A quantitative approach to accurate classification of RA. Tom Huizinga

Overview of seminar RA as a disease versus syndrome - perspective from a disease - perspective from a syndrome Treatment and being quantitative - early treatment - treatment focussed at a target - is there any difference in the way a target is defined?

Classification: syndrome versus disease RA=classic syndrome defined by criteria. Now new criteria based on the decision to start with MTX. RA as a disorder based on pathogenesis Syndrome Disease Disease subsets with a pathway leading to symptoms

244 (58%)109 (51%)42 (21%)- / (36%)88 (41%)111 (55%)+ / - 26 (6%)16 (7%)50 (25%)+ / + negativepositive Anti-CCP antibodies ControlsLeiden EAC RA patients SE-status* Association between anti-CCP-responses and HLA-DRB1 SE-alleles OR allele frequency: CCP+ vs Controls:3.38 ( ) CCP- vs Controls:1.22 ( ) Huizinga TW…..Criswell L, A&R, 2005

RA consists of two syndromes: ACPA+ versus ACPA- ACR-classification proces: define disease based on characteristic cases ACPA+ versus ACPA- What about other risk factors? Histology? Clinical Course? Treatment response?

RA consists of two syndromes: ACPA+ versus ACPA- ACR-classification proces: define disease based on characteristic cases ACPA+ versus ACPA- HLA-SE PTPN22 rs- C5-TRAF1 rs- TNFAIP3-OLIG3 rs- CTLA4 rs- STAT4 rs- CCL21 rs-MMEL1-TNFRSF14 rs-CDK6, PRKCQ, KIF5A CD40, IL2RA, IL2RB HLA-DR3 rs- IRF5 rs- STAT4 Raychaudhuri S et al. Nat Genet Oct;40(10): van der Helm A & Huizinga T. Arthr Res Ther. 2008;10(2):205. Huizinga et al. A&R, Arthritis Rheum Nov;52(11):

Conclusions Synovitis of anti-CCP positive RA differs from anti- CCP negative: More infiltrating lymphocytes in anti-CCP positive RA More fibrosis and increased synovial lining layer in anti-CCP negative RA Difference is already present early in the disease van Oosterhout M, Bajema I, Levarht EW, Toes RE, Huizinga TW, van Laar JM. Arthritis Rheum Jan;58(1):53-60

Phenotype clearly different Joint destruction over time drug free remission rate Fulfillment of the criteria for RA after 1 Year2 Years3 Years # 69 CCP+ Pts83%90%93% 249 CCP- Pts18%24%25% 318 Pts32%38%40%

Can the Course of UA being altered by Early Therapy ?  Undifferentiated Arthritis  ACR-criteria RA  if so verum MTX Inclusion:Primary End point: Increase MTX based on DAS Placebo t = 0 t = 3t = 12 t = mg 6 tabs 0 mg 0 tabs 15 – 30 mg 6 – 12 tabs t = 6t = 9 t = 15 MTX Taper MTX to 0

Anti-CCP pos group (n=27) p= Anti-CCP neg group (n=83) p=0.51 Time to diagnosis RA (months) Cumulative Survival (%) MTX group Placebo group Months Follow-up

Anti-CCP pos group (n=27) p=0.03 Anti-CCP neg group (n=83) p=0.46 Radiographic progression (Sharp/van der Heijde score) Cumulative probability (%) MTX group Placebo group Radiographic Progression

DAS in time stratified MTX Placebo DAS Time (months) ACPA pos ACPA neg

Summary of ACPA positive versus ACPA negative RA HLA, PTPN22, smoking point to two diseases C5-TRAF point to two diseases Output of WGAS studies point to two diseases Phenotypic data more “formally” studied Histological differences Subanalysis of PROMPT-study Propose as new criteria RA-type 1 and RA-type 2, to get criteria closer to pathogenesis

Overview of seminar RA as a disease versus syndrome - perspective from a disease - perspective from a syndrome Treatment and being quantitative - early treatment - treatment focussed at a target - is there any difference in the way a target is defined?

Chronic, destructive polyarthritis Slowly progressive Rapidly progressive General population Undifferentiated arthritis Timing and Uncertainty Window of Opportunity hypothesis Concept of time not a biological basis Criteria discussion leads to nosology – better to stick to probabilities Biology of probabilities – masterswitch Tom Huizinga. Personal data

Since patients included with > two year follow-up 800 undifferentiated arthritis 900 RA 700 other diagnosis Diagnosis at inclusion Lessons from Leiden Early Arthritis Cohort 40 % remission40 % RA

Prediction Rule for Development of RA 1. What is the age? Multiply with What is the gender?In case female1 point________ 3. How is the distribution of involved joints? In case small joints hands or feet: 0.5 point________ In case symmetric0.5 point________ In case upper extremities1 point________ Or: In case upper & lower extremities 1.5 points ________ 4. What is the length of the morning stiffness (minutes)? In case 30–59 minutes0.5 point________ In case ≥60 minutes1 point________ 5. What is the number of tender joints? In case 4–100.5 point________ In case 11 or higher1 point________ 6. What is the number of swollen joints? In case 4–100.5 point________ In case 11 or more1 point________ 7. What is the C-reactive protein level (mg/L)? In case 5–500.5 point________ In case 51 or higher1.5 points________ 8. Is the rheumatoid factor positive? If yes1 point________ 9. Are the anti-CCP antibodies positive? If yes2 points ________ TOTAL SCORE:________ van der Helm-van Mil AH, et al. Arthritis Rheum 2008;58:2241–7

Predicted Risk on RA vs Prediction Score AUC Replicated in UK, Norway, Germany, Japan, Middle east and Latin America AUC=area under the curve; van der Helm-van Mil AH, et al. Arthritis Rheum 2008;58:2241–7

Prediction Thinking is Now Implemented in the 2010 Criteria 1.Age (multiply by 0.02) 2.Gender (female 1) 3.Distribution of involved joints –Small joints hands and feet (0.5) –Symmetric (0.5) –Upper extremities (1) or upper and lower extremities (1.5) 4.VAS morning stiffness –26–90 mm (1) –90 mm (2) 1.Morning stiffness 2.Arthritis of 3 or more joint areas 3.Arthritis of hand joints 4.Symmetric arthritis 5.Rheumatoid nodules 6.Serum rheumatoid factor 7.Radiographic changes 1. Joint involvement – 1 medium-large joint (0) – 2–10 medium-large joints – 1–3 small joints (large joints not counted) (2) – 4–10 small joints (large joints not counted (3) – >10 joints (at least one small joint) (5) 2. Serology –Negative RF and negative ACPA (0) –Low positive RF or now positive ACPA (2) –High positive RF or high positive ACPA (3) 5.Number of tender joints –4–10 (0.5) –11 or more (1) 6.Number of swollen joints – 4–10 (0.5) –11 or more (1) 7.C-reactive protein (mg/L) –5–50 (0.5) –51 or more (1.5) 8.Rheumatoid factor positive (1) 9.Anti-CCP antibodies positive (2) 3.Acute phase reactants –Normal CRP and normal ESR (0) – Abnormal CRP or abnormal ESR (1) 4.Duration of symptoms – <6 weeks (0) – ≥6 weeks (1) Points are shown in parenthesis. Cut point for RA ≥8 points Four of these 7 criteria must be present. Criteria 1 through 4 must have been present for at least 6 weeks Points are shown in parenthesis. Cut point for RA ≥6 points. Patients are also classified as having RA if they have (a) typical erosions; (b) long-standing disease previously satisfying the classification criteria 1. Arnett FC, et al. Arthritis Rheum 1988;31:315-24; 2. New ACR/EULAR diagnostic criteria. Presented at ACR, Philadelphia, 10–16 th October 2009; 3. van der Helm-van Mil AHM, et al. Arthritis & Rheum 2007:56;433–440 ACR 1987 criteria 1 ACR/EULAR 2010 criteria 2 Early Arthritis Prediction 2007-van der Helm 3

A more sensitive tool for identifying early arthritis patients (n=2258 Leiden Early Arthritis Patients) 2010 ACR/EULAR Classification Criteria RA at baselineno RA at baseline 1987 ACR Classification Criteria RA at baseline no RA at baseline Total

Earlier detection of RA 297 patients fulfilled the 1987 ACR criteria during the first year, but not at baseline 202 (68.0%) however did fulfill the 2010 criteria at baseline RA patients classified in an earlier phase of the disease

Performance in early arthritis Outcome Measure MTX-initiationDMARD-initiation5-year Persistency Criteria SetSens.Spec.AUCSens.Spec.AUCSens.Spec.AUC 1987 ACR Classification Criteria ACR/EULAR Classification Criteria

Overview of seminar RA as a disease versus syndrome - perspective from a disease - perspective from a syndrome Treatment and being quantitative - early treatment: biology & observational - treatment focussed at a target - is there any difference in the way a target is defined?

ACPA characteristics :a biomarker of the window of opportunity Population Undifferentiated Artritis Reumatoide Artritis ACPAACPA Few isotypes limited epitope recognition only low avidities Many isotypes extensive epitope recognition high and low avidities No changes in ACPA characteristics The developing autoimmune response associates with worse prognosis

Results pre-RA versus RA 2 Number of epitopes recognized by sera from: Recognition of ≥ 1 peptide: 38% 66% p=0.013 None ≥ 1 peptide pre-RARA Vimentin peptide A Vimentin peptide B Fibrinogen peptide A Enolase peptide Fibrinogen peptide B

Number of epitopes recognized increase from pre-RA to RA Median number of peptides recognized over time

ACPA characteristics :a biomarker of the window of opportunity Population Undifferentiated Artritis Reumatoide Artritis ACPAACPA Few isotypes limited epitope recognition only low avidities Many isotypes extensive epitope recognition high and low avidities No changes in ACPA characteristics What is the relevance of this developing autoimmune response during early artritis?

A broader isotype usage is associated with Radiographic progression * comparison ≤4 isotypes versus ≥5 isotypes: p<0.05 EAC

* comparison ≤4 isotypes versus ≥5 isotypes: p<0.05 A broader isotype usage is associated with Radiographic progression EURIDISS

Aim of early treatment To prevent functional disability To prevent structural damage To prevent comorbidity (cardiovascular disease, amyloidosis) To prevent “MasterSwitches” turned on that induce chronicity Time is important

Delay < 12 weeks associates with: lower rate of joint destruction* higher chance of DMARD-free remission* Conclusion: Delay should be diminished RA-only

Chronic, destructive polyarthritis Slowly progressive Rapidly progressive General population Undifferentiated arthritis Why Recommendation 1: Window of Opportunity Window of Opportunity hypothesis: - Criteria discussion: probabilities. - Biology of probabilities: masterswitch - ACPA only know marker of this process

Overview of seminar RA as a disease versus syndrome - perspective from a disease - perspective from a syndrome Treatment and being quantitative - early treatment: biology & observational - treatment focussed at a target - is there any difference in the way a target is defined?

Importance of patient monitoring: evidence from RCT TICORA 1 –Intensive: monthly, DAS guided –Routine: every 3 months –Remission: 65% (intensive) vs. 16% (routine) CAMERA 2 –Intensive: monthly, computer program –Routine: every 3 months usual care rheumatologist –Remission: 50% (intensive) vs. 37% (routine) 1.Grigor et al. Lancet 2004; 364: 263–269 2.Verstappen et al. Ann Rheum Dis 2007; 66: 1443–1449

Importance of patient monitoring: evidence from longitudinal patient cohorts Early Arthritis Cohort Leiden –Patients treated from ’93–’95 with Pyramid strategy –Patients treated from ’95–’98 with DMARD within two weeks

Comparison after 4 years EAC

Delayed treatment Years after inclusion Survival probability 1993–1995 Survival curves of RA patients and the general Dutch population Early Arthritis Cohort Leiden

Early treatment Years after inclusion Survival probability 1996–1998 Survival curves of RA patients and the general Dutch population Early Arthritis Cohort Leiden

Early, aggressive treatment, goal-driven Years after inclusion Survival probability 1999–2006 Survival curves of RA patients and the general Dutch population Early Arthritis Cohort Leiden

RA management today Remission –Clinical –Radiographic Low disease activity Processes Goals “Remission” Tools “More & Better” More conventional DMARDs Biologics available as highly effective alternatives “More & Better” Early treatment is key Aggressive therapy approach with better results Disease activity measurement (e.g. DAS28)

Overview of seminar RA as a disease versus syndrome - perspective from a disease - perspective from a syndrome Treatment and being quantitative - early treatment: biology & observational - treatment focussed at a target - is there any difference in the way a target is defined? Perspective : ?Biology?-?Swollen joint etc.?-?Function?

Biomarker-based DAS 42 IRIDESCENT Academic database of relationships from abstracts IRIDESCENT Academic database of relationships from abstracts Ingenuity Commercial database of curated scientific facts Ingenuity Commercial database of curated scientific facts Bioinformatics Knowledge bases Literature Review Hundreds of scientific articles and posters Literature Review Hundreds of scientific articles and posters Manual Survey of Scientific Publications Gene Expression 1416 genes with secreted proteins profiled in 424 RA patients Gene Expression 1416 genes with secreted proteins profiled in 424 RA patients Protein Arrays 180 proteins profiled in 410 patients Protein Arrays 180 proteins profiled in 410 patients Proprietary Molecular Profiling Data Review evidence and prioritize Identify Assays: Analysis of Multiple Platforms Identify Assays: Analysis of Multiple Platforms Optimize Assays: Dilutions RF Blocking QC metrics Optimize Assays: Dilutions RF Blocking QC metrics 396 Candidate Markers Shen et al. Stepwise discovery of disease activity biomarkers in rheumatoid arthritis. EULAR 2010; Poster # THU0066

Pre-Analytic Validity: Results Individual Markers BiomarkerAvg. % Difference “OTC” vs. “Fresh” R 2 Conc. [log 10 pg/mL] CRP01.00 EGF ICAM IL IL6-R00.56 IL IL-B Leptin MDC00.91 MMP MMP Resistin SAA TNF-RI BiomarkerAvg. % Difference “OTC” vs. “Fresh” ` VCAM VEGF YKL COMP11.00 ICAM ICTP IL-2RA IP MCSF OPG RANKL01.00 THBD TIMP Qureshi et al. Pre-Analytical Effects of Serum Collection and Handling in Quantitative Immunoassays for Rheumatoid Arthritis; ACR 2010; Poster #1606

Training: Vectra™ DA Algorithm Includes 12 biomarkers and uses a formula similar to DAS28CRP Different subsets and/or weightings of biomarkers are used to estimate SJC28, TJC28, and PG CRP IL-6 SAA YKL-40 EGF TNF-RI Leptin VEGF-A VCAM-1 MMP-1 MMP-3 Resistin TJC28 SJC28 Patient Global CRP Biomarkers Used To Predict Each DAS Component Bakker et al. Development of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA). ACR 2010; Poster #1753 DAS28CRP=0.56√TJC √SJC PG log(CRP+1) TJC=tender joint count; SJC=swollen joint count; PG =patient global health Vectra DA Score =(0.56√PTJC √PSJC PPG log(CRP+1) ) * PT JC=predicted TJC, PSJC=predicted SJC, PPG =predicted PG

Vectra™ DA Validation (RF+ and/or Anti-CCP+): Patient Cohort Characteristics ParameterBRASSLeidenInFoRMTotal n Gender, % female Median Age (IQR)58 (48-69)56 (45-65)59 (50-66)58 (48-66) RF-positive, % CCP-positive, % Median Tender Joint Count (IQR)15 (4-22)1 (0-6)6 (0-21)5 (0-18) Median Swollen Joint Count (IQR)12 (5-17)0 (0-4)4 (0-11)4 (0-12) Median CRP in mg/L (IQR)7 (3-15)7 (3-17)6 (2-21)7 (3-17) Mean Patient Global VAS (IQR)47 (25-70)34 (17-50)45 (16-70)42 (19-65) Median DAS28CRP (IQR)5.5 ( )2.7 ( )4.2 ( )4.1 ( ) Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782

Vectra™ DA Validation (RF+ and/or Anti-CCP+): Results Pearson Correlation = 0.56 The Vectra DA score was also associated with DAS28-CRP (p 25),not overweight, on anti-TNF medications, on methotrexate but not biologics and on steroids. Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782; Data on file Crescendo Bioscience

Vectra™ DA Validation (RF+ and/or Anti-CCP+): Ability to Detect Low Disease Activity The exploratory analysis shows that patients with low Vectra DA scores tended to have a higher likelihood of low joint counts than those with low CRP Although these results were not statistically significant, they do suggest that the Vectra DA score may more accurately detect low joint counts than CRP. Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782

Vectra™ DA Validation (RF+ and/or Anti-CCP+): Biomarkers Other Than CRP In a multivariate regression analysis of predictors of the DAS28CRP using the Vectra DA score (without CRP) and CRP as predictors, both the Vectra DA score (without CRP) and CRP were statistically significant (p<0.001) Since the DAS28CRP includes CRP itself, a multivariate regression analysis was carried out to evaluate both CRP and the Vectra DA Score (without CRP) as predictors of the DAS28CRP with CRP removed – The Vectra DA score (without CRP) was statistically significant (p<0.001), and the CRP term was not significant (p=0.22). Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782

Predictors of HAQ response after 3 months of treatment with different strategies in recent onset active RA are different than predictors of rapid radiological progression BeSt Treatment Strategies in Rheumatoid Arthritis

MTX monotherapy MTX monotherapy MTX + SSA + predMTX + IFX Sequential monotherapy n=126 Step-up combination n=121 Initial combination with prednisone n=133 Initial combination with infliximab n=128 BeSt trial Each strategy further treatment steps per 3 months if DAS >2.4

Predictors RRP PredictorsOdds ratio95% CI RF/ACPA both negative 1 positive both positive ref Erosions  4 ref CRP mg/L <  35 ref Therapy mono combi prednisone combi IFX ref

< Risk of RRP (%)  50 Matrix: RRP after 1 year of treatment

Predictors HAQ >=1 Baseline predictorsOR (95% CI) Initial treatment mono combo prednisone combo infliximab ref 0.3 ( ) 0.4 ( ) HAQ < > 2.0 ref 2.6 ( ) 5.3 ( ) VAS pain < 40 (tertiles) > 60 ref 2.2 ( ) 2.7 ( ) RAI < 10 (tertiles) > 16 ref 1.7 ( ) 2.7 ( )

> > < > <10 < > <10 < >60< >60 > > < > <10 < > <10 < >60 Matrix: predicted risk HAQ ≥ 1 after 3 months Monotherapy Combo with prednisoneCombo with infliximab VAS pain HAQ RAI High risk Intermediate risk Lower risk Low risk

Differences RRP and HAQ model Of all 508 patients in the BeSt, 12% had a HAQ ≥ 1 after three months of treatment as well as RRP after one year. Thus, it seems that short-term functional ability and radiological damage progression are different concepts. The choice of the best initial treatment is dependent on the relevance of the respective outcome measures for an individual patient.

Which target is relevant for which patient? Patient develops symptoms Patient visits GP GP refers patient to Rheumatologist Guidance of treatment possible by prediction based on serum-based activity measurments or measurements focussed at prevention of damage versus function Relevance of CCP-test DELAY has a price (less remission, more destruction, more suffering) Measure disease activity