Tsung Yu1,2, Janet T Holbrook1, Jennifer E Thorne1,3, Milo A Puhan2. 1. Department of Epidemiology, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. 2. Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland. 3. Department of Ophthalmology/Wilmer Eye Institute, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract
BACKGROUND: Synthesizing evidence from comparative effectiveness trials can be difficult because multiple outcomes of different importance are to be considered. The goal of this study was to demonstrate an approach to conducting quantitative benefit-harm assessment that considers patient preferences. METHODS: We conducted a benefit-harm assessment using data from the Multicenter Uveitis Steroid Treatment Trial that compared corticosteroid implant versus systemic corticosteroids and immunosuppression in non-infectious intermediate, posterior, and panuveitis. We focused on clinical outcomes considered important to patients, including visual acuity, development of cataracts/glaucoma, need for eye surgery, prescription-requiring hypertension, hyperlipidemia, and infections. Patient preferences elicited in a recent survey were then incorporated into our assessment of the benefit-harm balance. RESULTS: Benefit-harm metrics were calculated for each time point that summarized the numbers of outcomes, caused or prevented by implant therapy versus systemic therapy if 1000 patients were treated. The benefit-harm metric was -129 (95% confidence interval: -242 to -14), -317 (-436 to -196), -390 (-514 to -264), and -526 (-687 to -368) at 6, 12, 18, and 24 months follow up, respectively, suggesting that systemic therapy may have a better benefit-harm balance. However, measures of quality of life for patients treated with implant therapy were found to be better than patients treated with systemic therapy over the same time period. CONCLUSIONS: Results of benefit-harm assessment were different from the prospectively collected quality of life data during trial follow up. Future studies should explore the reasons for such discrepancies and the strength and weakness of each method to assess treatment benefits and harms.
BACKGROUND: Synthesizing evidence from comparative effectiveness trials can be difficult because multiple outcomes of different importance are to be considered. The goal of this study was to demonstrate an approach to conducting quantitative benefit-harm assessment that considers patient preferences. METHODS: We conducted a benefit-harm assessment using data from the Multicenter Uveitis Steroid Treatment Trial that compared corticosteroid implant versus systemic corticosteroids and immunosuppression in non-infectious intermediate, posterior, and panuveitis. We focused on clinical outcomes considered important to patients, including visual acuity, development of cataracts/glaucoma, need for eye surgery, prescription-requiring hypertension, hyperlipidemia, and infections. Patient preferences elicited in a recent survey were then incorporated into our assessment of the benefit-harm balance. RESULTS: Benefit-harm metrics were calculated for each time point that summarized the numbers of outcomes, caused or prevented by implant therapy versus systemic therapy if 1000 patients were treated. The benefit-harm metric was -129 (95% confidence interval: -242 to -14), -317 (-436 to -196), -390 (-514 to -264), and -526 (-687 to -368) at 6, 12, 18, and 24 months follow up, respectively, suggesting that systemic therapy may have a better benefit-harm balance. However, measures of quality of life for patients treated with implant therapy were found to be better than patients treated with systemic therapy over the same time period. CONCLUSIONS: Results of benefit-harm assessment were different from the prospectively collected quality of life data during trial follow up. Future studies should explore the reasons for such discrepancies and the strength and weakness of each method to assess treatment benefits and harms.
Authors: D A Jabs; J T Rosenbaum; C S Foster; G N Holland; G J Jaffe; J S Louie; R B Nussenblatt; E R Stiehm; H Tessler; R N Van Gelder; S M Whitcup; D Yocum Journal: Am J Ophthalmol Date: 2000-10 Impact factor: 5.258
Authors: M H Gail; J P Costantino; J Bryant; R Croyle; L Freedman; K Helzlsouer; V Vogel Journal: J Natl Cancer Inst Date: 1999-11-03 Impact factor: 13.506
Authors: Nancy K Janz; Patricia A Wren; Kenneth E Guire; David C Musch; Brenda W Gillespie; Paul R Lichter Journal: Ophthalmology Date: 2007-05-09 Impact factor: 12.079
Authors: Shahrul Mt-Isa; Christine E Hallgreen; Nan Wang; Torbjörn Callréus; Georgy Genov; Ian Hirsch; Stephen F Hobbiger; Kimberley S Hockley; Davide Luciani; Lawrence D Phillips; George Quartey; Sinan B Sarac; Isabelle Stoeckert; Ioanna Tzoulaki; Alain Micaleff; Deborah Ashby Journal: Pharmacoepidemiol Drug Saf Date: 2014-05-13 Impact factor: 2.890