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Abstract Number: 1410

Cycling of Tumor Necrosis Factor-α (TNF-α) Inhibitors versus Switching to Different Μechanism of Αction in Rheumatoid Arthritis Patients with Inadequate Response to TNF-α Inhibitor: A Bayesian Network Meta-analysis

Alberto Migliore1, Giuseppe Pompilio 2, Davide Integlia 2, Joe Zhuo 3 and Evo Alemao 4, 1Unit of Rheumatology Ospedale S. Pietro Fatebenefratelli, Rome, Italy, 2Isheo Srl, Rome, Italy, 3Bristol-Myers Squibb, Princeton, NJ, 4Bristol-Myers Squibb, Princeton

Meeting: 2019 ACR/ARP Annual Meeting

Keywords: ACR and Health Assessment Questionnaire, anti-TNF therapy, monoclonal antibodies, Rheumatoid arthritis (RA)

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Session Information

Date: Monday, November 11, 2019

Session Title: RA – Treatments Poster II: Established Treatments

Session Type: Poster Session (Monday)

Session Time: 9:00AM-11:00AM

Background/Purpose: TNF inhibitors are a common treatment for rheumatoid arthritis (RA), but there is no best practice for when a specific TNF inhibitor stops working1. The main options are to ‘cycle’ patients onto a different TNF inhibitor, or to ‘switch’ patients onto a drug with a different mechanism of action. Building on a previous developed systematic review of existing RCTs and observational studies, this network meta-analysis (NMA) assess the clinical comparative efficacy of ‘cycling’ versus ‘switching’.

Methods: We conducted a literature search in MEDLINE, Embase and Cochrane Library  in June 2018. RCTs and observational studies investigating second-line treatments for rheumatoid arthritis, respectively for TNF inhibitor (adalimumab, infliximab, etanercept, certolizumab, golimumab) and drugs with different mechanism of action (Moa) were considered.
The outcomes included the mean reduction in HAQ score; proportion of patients with a clinically meaningful HAQ reduction (defined as a reduction of at least 0.22); proportion of patients with a 20% (ACR20), 50% (ACR50) or 70% (ACR70) response on the ACR score; proportion of patients achieving a DAS28 score below 2.6 (classified as remission) or between 2.6 and 3.2 (classified as low disease activity); mean change in DAS28 score; rate of serious adverse events (SAEs); and number of withdrawals for any reason or due to adverse events or lack of treatment efficacy.
Risk of bias was assessed both RCTs and observational studies through Cochrane Risk of Bias Tool and Newcastle-Ottawa Scale respectively. We classed interventions as ‘cycle’, ‘switch’ or placebo and performed three models of NMA: a fixed effect model, a random-effect model and hierarchical Bayesian network meta-analysis2,3 for each outcome with appropriate data.

Results: We identified 9 RCTs (4 for ‘cycling’ and 5 for ’switching’) and 16 observational studies (8 for ‘cycling’ and 8 for ‘switching’) meeting our inclusion criteria, with patient numbers ranging from small studies of 15 patients up to 1683 patients. The proportion of females in the studies were at least 71.1% and the mean age of participants ranged from 45.1 to 59.0 years. 
The fixed effects NMA suggested a 0.99 probability that ‘switch’ was the better strategy for increasinng the odds of a clinically meaningful improvement in ACR20 (OR: 1.38 [95% CI: 1.06-1.78]). ‘Switch’ was also associated with fewer rates of withdrawals due of lack of efficacy (OR: 0.35 [95% CI: 0.19-0.62]) and withdrawals for any reasons. 
Random effects and hierarchical Bayesian models reflected additional uncertainty but gave similar results. (Figure 1)

Conclusion: Results suggest that “switching” to a drug with a different mechanism of action is more effective and with lower rates of withdrawals than “cycling” to a different TNF inhibitor after first-line TNF inhibitor failure. Further trials to directly compare ‘cycling’ with ‘switching’ is warranted to better assess the comparative efficacy.

References

1.   Favalli EG, et al. Autoimmunity Reviews 2017;16(12):1185-95
2.   Prevost T, et al (2000). Stat Med 2000;19:3359-76
3.   Ioannidis JP, et al. JAMA 2001;286(7):821-30

DIC: Deviance Information Criterion; OR: Odds Ratio; PBO: Placebo; LB: Lower Bound; UP: Upper Bound; Fixed: Fixed Effect Estimate; Random: Random Effect Estimate; Hierarchical: Hierarchical Estimate.


Disclosure: A. Migliore, Pfizer, 2, UCBPharma, 2, Merck, 2, Roche, 2, Brystol-Myers Squibb, 2, IBSA, 2, Sanofi-Aventis, 2, Fidia Pharma, 2; G. Pompilio, None; D. Integlia, Abbvie, 5, Merck Serono, 5, Bristol-Myers Squibb, 5, Eli Lilly, 5, Boehringer Ingelheim, 5, Angelini, 5, Fidia Pharma, 5; J. Zhuo, Bristol-Myers Squibb, 1, 3; E. Alemao, Bristol Myers Squibb, 1, 3, 4.

To cite this abstract in AMA style:

Migliore A, Pompilio G, Integlia D, Zhuo J, Alemao E. Cycling of Tumor Necrosis Factor-α (TNF-α) Inhibitors versus Switching to Different Μechanism of Αction in Rheumatoid Arthritis Patients with Inadequate Response to TNF-α Inhibitor: A Bayesian Network Meta-analysis [abstract]. Arthritis Rheumatol. 2019; 71 (suppl 10). https://acrabstracts.org/abstract/cycling-of-tumor-necrosis-factor-%ce%b1-tnf-%ce%b1-inhibitors-versus-switching-to-different-%ce%bcechanism-of-%ce%b1ction-in-rheumatoid-arthritis-patients-with-inadequate-response-to-tnf-%ce%b1-inhi/. Accessed January 31, 2023.
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