C L M Krieckaert1, S C Nair2, M T Nurmohamed3, C J J van Dongen1, W F Lems4, F P J G Lafeber2, J W J Bijlsma2, H Koffijberg5, G Wolbink6, P M J Welsing7. 1. Jan van Breemen Research Institute | Reade, Amsterdam, The Netherlands. 2. Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands. 3. Jan van Breemen Research Institute | Reade, Amsterdam, The Netherlands Department of Internal Medicine, VU University Medical Center, Amsterdam, The Netherlands. 4. Department of Rheumatology, VU University Medical Center, Amsterdam, The Netherlands. 5. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. 6. Jan van Breemen Research Institute | Reade, Amsterdam, The Netherlands Department of Immunopathology, Sanquin Research and Landsteiner Laboratory Academic Medical Centre, Amsterdam, The Netherlands. 7. Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Abstract
OBJECTIVE: To evaluate the cost-effectiveness of personalised treatment for rheumatoid arthritis (RA) using clinical response and serum adalimumab levels. METHODS: A personalised treatment algorithm defined, based on clinical (European League Against Rheumatism) response and drug levels at 6 months, whether adalimumab treatment should be continued in a specific dose or discontinued and/or switched to a next biological. Outcomes were simulated using a patient level Markov model, with 3 months cycles, based on a cohort of 272 adalimumab-treated patients with RA for 3 years and data of patients from the Utrecht Rheumatoid Arthritis Cohort. Costs, clinical effectiveness and quality adjusted life years (QALYs) were compared with outcomes as observed in usual care and incremental cost-effectiveness ratios were calculated. Analyses were performed probabilistically. RESULTS: Clinical effectiveness was higher for the cohort simulated to receive personalised care compared with usual care; the average difference in QALYs was 3.84 (95 percentile range -8.39 to 16.20). Costs were saved on drugs: €2 314 354. Testing costs amounted to €10 872. Mean total savings were €2 561 648 (95 percentile range -3 252 529 to -1 898 087), resulting in an incremental cost-effectiveness ratio of €666 500 or €646 266 saved per QALY gained from a societal or healthcare perspective, respectively. In 72% of simulations personalised care saved costs and resulted in more QALYs, in 28% it was cost saving with lower QALYs. Scenario analyses showed cost saving along with QALYs gain or limited loss. CONCLUSIONS: Tailoring biological treatment to individual patients with RA starting adalimumab using drug levels and short-term outcome is cost-effective. Results underscore the potential merit of personalised biological treatment in RA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
OBJECTIVE: To evaluate the cost-effectiveness of personalised treatment for rheumatoid arthritis (RA) using clinical response and serum adalimumab levels. METHODS: A personalised treatment algorithm defined, based on clinical (European League Against Rheumatism) response and drug levels at 6 months, whether adalimumab treatment should be continued in a specific dose or discontinued and/or switched to a next biological. Outcomes were simulated using a patient level Markov model, with 3 months cycles, based on a cohort of 272 adalimumab-treated patients with RA for 3 years and data of patients from the Utrecht Rheumatoid Arthritis Cohort. Costs, clinical effectiveness and quality adjusted life years (QALYs) were compared with outcomes as observed in usual care and incremental cost-effectiveness ratios were calculated. Analyses were performed probabilistically. RESULTS: Clinical effectiveness was higher for the cohort simulated to receive personalised care compared with usual care; the average difference in QALYs was 3.84 (95 percentile range -8.39 to 16.20). Costs were saved on drugs: €2 314 354. Testing costs amounted to €10 872. Mean total savings were €2 561 648 (95 percentile range -3 252 529 to -1 898 087), resulting in an incremental cost-effectiveness ratio of €666 500 or €646 266 saved per QALY gained from a societal or healthcare perspective, respectively. In 72% of simulations personalised care saved costs and resulted in more QALYs, in 28% it was cost saving with lower QALYs. Scenario analyses showed cost saving along with QALYs gain or limited loss. CONCLUSIONS: Tailoring biological treatment to individual patients with RA starting adalimumab using drug levels and short-term outcome is cost-effective. Results underscore the potential merit of personalised biological treatment in RA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Authors: Eva L Kneepkens; Mieke F Pouw; Gerrit Jan Wolbink; Tiny Schaap; Michael T Nurmohamed; Annick de Vries; Theo Rispens; Karien Bloem Journal: Br J Clin Pharmacol Date: 2017-08-22 Impact factor: 4.335
Authors: Irina A Tikhonova; Huiqin Yang; Segun Bello; Andrew Salmon; Sophie Robinson; Mohsen Rezaei Hemami; Sophie Dodman; Andriy Kharechko; Richard C Haigh; Meghna Jani; Timothy J McDonald; Martin Hoyle Journal: Health Technol Assess Date: 2021-02 Impact factor: 4.014