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Biologic agents that block the action of tumor necrosis factor have dramatically improved outcomes in rheumatoid arthritis. But they sometimes have little effect or lose effectiveness over time, necessitating a change in therapy. Emerging evidence, recently incorporated into a treatment algorithm, is helping to guide selection of the next biologic for such patients in a rational, personalized way (Rheumatology 2012;51:600-9).
Primary vs. Secondary Nonresponse
The first key consideration in selecting the next therapy is whether the patient has primary or secondary nonresponse to the anti-TNF agent, as this influences the odds of response to another agent in this class. The distinction is not clear-cut, but generally, primary nonresponse manifests 12-16 weeks after starting the agent, whereas secondary nonresponse emerges after 6-12 months.
Rheumatoid arthritis is increasingly recognized to be a highly cellularly and molecularly diverse collection of entities having essentially the same clinical picture, as is evident from varied treatment responses. In the context of anti-TNF therapy, compared with their counterparts having a response, primary nonresponders appear to have disease that is less dependent on TNF and to have a lower proinflammatory gene profile in the synovium.
In contrast, the reason for secondary nonresponse is usually unrelated to the disease process, and instead often is due to the development of antibodies against the TNF blocker – either human antichimeric antibodies (HACAs), as in the case of infliximab (Remicade), or human antihuman antibodies (HAHAs), as in the case of adalimumab (Humira).
Thus, primary nonresponders to TNF blockers are less likely to respond to other agents in this class, whereas secondary nonresponders seem to respond almost as well as patients who have never been given one of these agents before (EULAR 2008, abstract FRI0125).
Presence vs. Absence of Autoantibodies
The second key consideration after failure of a TNF blocker is whether the patient has autoantibodies, specifically, rheumatoid factor and/or anti–citrullinated protein antibodies (ACPAs), as their presence influences the odds of response to the B cell–depleting agent rituximab (Rituxan).
Autoantibody-positive patients have a better response than their autoantibody-negative counterparts to rituximab (EULAR 2009, abstract FRI0256). Occasionally, patients who appear to be autoantibody negative still benefit, likely because they have autoantibodies that we cannot yet detect.
Taken together, current data suggest that among primary anti-TNF nonresponders, patients who are autoantibody positive are most likely to benefit from three agents having other mechanisms of action: rituximab; abatacept (Orencia), a T-cell costimulation modulator; and tocilizumab (Actemra), an antibody to the interleukin-6 receptor. Those who are antibody negative are more likely to benefit only from abatacept or tocilizumab.
Among secondary nonresponders, patients who are autoantibody positive appear to have the most options – another anti-TNF agent, rituximab, abatacept, and tocilizumab – whereas those who are autoantibody negative are likely to benefit from any of these agents except rituximab.
Future Directions
We may be able to refine this personalized approach in the future. For example, the type 1 interferon signature may protect against rituximab-induced B cell depletion, as a higher signature in peripheral blood is associated with a lack of clinical response to this agent (Arthritis Rheum. 2010;62:3607-14). There may well be other predictive markers too, so we may one day be able to apply a multimarker panel in the clinic.
Also, additional treatment factors being identified may help guide the selection among multiple agents. For instance, a patient’s ability to take methotrexate, often given in combination with biologics, may play a role, as evidence suggests that tocilizumab given as monotherapy is just as effective as combinations of TNF blockers with methotrexate.
Identification of predictive biomarkers, while challenging and expensive, will help to optimize treatment of rheumatoid arthritis. There is a very clear need to come up with a much more sophisticated approach as opposed to the current one based on clinical measures. There has been progress in this area, but we need to continue to invest in biomarker research because this is really a more rational approach and the way forward.
Dr. Tak is professor of medicine at the AMC/University of Amsterdam and Senior Vice President/Head, Therapy Area Immunoinflammation at GlaxoSmithKline. He disclosed that he has been a consultant to Abbott, Amgen, Merck, Pfizer, and Roche/Genentech.
Biologic agents that block the action of tumor necrosis factor have dramatically improved outcomes in rheumatoid arthritis. But they sometimes have little effect or lose effectiveness over time, necessitating a change in therapy. Emerging evidence, recently incorporated into a treatment algorithm, is helping to guide selection of the next biologic for such patients in a rational, personalized way (Rheumatology 2012;51:600-9).
Primary vs. Secondary Nonresponse
The first key consideration in selecting the next therapy is whether the patient has primary or secondary nonresponse to the anti-TNF agent, as this influences the odds of response to another agent in this class. The distinction is not clear-cut, but generally, primary nonresponse manifests 12-16 weeks after starting the agent, whereas secondary nonresponse emerges after 6-12 months.
Rheumatoid arthritis is increasingly recognized to be a highly cellularly and molecularly diverse collection of entities having essentially the same clinical picture, as is evident from varied treatment responses. In the context of anti-TNF therapy, compared with their counterparts having a response, primary nonresponders appear to have disease that is less dependent on TNF and to have a lower proinflammatory gene profile in the synovium.
In contrast, the reason for secondary nonresponse is usually unrelated to the disease process, and instead often is due to the development of antibodies against the TNF blocker – either human antichimeric antibodies (HACAs), as in the case of infliximab (Remicade), or human antihuman antibodies (HAHAs), as in the case of adalimumab (Humira).
Thus, primary nonresponders to TNF blockers are less likely to respond to other agents in this class, whereas secondary nonresponders seem to respond almost as well as patients who have never been given one of these agents before (EULAR 2008, abstract FRI0125).
Presence vs. Absence of Autoantibodies
The second key consideration after failure of a TNF blocker is whether the patient has autoantibodies, specifically, rheumatoid factor and/or anti–citrullinated protein antibodies (ACPAs), as their presence influences the odds of response to the B cell–depleting agent rituximab (Rituxan).
Autoantibody-positive patients have a better response than their autoantibody-negative counterparts to rituximab (EULAR 2009, abstract FRI0256). Occasionally, patients who appear to be autoantibody negative still benefit, likely because they have autoantibodies that we cannot yet detect.
Taken together, current data suggest that among primary anti-TNF nonresponders, patients who are autoantibody positive are most likely to benefit from three agents having other mechanisms of action: rituximab; abatacept (Orencia), a T-cell costimulation modulator; and tocilizumab (Actemra), an antibody to the interleukin-6 receptor. Those who are antibody negative are more likely to benefit only from abatacept or tocilizumab.
Among secondary nonresponders, patients who are autoantibody positive appear to have the most options – another anti-TNF agent, rituximab, abatacept, and tocilizumab – whereas those who are autoantibody negative are likely to benefit from any of these agents except rituximab.
Future Directions
We may be able to refine this personalized approach in the future. For example, the type 1 interferon signature may protect against rituximab-induced B cell depletion, as a higher signature in peripheral blood is associated with a lack of clinical response to this agent (Arthritis Rheum. 2010;62:3607-14). There may well be other predictive markers too, so we may one day be able to apply a multimarker panel in the clinic.
Also, additional treatment factors being identified may help guide the selection among multiple agents. For instance, a patient’s ability to take methotrexate, often given in combination with biologics, may play a role, as evidence suggests that tocilizumab given as monotherapy is just as effective as combinations of TNF blockers with methotrexate.
Identification of predictive biomarkers, while challenging and expensive, will help to optimize treatment of rheumatoid arthritis. There is a very clear need to come up with a much more sophisticated approach as opposed to the current one based on clinical measures. There has been progress in this area, but we need to continue to invest in biomarker research because this is really a more rational approach and the way forward.
Dr. Tak is professor of medicine at the AMC/University of Amsterdam and Senior Vice President/Head, Therapy Area Immunoinflammation at GlaxoSmithKline. He disclosed that he has been a consultant to Abbott, Amgen, Merck, Pfizer, and Roche/Genentech.
Biologic agents that block the action of tumor necrosis factor have dramatically improved outcomes in rheumatoid arthritis. But they sometimes have little effect or lose effectiveness over time, necessitating a change in therapy. Emerging evidence, recently incorporated into a treatment algorithm, is helping to guide selection of the next biologic for such patients in a rational, personalized way (Rheumatology 2012;51:600-9).
Primary vs. Secondary Nonresponse
The first key consideration in selecting the next therapy is whether the patient has primary or secondary nonresponse to the anti-TNF agent, as this influences the odds of response to another agent in this class. The distinction is not clear-cut, but generally, primary nonresponse manifests 12-16 weeks after starting the agent, whereas secondary nonresponse emerges after 6-12 months.
Rheumatoid arthritis is increasingly recognized to be a highly cellularly and molecularly diverse collection of entities having essentially the same clinical picture, as is evident from varied treatment responses. In the context of anti-TNF therapy, compared with their counterparts having a response, primary nonresponders appear to have disease that is less dependent on TNF and to have a lower proinflammatory gene profile in the synovium.
In contrast, the reason for secondary nonresponse is usually unrelated to the disease process, and instead often is due to the development of antibodies against the TNF blocker – either human antichimeric antibodies (HACAs), as in the case of infliximab (Remicade), or human antihuman antibodies (HAHAs), as in the case of adalimumab (Humira).
Thus, primary nonresponders to TNF blockers are less likely to respond to other agents in this class, whereas secondary nonresponders seem to respond almost as well as patients who have never been given one of these agents before (EULAR 2008, abstract FRI0125).
Presence vs. Absence of Autoantibodies
The second key consideration after failure of a TNF blocker is whether the patient has autoantibodies, specifically, rheumatoid factor and/or anti–citrullinated protein antibodies (ACPAs), as their presence influences the odds of response to the B cell–depleting agent rituximab (Rituxan).
Autoantibody-positive patients have a better response than their autoantibody-negative counterparts to rituximab (EULAR 2009, abstract FRI0256). Occasionally, patients who appear to be autoantibody negative still benefit, likely because they have autoantibodies that we cannot yet detect.
Taken together, current data suggest that among primary anti-TNF nonresponders, patients who are autoantibody positive are most likely to benefit from three agents having other mechanisms of action: rituximab; abatacept (Orencia), a T-cell costimulation modulator; and tocilizumab (Actemra), an antibody to the interleukin-6 receptor. Those who are antibody negative are more likely to benefit only from abatacept or tocilizumab.
Among secondary nonresponders, patients who are autoantibody positive appear to have the most options – another anti-TNF agent, rituximab, abatacept, and tocilizumab – whereas those who are autoantibody negative are likely to benefit from any of these agents except rituximab.
Future Directions
We may be able to refine this personalized approach in the future. For example, the type 1 interferon signature may protect against rituximab-induced B cell depletion, as a higher signature in peripheral blood is associated with a lack of clinical response to this agent (Arthritis Rheum. 2010;62:3607-14). There may well be other predictive markers too, so we may one day be able to apply a multimarker panel in the clinic.
Also, additional treatment factors being identified may help guide the selection among multiple agents. For instance, a patient’s ability to take methotrexate, often given in combination with biologics, may play a role, as evidence suggests that tocilizumab given as monotherapy is just as effective as combinations of TNF blockers with methotrexate.
Identification of predictive biomarkers, while challenging and expensive, will help to optimize treatment of rheumatoid arthritis. There is a very clear need to come up with a much more sophisticated approach as opposed to the current one based on clinical measures. There has been progress in this area, but we need to continue to invest in biomarker research because this is really a more rational approach and the way forward.
Dr. Tak is professor of medicine at the AMC/University of Amsterdam and Senior Vice President/Head, Therapy Area Immunoinflammation at GlaxoSmithKline. He disclosed that he has been a consultant to Abbott, Amgen, Merck, Pfizer, and Roche/Genentech.