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Antidrug antibodies to tumour necrosis factor specific neutralising agents in chronic inflammatory diseases: a real issue, a clinical perspective; comment on the article by Vincent et al
  1. Alfons A den Broeder1,
  2. Aatke van der Maas1,
  3. Bart J F van den Bemt2
  1. 1Department of Rheumatology, Sint Maartenskliniek, Nijmegen, The Netherlands
  2. 2Department of Pharmacy, Sint Maartenskliniek, Nijmegen, The Netherlands
  1. Correspondence to Dr Alfons A den Broeder, Department of Rheumatology, Sint Maartenskliniek, Hengstdal 3, Nijmegen 6522 JV, The Netherlands; a.denbroeder{at}

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Vincent et al present a thorough review of available clinical research on antidrug antibodies to tumour necrosis factor (TNF) blocking agents.1 We agree to a large extent with their interpretation of the data with regard to pathophysiology, 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 thus far insufficiently supported by evidence. In our comment we will focus on rheumatoid arthritis (RA), but for other inflammatory disease the same comments can be made.

First, 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 biological or a higher dose of the same biological, 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. Unnecessary flares and unneeded drug exposition (cost and adverse events) could thus be prevented. Second, 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 biological, either a TNF blocker or one with a different mechanism of action. Increasing the dose has a much lower chance of response in rheumatic diseases2 ,3 and is associated with more adverse events and costs4 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) an important clinical outcome is uncertain; (2) a reliable and valid test is available that is strongly associated with this outcome and gives additional information about this outcome above the 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 al5). The proposed algorithm of Vincent et al does not fulfil these criteria. First, increasing the dose in arm 1 is arguably not safe and (cost) effective. Also, arms 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—have 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 either patients with 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, C reactive protein) should be done to determine the additive value of TDM above regular clinical tight control. A clear change from pre-test to post-test 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 gold 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 were in RA, assessing (anti)drug levels for the five anti-TNF agents. These studies include basic laboratory studies, 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 pre-test and post-test chances, let alone cost effectiveness analyses. Of note, the cost effectiveness analysis of TDM in adalimumab  done in RA patients by Krieckaert et al6 is a Markov modelling 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, modelled 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 yet been published.7 These studies assessed respectively the predictive value of infliximab (anti)drug levels in RA patients to predict response after initiation, and predict successful dose reduction, and in ankylosing spondylitis patients to predict response after dose increase.

Interestingly, all three studies failed to demonstrate any relevant contribution of TDM to clinical decision making in the respective contexts. Other studies are currently underway to further explore this for other biologicals in other diseases (eg, DRESS study in RA, TAXIT study in inflammatory bowel disease).

In conclusion, TDM has no proven value yet in biological treatment, and should not be advocated at this time. The most promising context seems to be 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, for both test development and execution of appropriate clinical studies.


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  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.