Relating intracellular methotrexate polyglutamate concentrations in red blood cells with clinical response in rheumatoid arthritis

Background: Methotrexate (MTX) is used as the gold standard treatment of rheumatoid arthritis (RA). However, the required dose of MTX to achieve the desired clinical outcome varies widely between individuals and is difficult to predict. MTX plasma concentrations have not proven useful as a predictor for MTX treatment outcomes in RA [1]. It has been postulated that intracellular red blood cell (RBC) concentrations of polyglutamated MTX metabolites (MTXGlun, n=2, 3, 4, 5) may instead be predictive of clinical outcomes [2].

Aims: The overarching aim was to develop a population pharmacokinetic-pharmacodynamic (PKPD) model that links MTX and MTXGlun concentrations with the clinical response in RA. As preliminary steps towards this goal, the specific objectives for the current work are:
1. To identify which RBC MTXGlun may best predict the clinical responses and what the suitable clinical response variables might be
2. To assess whether an immediate or delayed concentration-effect relationship is present

Materials & Methods: Pharmacokinetic (PK) and pharmacodynamic (PD) data were available from 48 patients with RA [3,4]. These patients started (n=10), stopped (n=10, including 1 restarter) or received continuous (n=28) MTX treatment. A PK model for RBC concentrations of MTX and MTXGlun was developed previously based on this dataset [5]. The available PD data included swollen joint counts from 28 joints (SJC28), tender joint counts from 28 joints (TJC28), plasma concentrations of C-reactive protein (CRP) and the Disease Activity Score (DAS28).
A graphical analysis was conducted to compare the PK and PD responses for those subjects that started, stopped or continued MTX treatment. Predicted RBC MTXGlun concentrations and the observed clinical responses were plotted over time for each subject using MATLAB. It was assessed which of the MTXGlun showed the best visual correlation with the PD measures, which of the PD measures were suitable variables, and whether there was a time delay present between the maximum PK and maximum PD response.

Results: The plots of RBC PK and PD responses suggested that MTXGlu3 appeared to provide the best descriptor of clinical response measurements based on alignment of the time course. Out of the four clinical response variables, DAS28 and CRP showed good visual correlation with RBC MTXGlu3 in starters, and no delay was evident. However, the PD response variables were highly variable in continuers and stoppers suggesting more complex clinical response changes may have occurred already in the stoppers.

Conclusions: Current graphical analysis gives some direction of the future PKPD development in starters and an immediate PD model will be initially considered. For stoppers a more complicated mechanism needs to be explored such as MTX resistance.

References:
[1] Angelis-Stoforidis P. Clinical and experimental rheumatology Supplement. 1999;17(3): 313.
[2] Dervieux T et al. Arthritis & Rheumatism. 2004;50(9): 2766-2774.
[3] Dalrymple JM et al. Arthritis Rheum. 2008;58(11): 3299-3308.
[4] Stamp LK et al. J Rheumatol. 2011;38(12): 2540-2547.
[5] Korell J et al. Clin Pharmacokinet. 2013;(manuscript submitted).

Shan Pan

  • University of Otago, School of Pharmacy