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Registry evidence – the Italian experience

Registry evidence – the Italian experience. Professor Gianfranco Ferraccioli Professor of Rheumatology Director Division of Rheumatology School of Medicine Catholic University of the Sacred Heart Rome, Italy. Evidence for prognostic factors for clinical remission.

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Registry evidence – the Italian experience

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  1. Registry evidence – the Italian experience Professor Gianfranco Ferraccioli Professor of RheumatologyDirector Division of RheumatologySchool of MedicineCatholic University of the Sacred HeartRome, Italy

  2. Evidence 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

  3. Treatment of RA aims at REMISSION Baseline patient characteristics What are the clinical predictors of response to therapy and remission?

  4. Remission 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 2008;58:2642-51

  5. Prognostic factors of clinical remission on DMARDs: The Quest-RA study Sokka T et al. Arthritis Rheum 2008;58:2642-51

  6. Treatment of RA aims at REMISSION Baseline patient characteristics Biomarkers What are the clinical predictors of response to rescue therapy for DMARDs failure, and remission?

  7. Prognostic factors for clinical remission with TNF inhibitors: The GISEA study Mancarella L et al. J Rheumatol 2007;34:1670-73 GISEA,Gruppo Italiano per lo Studio delle Early Arthritis

  8. Characteristics of 591 patients with RA at baseline Mancarella L et al. J Rheumatol 2007;34:1670-73

  9. Characteristics of patients at baseline according to RF status * C-reactive protein positivity: *CRP>5 mg/L Mancarella L et al. J Rheumatol 2007;34:1670-73

  10. Prognostic factors for clinical remission with TNF inhibitors Hosmer-Lemeshow test: p=0.935. Hosmer-Lemeshow test: p=0.554. Mancarella L et al. J Rheumatol 2007;34:1670-73

  11. Significantly better EULAR responses on follow-up in RF-negative patients Mancarella L et al: J Rheumatol 2007;34:1670-73

  12. Is there a correlation between RF isotype and clinical response to TNF inhibitors? Bobbio-Pallavicini F et al. Ann Rheum Dis 2007;66:302-7

  13. Investigation of a correlation between RF isotype and clinical response to TNF inhibitors 132 patients Advanced RA, DMARD-IR Treated with: infliximab (n=63) etanercept (n=35) adalimumab (n=34) 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 2007;66:302-7

  14. Trend for higher levels of RF and anti-CCP titres in non-responders to TNF inhibitors *The negative RF samples were included and counted with the measured values. Bobbio-Pallavicini F et al. Ann Rheum Dis 2007;66:302-7

  15. High IgA RF levels are associated with poor clinical response to TNF inhibitors 100 p=0.017 p<0.001 p=0.190 80 60 40 20 0 IgA-RF negative(45 pts) IgA-RF low(38 pts) IgA-RF high (43 pts) Percentage of responders Bobbio-Pallavicini F et al. Ann Rheum Dis 2007;66:302-7

  16. Take 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; 34:1670–1673; Bobbio-Pallavicini et al. Ann Rheum Dis 2007;66:302-307; Potter C, et al: Ann Rheum Dis. 2009 Jan;68(1):69-74. Epub 2008 Mar 28.

  17. What 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

  18. Conclusions 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

  19. Acknowledgements Bari Ferrara Modena Padova Perugia Ancona Roma Brescia Milano 1 Milano 2 Verona Pavia L’Aquila Palermo Genova Siena

  20. What does this mean for Ed’s patient? Seropositivity suggests a lower probability of a response to a TNF inhibitor

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