summary
- Co-occurrence of other AIDs with RA is frequent
(1835) - A particular RA phenotype
- No statistical significant difference between RA
patients with overlapping AIDs and those without - Erosions
- Mean age at onset
- Mean disease duration
- Significant difference
- Anti-CCP and RF positive status
- High anti-CCP production
90Questions and Perspective (1)
- Do these RA patients have a strong B
cell-driven disease? - Anti-CCP and RF
- High anti-CCP production
- Other autoantibodies
91Questions and Perspective (2)
- Influence of anti-CCP status in RTX response?
- Unclear
- Which isotype?
- Low anti-CCP IgM patients responded better to RTX
- Anti-CCP IgM production is related to CD20-,
CD79a B cell - Re-analyse RTX responses according to
- Anti-CCP status
- Qualitative anti-CCP status (isotype)
- Quantitative anti-CCP status
Tak PP.et al Arthritis Rheum 2006 54 Supl9 S368
Teng YKO et al. Arthritis Rheum 2007
56(12)3909-3918)
92Questions and Perspective (3)
- Is rituximab more efficient in this particular RA
patient segment? - Our studies were not designed to detect such
effect - Re-analyse RTX response according to
- Enriched immunological phenotype
- Overlapping AIDs
- Personal experience of overlapping AIDs with RA
- All were responders (EULAR)
- 79 received a 2nd course of RTX, 54 a 3rd
course
93What does this mean for Eds patient?
- There is not enough biomarker data for this
patient to suggest an overlapping AID
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95Patient profiling and predictors of response and
non-response to RA therapies
- Workshop Summary
- John Isaacs
- Professor of Clinical Rheumatology, Newcastle
University, UK
96Exploring the use of biomarkers in patient
profiling and prediction of response/non-response
to RA therapies
97How far have we come in the use of biomarkers for
clinical diagnosis and prognosis of RA?
Conclusions
- Anti-CCP antibodies can be detected prior to RA
occurrence
- Detection of anti-CCP significantly improves the
diagnosis of early RA
- Citrullination modifies potential autoantigens
and plays an important role in the pathogenesis
of RA
- Anti-CCP and anti-mutated citrullinated vimentin
(MCV) immunoassays have comparable diagnostic
sensitivity and specificity
98Is there any evidence that biomarkers can predict
responsiveness to biologic therapies?
Conclusions
- Conflicting reports of association between TNF
polymorphisms and clinical response to TNF
inhibitors
- Rituximab shows consistent association with RF
and/or anti-CCP as the biomarkers predictive of
clinical response
- RA patients who are seropositive (RF and/or
anti-CCP) appear to have an enriched response to
rituximab
99REFLEX study Placebo-adjusted ACR responses at
Week 24 according to RF and anti-CCP status
RF and/or anti-CCP positive
RF negative and anti-CCP negative
Patients ()
Rituximab (n157)
Rituximab (n29)
Cohen et al, 2006 Smolen et al. 2006
100REFLEX Study 56 week radiographic outcomes
seropositive subgroups
RF and/or anti-CCP positive
RF negative and anti-CCP negative
P0.0085
P0.0225
P 0.0018
Roche, data on file
101Can RCT and registry data identify prognostic
factors for clinical remission? Conclusions
- Yes prognostic for clinical response and
remission have been identified, but require
further investigation
- TNF inhibitors
- Baseline predictors HAQ, gender
- Biomarker predictors RF, RF/CCP and high IgA
RF levels predict a poor response to TNF
inhibitors - Biomarkers that can predict good clinical
response to TNF inhibitors still remain to be
defined
102Prognostic factors for clinical remission with
TNF inhibitors
No. patients 591 Clinical evidence in database No. patients 591 Clinical evidence in database No. patients 591 Clinical evidence in database
Baseline variables OR (95 CI)
Age (53 years) 0.64 (0.440.94)
HAQ score (1.63) 0.56 (0.380.83)
RF (positivity) 0.61 (0.390.96)
Sex (female/male) 24 vs 36 p0.03
- Hosmer-Lemeshow test p0.935. Hosmer-Lemeshow
test p0.554.
Mancarella L et al. J Rheumatol 2007341670-73
103Significantly better EULAR responses on
follow-up in RF-negative patients
EULAR response RF-positive patients RF-negative patients p-value
n () n ()
Good 164 (37) 60 (50) 0.01
Moderate 241 (37) 45 (54) 0.001
Remission 112 (24) 43 (36) 0.03
Mancarella L et al J Rheumatol 2007341670-73
104High IgA RF levels are associated with poor
clinical response to TNF inhibitors
Percentage of responders
Bobbio-Pallavicini F et al. Ann Rheum Dis
200766302-7
105How close are we to personalised medicine in
RA? Conclusions
- Studies have shown
- Co-occurrence of other autoimmune diseases (AIDs)
in patients with RA is frequent (1835) - More common in a particular RA subset anti-CCP
and RF
106Frequency of overlapping autoimmune diseases
38
Frequency of overlapping AID in the global RA
sample 18
107RA phenotype according to the overlap syndrome
Plt0.001
Plt0.004
108Take home message
- Biomarkers will become increasingly important in
the management of the patient with synovitis - Diagnosis
- Prognosis
- Treatment
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