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• Antidrug antibodies (ADAb) to tumour necrosis factor (TNF)-specific neutralizing agents in chronic inflammatory diseases: a real issue, a clinical perspective. Comment on the article of Vincent et al.
  Alfons A den Broeder
  Published on: 13 April 2016

• Published on: 13 April 2016

  Antidrug antibodies (ADAb) to tumour necrosis factor (TNF)-specific neutralizing agents in chronic inflammatory diseases: a real issue, a clinical perspective. Comment on the article of Vincent et al.

  • Alfons A den Broeder, rheumatologist-epidemiologist
  • Other Contributors:
    • Aatke van der Maas, Bart JF van den Bemt

  Dear Editor,

  Vincent et al present a thorough review of available clinical research on antidrug antibodies to tumour necrosis factor blocking agents (1). We agree to a large extent with their interpretation of the data with regard to pathofysiology, assay characteristics and variation in drug and antidrug antibody serum levels. However, the conclusion that measurement of (anti)drug levels should therefore be used f...

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  Dear Editor,

  Vincent et al present a thorough review of available clinical research on antidrug antibodies to tumour necrosis factor blocking agents (1). We agree to a large extent with their interpretation of the data with regard to pathofysiology, assay characteristics and variation in drug and antidrug antibody serum levels. However, the conclusion that measurement of (anti)drug levels should therefore be used for clinical decision making in non-responding biological patients with inflammatory diseases to save costs, prevent adverse events and improve disease activity, including their proposed algorithm, seems flawed and is thusfar insufficiently supported by evidence. In our comment we will focus on RA, but for other inflammatory disease the same comments can be made.

  Firstly, we would argue that the most promising application for therapeutic drug monitoring (TDM) to save costs or adverse events is not to predict response to the next treatment option in non responding patients, but rather to predict successful dose reduction and stopping in patients who are doing well. All treatment alternatives in non responding patients employ either another biologic or a higher dose of the same biologic, so even optimal channelling of patients can only lead to better disease control, not to saved costs or prevented adverse events. In patients doing well however, it could be possible to use TDM to optimise dose reduction or stopping compared to a trial and error strategy. This way, unnecessary flares and unneeded drug exposition (cost and adverse events) could be prevented.

  Secondly, when TDM is done in non responding patients and a low serum drug level is found it is not sensible, at least in RA, to increase the dose as suggested. The better choice would be to change to another biologic, either TNF blocker or with another mechanism of action. Increasing the dose has a much lower chance of response in rheumatic diseases (2,3) and is associated with more adverse events and costs (4) than switching to another biological, and is therefore probably not cost effective. In addition to these arguments, there is also a lack of specific empirical data to support the proposed decision tree. The theoretical framework for TDM indicates that any test that is used for TDM in clinical practice should meet the following requirements: 1/ uncertainty exist on an important clinical outcome, 2/ a reliable and valid test is available that is strongly associated with this outcome and gives additional information about this outcome above simple test, 3/ the use of the test has treatment consequences and 4/ the use of the test is cost effective (adapted from Aarnoutse et al, 5). The proposed algorithm of Vincent et al does not fulfill these criteria. Firstly, increasing the dose in arm 1 is arguably not safe and (cost)effective. Also, arm 2 and 3 converge to the same treatment option, negating the possible value of testing. For arm 4, switching to another class of biological, a clearly higher post test chance of response has not been consistently demonstrated.

  Finally and most importantly, the possible advantages of TDM in this context - better disease control - has never been demonstrated compared to usual tight control care.
  The appropriate clinical study design to assess the value of TDM is a prediction cohort study in patients with either active disease and starting or switching a biological, or patients with low disease and withdrawing medication. After the clinical outcome has been measured prospectively, the sensitivity and specificity of baseline (anti)drug levels for (non)response measured using a validated test should be estimated using ROC analyses. Thereafter, prediction modelling including all other known predictors (eg clinical, CRP) should be done to determine the additive value of TDM above regular clinical tight control. A clear change from pretest to posttest chances should be demonstrated, expressed preferably in numbers needed to diagnose, and cost effectiveness measures should be provided. Finally, confirmation of the cost effectiveness in a so called diagnostic study - a randomised trial comparing test based treatment with usual care - would be considered to be the golden standard in proving the value of any diagnostic or prognostic test, including TDM. The current review describes 76 studies done in the last 13 years of which 36 in RA assessing (anti)drug levels for the five anti-TNF agents. These studies include basic labstudies, cross-sectional studies and longitudinal non interventional studies. Unfortunately, however, due to the specific design limitations, not one of these studies was able to provide test characteristics for an important clinical outcome, including sensitivity and specificity, and pretest and posttest chances, let alone cost effectiveness analyses. Of note, the cost effectiveness analysis of TDM in adalimumab done in RA patients by Krieckaert et al (6) is a Markov modeling study showing that TDM using adalimumab (anti)drug levels could be cost-effective, based on the presumption that (anti)adalimumab serum levels are predictive for successful dose reduction, and this has indeed yet to be established. Also, modeled TDM guided dose reduction was compared to no change in adalimumab treatment instead of the more valid comparison with clinically guided doses reduction.

  We are currently aware of three studies in rheumatic diseases specifically designed to assess the value of TDM, two of which have not been published yet (7-9). These studies assessed respectively the predictive value of infliximab (anti) drug levels in RA patients to predict response after initiation, prediction of successful dose reduction, and in ankylosing spondylitis patients prediction of response after dose increase. Interestingly, all three studies failed to demonstrate any relevant contribution of TDM for clinical decision making in the respective contexts. Other studies are currently underway to further explore this for other biologicals in other diseases (e.g. DRESS study in RA, TAXIT study in IBD).
  In conclusion, TDM has no proven value yet in biological treatment, and should not be advocated at this moment. The most promising context seems TDM guided dose reduction in patients doing well. We strongly support research in this field, as it might enable us to treat our patients better, resulting in optimal disease control, better safety, and lower costs. However, a proposed TDM algorithm should be logically sound and empirically tested with scrutiny. We can therefore wholeheartedly join Vincent et al in their plea for significant research investment in this topic, both for test development as well as execution of appropriate clinical studies.

  References

  1. Vincent FB, Morand EF, Murphy K, et al. Antidrug antibodies (ADAb) to tumour necrosis factor (TNF)-specific neutralizing agents in chronic inflammatory diseases: a real issue, a clinical perspective. Ann Rheum Dis 2013;72:165-78.

  2. Pavelka K, Jarosov K, Such D, et al. Increasing the infliximab dose in rheumatoid arthritis patients: a randomised, double blind study failed to confirm its efficacy. Ann Rheum Dis 2009;68:1285-9.

  3. van den Bemt BJF, den Broeder AA, Snijders GF, et al. Sustained effect after lowering high dose infliximab in patients with rheumatoid arthritis: a prospective dose titration study. Ann Rheum Dis 2008;67:1697-701.

  4. Bongartz T, Sutton AJ, Sweeting MJ, et al. Anti-TNF antibody therapy in rheumatoid arthritis and the risk of serious infections and malignancies: systematic review and meta-analysis of rare harmful effects in randomized controlled trials. JAMA 2006;295:2275-85

  5. Aarnoutse RE, Schapiro JM, Boucher CA, et al. Therapeutic drug monitoring: an aid to optimising response to antiretroviral drugs? Drugs 2003;63:741-53.

  6. Krieckaert C, Nair SC, Nurmohamed MT, et al. Evaluating the cost-effectiveness of personalized treatment with adalimumab using serum drug level and anti-adalimumab antibodies in rheumatoid arthritis patients. Ann Rheum Dis 2012;71(suppl 3):104.

  7. Inman RD, Davis JC Jr, Heijde D vd, et al. Efficacy and safety of golimumab in patients with ankylosing spondylitis: results of a randomized, double-blind, placebo-controlled, phase III trial. Arthritis Rheum 2008;58:3402-12.

  8. van der Maas A, van den Bemt BJF, van den Hoogen FHJ, et al. Baseline (anti-) infliximab serum trough levels do not predict successful down-titration or cessation of infliximab in Rheumatoid Arthritis patients with long term low disease activity. Submitted 2013.

  9. van den Bemt BJF, den Broeder AA, Wolbink GJ, et al. The combination of disease activity and infliximab serum trough levels for early prediction of (non-) response to infliximab-treatment in patients with rheumatoid arthritis. Submitted 2013.

  Conflict of Interest:

  None declared

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  Conflict of Interest:
  None declared.

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