Economic evaluation of a tight-control treatment strategy using an imaging device (handscan) for monitoring joint inflammation in early rheumatoid arthritis.
OBJECTIVE
To evaluate the cost-effectiveness of a tight-control treatment strategy using the handscan (TCHS) compared to using only clinical assessments (TC) and compared to a general non-tight-control treatment strategy (usual care; UC) in early rheumatoid arthritis (RA).


METHODS
Data from 299 early RA patients from the CAMERA trial were used. Clinical outcomes were extrapolated to Quality Adjusted Life Years (QALYs) and costs using a Markov model. Costs and QALYs were compared between the TC and UC treatment strategy arm of the CAMERA trial and a simulated tight-control treatment strategy using the handscan (TCHS). Incremental Cost-Effectiveness Ratios (ICERs) were calculated and several scenario analyses performed. All analyses were performed probabilistically to obtain confidence intervals and costs-effectiveness planes and acceptability curves.


RESULTS
In TCHS, €4,660 (95% CI -€11,516 to €2,045) was saved and 0.06 (95% CI 0.01 to 0.11) QALYs were gained when compared to UC, with an ICER of €77,670 saved per QALY gained. Ninety-one percent (91%) of simulations resulted in less costs and more QALYs. TCHS resulted in comparable costs or even limited savings €642 (95% CI -€6,903 to €5,601)) and comparable QALYs to TC. In all scenario analyses, TCHS and TC were found to be cost effective as compared to UC.


CONCLUSIONS
A tight-control treatment strategy is highly cost-effective compared to a non-tight-control approach in early RA. Using the handscan as a monitoring device might facilitate implementation of tight-control treatment strategy at comparable costs and with comparable effects. This approach should be investigated further.
Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands. s.c.nair@umcutrecht.nl.
S C
SC
Nair
Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
P M J
PM
Welsing
Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
J W G
JW
Jacobs
Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
J M
JM
van Laar
Hemics, Eindhoven, The Netherlands.
W H J
WH
Rensen
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands.
G
G
Ardine de Wit
Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht; and Amsterdam Rheumatology and Immunology Center (ARC), AMC Amsterdam, The Netherlands.
J W J
JW
Bijlsma
Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
F P J G
FP
Lafeber
D000328:Adult; D018501:Antirheumatic Agents / Q000627:therapeutic use; D001172:Arthritis, Rheumatoid / Q000175:diagnosis / Q000191:economics / Q000628:therapy; D003362:Cost-Benefit Analysis; D016903:Drug Monitoring / Q000191:economics / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008390:Markov Chains; D008727:Methotrexate / Q000627:therapeutic use*; D008875:Middle Aged; D009426:Netherlands; D010043:Outcome and Process Assessment, Health Care; D062072:Patient Acuity; D010346:Patient Care Management / Q000191:economics / Q000379:methods; D019057:Quality-Adjusted Life Years
D018501:Antirheumatic Agents; D008727:Methotrexate