Article Text

Download PDFPDF

SAT0252 Clinical and functional response to tofacitinib and adalimumab in patients with rheumatoid arthritis: probability plot analysis of results from the oral strategy trial
Free
  1. T. Takeuchi1,
  2. J. S. Smolen2,
  3. R. Fleischmann3,
  4. N. Iikuni4,
  5. H. Fan5,
  6. K. Soma6,
  7. E. Akylbekova7,
  8. T. Hirose8
  1. 1Keio University, Tokyo, Japan
  2. 2Medical University of Vienna and Heitzing Hospital, Vienna, Austria
  3. 3Metroplex Clinical Research Center and University of Texas Southwestern Medical Center, Dallas, TX
  4. 4Pfizer Inc, New York, NY
  5. 5Pfizer Inc, Collegeville, PA
  6. 6Pfizer Inc, Groton, CT
  7. 7IQVIA, Durham, NC, United States
  8. 8Pfizer Japan Inc, Tokyo, Japan

Abstract

Background: Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). ORAL Strategy (NCT02187055), a 12-month, global, Phase 3b/4 study, demonstrated that in patients with RA and an inadequate response to methotrexate (MTX), tofacitinib + MTX was non-inferior to adalimumab + MTX, while tofacitinib monotherapy was not non-inferior to either combination based on American College of Rheumatology (ACR)50 response rates at Month 6.1

Objectives: To assess clinical and functional efficacy across treatments in the ORAL Strategy trial using cumulative probability plots.

Methods: Efficacy was evaluated between patients who received tofacitinib 5 mg twice daily (BID) as monotherapy (N=384), tofacitinib 5 mg BID + MTX (N=376) and adalimumab 40 mg subcutaneously once every 2 weeks + MTX (N=386) based on ACR responses and changes from baseline in Health Assessment Questionnaire-Disability Index (ΔHAQ-DI) score at Month 12. Cumulative probability plots for ACR-n (where ACR is the % improvement from baseline in ACR components, and n represents the mimimum % achieved by each patient) and ΔHAQ-DI are presented. The area under the curve (AUC) was calculated for ACR-n up to Month 12 (in months), and an analysis of covariance model was used to assess treatment effects in terms of the AUC of ACR-n at Month 12; there was no adjustment for multiplicity for this post hoc analysis.

Results: The cumulative probability plots of ACR responses at Month 12 indicated that the proportion of patients who achieved responses of ACR20, ACR50 and ACR70 was similar for tofacitinib + MTX and adalimumab + MTX, but was numerically smaller for tofacitinib monotherapy (figure, A). Responses of approximately ≥ACR80 were achieved by a similar proportion of patients in each treatment group. Least squares mean (standard error) AUC of ACR-n up to Month 12 (in months) was similar for tofacitinib + MTX (437 [35]) and adalimumab + MTX (402 [35]), but was smaller for tofacitinib monotherapy (319 [35]; p<0.05). The cumulative probability plots of ΔHAQ-DI suggested that, in general, reductions from baseline in HAQ-DI were similar across treatment groups (figure, B), although a slightly higher proportion of patients who received tofacitinib monotherapy reported an increase in HAQ-DI vs other treatments.


Embedded Image

Figure 1 Cumulative probability plot of A) ACR response and B) VHAQ-DI at Month 12

Two outlets for ACR response are not shown: tofacitinib 5 mg BID monotherapy, ACR-n-1700, cumulative probability-0.0003; adailmumab 40 mg SC Q2W + MTX, ACR-n-463, cumulative probability-0.003

Conclusions: These data support the primary ORAL Strategy findings,1 indicating that in patients with RA, clinical efficacy, based on ACR response, was generally similar for tofacitinib + MTX and adalimumab + MTX, while a smaller proportion of patients who received tofacitinib monotherapy achieved ACR response in general, and particularly for <ACR80. Functional efficacy, based on ΔHAQ-DI, was generally similar across all treatment groups. Cumulative probability analyses for CDAI will be further evaluated.

Reference [1]Fleischmann R, et al. Lancet2017;390:457–68.

Acknowledgements: Study sponsored by Pfizer Inc. Medical writing support was provided by A MacLachlan of CMC and funded by Pfizer Inc.

Disclosure of Interest: T. Takeuchi Grant/research support from: AbbVie, Asahi Kasei, Astellas, AstraZeneca, AYUMI, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Eli Lilly Japan, Janssen, Mitsubishi Tanabe, Nippon Kayaku, Novartis, Pfizer Japan Inc, Taiho, Taisho Toyama, Takeda, Teijin, Consultant for: AbbVie, Asahi Kasei, Astellas, AstraZeneca, AYUMI, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Eli Lilly Japan, Janssen, Mitsubishi Tanabe, Nippon Kayaku, Novartis, Pfizer Japan Inc, Taiho, Taisho Toyama, Takeda, Teijin, Speakers bureau: AbbVie, Asahi Kasei, Astellas, AstraZeneca, AYUMI, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Eli Lilly Japan, Janssen, Mitsubishi Tanabe, Nippon Kayaku, Novartis, Pfizer Japan Inc, Taiho, Taisho Toyama, Takeda, Teijin, J. Smolen Grant/research support from: AbbVie, Eli Lilly, Janssen, MSD, Pfizer Inc, Roche, Consultant for: AbbVie, Amgen, AstraZeneca, Astro, Celgene, Celtrion, Eli Lilly, GSK, ILTOO, Janssen, MedImmune, MSD, Novartis-Sandoz, Pfizer Inc, Roche, Samsung, Sanofi, UCB, Speakers bureau: AbbVie, Amgen, AstraZeneca, Astro, Celgene, Celtrion, Eli Lilly, GSK, ILTOO, Janssen, MedImmune, MSD, Novartis-Sandoz, Pfizer Inc, Roche, Samsung, Sanofi, UCB, R. Fleischmann Consultant for: AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, Celltrion, Eli Lilly, Genentech, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, UCB, N. Iikuni Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, H. Fan Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, K. Soma Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, E. Akylbekova Consultant for: Pfizer Inc, Employee of: IQVIA, T. Hirose Shareholder of: Pfizer Japan Inc, Employee of: Pfizer Japan Inc

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.