Researchers have created a model of predictability of long-term efficacy using 3-month efficacy data in rheumatoid arthritis treatment. Moreover, researchers also show how short-term data can inform the probability of clinical success. The research paper, entitled “Short-term Efficacy Reliably Predicts Long-term Clinical Benefit in Rheumatoid Arthritis Clinical Trials As Demonstrated by Model-Based Meta-Analysis,” was published in The Journal of Clinical Pharmacology.
Rheumatoid Arthritis (RA) is a chronic autoimmune disease characterized by abnormal inflammation, stiffness and swelling of the joints, leading to limited motion and function. According to the American College of Rheumatology, the disease affects more than 1.3 million Americans. At the present, RA is treated through the administration of disease-modifying antirheumatic drugs (DMARDs), that not only manage symptoms but also slow disease progression. These therapeutic agents are classified according to their mechanisms of action, including the commonly prescribed methotrexate (Rheumatrex, Trexall, Otrexup,Rasuvo), leflunomide (Arava), hydroxychloroquine (Plaquenil) and sulfasalazine (Azulfidine).
The development of new drugs for RA treatment is a costly process so, in early stage proof-of-concept (PoC) trials, scientists use 3-month efficacy as a primary endpoint, while 6-month efficacy is used as a primary endpoint in late stage clinical trials. To evaluate if this empirical inference was quantitatively correct and test the ability to predict long-term clinical efficacy of a drug based on short-term data, scientists gathered previously published results from a large RA database of 40 controlled randomized RA clinical trials. Meta-analysis of the relationship between short-term and long-term clinical efficacies in RA trials was made through evaluation of clinical endpoints ACR50 (American College of Rheumatology score, 50% improvement in disease activity) and DAS28 (Disease Activity Score in 28 Joints). Results showed that ACR50 is a reasonable predictor of long-term efficacy, with 3-months values highly correlated with those observed at 6 and 12-months, meaning that efficacy reaches a “plateau” after 3 months of treatment and can be a strong tool in decision-making. Moreover, DAS28, a continuous variable, showed promising results, with values from as early as 1-month proving to be good predictors of long-term efficacy. However, researchers warn these results were based on a limited amount of data, so conclusions are not definitive.
This type of analysis is widely used for the development of new drugs and allows scientists to interpret safety and efficacy results from clinical trials at different stages. The research team concluded that “early efficacy readouts may be helpful at the PoC stage, but this does not supplant the need for longer term safety monitoring that must be accrued in the later stages of clinical development.”
