Improvement in work productivity among psoriatic arthritis patients treated with biologic or targeted synthetic drugs: a systematic literature review and meta-analysis.
Laure GossecBrittany HumphriesMegan RutherfordVanessa TaiebDamon WillemsWilliam TillettPublished in: Arthritis research & therapy (2024)
This systematic literature review and meta-analysis confirmed that patients with active PsA have a substantially reduced capacity to work and participate in leisure activities. Substantial improvements across various WPAI domains were noted after 24 weeks of b/tsDMARD treatment, especially in presenteeism, total work productivity, and activity impairment. These findings may be useful for reimbursement purposes and in the context of shared decision-making. This systematic literature review (SLR) of randomized clinical trials and observational studies of biologic (b) and targeted synthetic (ts) disease-modifying antirheumatic drugs b/tsDMARDs in patients with PsA found that at treatment introduction, patients presented with a 42.7% mean productivity loss per week as assessed by the Work Productivity and Activity Impairment (WPAI) Questionnaire. Through a meta-analysis comparing before/after values without adjustment for placebo response, we found that after 24 weeks of treatment with b/tsDMARDs, there was a mean absolute improvement of 17.6 percentage points and a mean relative improvement of 41% in total work productivity, with similar magnitudes of improvement in time spent at work and regular activities outside of work. These results provide clinical-, regulatory- and reimbursement decision-makers with data on the potential societal and socio-economic benefits of b/tsDMARDs in PsA.
Keyphrases
- climate change
- prostate cancer
- rheumatoid arthritis
- end stage renal disease
- case report
- chronic kidney disease
- randomized controlled trial
- cancer therapy
- clinical trial
- newly diagnosed
- physical activity
- ejection fraction
- drug delivery
- risk assessment
- peritoneal dialysis
- human health
- prognostic factors
- deep learning
- double blind
- preterm birth
- data analysis
- phase iii