Faculty Bibliography

Background With the availability of multiple biologic agents, with different modes of action, and no head to head trials, it is of use to examine comparative effectiveness of these agents in real world registries to inform physicians how they might be used for the treatment of rheumatoid arthritis. Objectives To compare time to response and efficacy among biologic agents. Methods Usage of the biologic medications abatacept, adalimumab, etanercept,infliximab and rituximab along with self-reported disease activity and clinic measures were abstracted from ARMD registry at NYU. Time to first response defined as an improvement in RAPID3 of at least 3.6 was calculated; change from biologic medication initiation to first response for self-reported disease activity and clinic measures was estimated. Differences in time to first response between biologic medications were estimated using Cox proportional hazards model. Results 4299 encounteres were reviewed for this analysis. A total of 526 treatment courses were determined. 406 of 526 courses represent the first biologic medication used by an individual; 88 individuals used two biologic medications at different times, while 26 had used three biologics, and 6 had used 4. Abatacept had more patients achieve response (66%) characterized by a reduction in RAPID of 3.6 points or greater than adalimumab (63%), etanercept (61%), infliximab (43%), rituximab (41%) although this difference was not statistically siginficant. Increased age and increased duration of disease were associated with decreased likelihood of achieving a RAPID3 reponse. Time to reponse in the first 6 months after treatment was not significantly different among any of the biologics Conclusions No differences in efficacy and time to response among adalimumab, abatacept, etanercept, infliximab or rituximab in the first 6 months after RA treatment was initiated were noted. With no difference in clinical outcomes, most treatment decisions may be based on ease of use and safety data of respective!

Background Behcet's syndrome (BS) is a systemic vasculitis that may different pathogenic mechanisms leading to different manifestations, such as eye, mucocutaneous and GI disease. We started a dedicated Behcet's clinic in 2004 and have treated over 850 patients to date. Objectives To determine the response to therapy depending on type of organ involvement and documentation of improvement with patient reported outcomes. Methods All patients seen at the Center complete MDHAQ, medical history, medication use, Behcet's specific history, ethnic and demographic information forms. In addition a Behcet Syndrome Activity Score (BSAS) is also completed by all Behcet patients. These data are prospectively collected and updated each visit. Patients were divided into eye disease only, GI only, both or none groups and compared for disease activity and medication, specifically azathioprine, use. They could have mucocutaneous disease in addition to above manifestations Results 484 patients (78% female, disease duration 4.8 (7.1) years, age 35.3 (13.8)) were analyzed. 244 patients had no eye or GI disease, 83 had eye, 111 GI and 46 both eye and GI involvement. Both groups of azathioprine treated and untreated patients showed improvement in their disease activity scores but the improvement were more pronounced for GI disease by BSAS. RAPID3 responses were more in the azathioprine treated group with eye and both eye and GI disease. Patients with no eye or GI disease did similarly with or without azathioprine. (Table presented) Conclusions In this cohort of 484 Behcet patients, some treatment response differences were noted between patients with eye or GI involvement vs those who did not have these. Overall, azathioprine, led to better outcomes regardless of organ involvement. It was possible to demonstrate these improvements using patient reported outcomes, RAPID3 and BSAS, as part of routine clinical care

Background A patient self-report joint count, rheumatoid arthritis disease activity index (RADAI),1 is correlated significantly with tender and swollen joint counts performed by a health professional in rheumatoid arthritis (RA) patients2. The RADAI is included on the multidimensional health assessment questionnaire (MDHAQ), which is completed in many rheumatology settings by all patients with all diagnoses, as the same questionnaire is (logistically) most feasible. Objectives To analyze RADAI painful joint count scores in patients with diagnoses other than RA in usual care setting. Methods Each patient seen at an academic rheumatology site completes an MDHAQ at each visit, while waiting to see the doctor in the infrastructure of clinical care. The RADAI on the MDHAQ includes 8 bilateral specific joint groups: fingers, wrist, elbow, shoulder, hip, knee, ankle and toes, each scored from 0 ("no pain") to 3 ("severe pain") (total 0-48). A random visit of 465 patients was analyzed including 75 with SLE, 50 with gout, 53 with PsA, 113 with OA, as well as 174 with RA. Mean RADAI and % of patients scoring each specific joint group as affected were computed for each diagnosis, and compared to the MDHAQ patient global estimate (PATGL) and physician global estimate (DOCGL) using Spearman correlations. Results Patients were primarily women (68%), age 51+16 years;SLE patients were youngest (39.5+13.8) and OA patients oldest (62.8+12.5). An abnormal RADAI score >0 was reported by 99% of patients with OA, 87% of patients with RA, 83% with PsA, 60% with gout, and 59% with SLE. The joints reported as most affected were knees (58%) and fingers (52%) in all patients; in RA, fingers (52%), wrists (58%), and knees (58%); in SLE, fingers (37%) and shoulders (32%); in gout, toes (24%) and knees (22%); in PsA, knees (43%) and fingers (40%), and in OA, knees (68%) and fingers (42%) (Table). RADAI scores were correlated significantly with PATGL (rho =0.50-0.75, p<0.001), and moderately, though significantly, with DOCGL!

Background CDAI (clinical disease activity index) and RAPID3 (routine assessment of patient index data 3) cut points defining responses that best match ACR20/50/70 response in rheumatoid arthritis (RA) patients (pts), are unknown. Objectives To evaluate cut points in a study population treated with certolizumab pegol (CZP) plus methotrexate (MTX).1 Methods ACR responders through Week (Wk) 12 from 393 CZP treated pts (400 mg at Wks 0, 2 and 4 then 200 mg every 2 Wks) plus MTX in RAPID 1 (NCT00152386) were categorized by proposed response (R) cut points in CDAI (change from baseline [CFB] >6.7, >10.0, >13.9) and RAPID3 (CFB >1.8, >3.6). ACR20/50/70 responses were compared with proposed categorizations using cross-tabulations, AUC under the ROC curve (AUC-ROC), % correctly classified (%CC) pts and kappa statistics. CART2 (classification and regression trees) modeling identified CDAI and RAPID3 cut points defining responses most closely associated with ACR20/50/70 responses. Results Sensitivities were very high; at Wk 12, 93-100% ACR20/50/70 responders achieved CFB in CDAI (>6.7,>10.0,>13.9). Positive predictive value [PPV] was lower indicating CDAI-R is not as strongly associated with ACR-R as ACR-R is with CDAI-R; lower specificities indicate that ACR nonresponse (NR) does not correspond well to CDAI-NR (particularly for ACR50/70). However, CDAI-NR predicts well ACR-NR (very high negative predictive value [NPV]) (Table). CFB in CDAI>13.9 was most closely associated with ACR20-R (=0.57). Association between proposed CDAI categorizations and ACR50/70 was weak (=0.05-0.29). A similar trend was observed for RAPID3. CART modeling identified CFB in CDAI >13.80/>20.15/>20.15 and CFB in RAPID3 >5.46/>7.28/>5.53 as categorizations most closely associated with ACR20/50/70 responses. Conclusions CDAI and RAPID3 CFB thresholds were identified that defined the closest associations with ACR responses in pts with inadequate response to MTX and high disease activity at baseline (mean DAS28 6.9). Sensitivities/NP!

Background Randomized controlled trials (RCT) are designed to answer specific questions using a certain number of patients, determined by sample size calculation. If the calculation is not done properly, more than the needed number of patients may be enrolled, leading to unnecessary exposure for those patients to potentially harmful drugs. In an ideal world, assumptions that go into the calculation of the sample size would be more certain. However in the real world it is not always possible to have ideal calculations and it would be expected that under and over enrolling would be seen in roguishly similar number of RCTs. Objectives To determine the actual numbers of patients needed to be enrolled in RA biologic RCT. Methods A Pubmed search was conducted, for RCT of abatacept, adalimumab, etanercept, infliximab, rituximab and tocilizumab, in rheumatoid arthritis (RA) patients (n=291). Only original initial studies where the primary outcome was efficacy were analyzed (n=42). Using the final results of the primary outcome, back calculation of the actually needed patients for the trials were calculated and compared to the actual enrollment numbers. Results 42 studies were analyzed (infliximab 10, etanercept 7, adalimumab 8, abatacept 7, tocilizumab 5, rituximab 5). Primer efficacy outcome was ACR 20 in 29 studies. ACR 50 in 3 studies, ACR N in 2 studies, DAS-28 in 5 studies, Paulus 20 in 2 studies and reduction of number of swollen/tender joints in 1 study. The mean number of patients enrolled in the treatment arms were 153 and the control arms were 114. After back calculation, the actual needed numbers for the treatment arm was 79 and control arm was 79. According to the recalculated sample size results, there were more patient than required to show differences between groups in 35 studies (83%) and less patients than required in 7 studies. In the 35 studies were more than necessary patients were enrolled had a median of 103 extra patients. Conclusions Over 80% of RCT of biologic agents in the tre!