Kevin M Fain1, Tsung Yu2, Tianjing Li2, Cynthia M Boyd3, Sonal Singh4, Milo A Puhan5. 1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA. Electronic address: kfain1@jhu.edu. 2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA. 3. Division of Geriatric Medicine and Gerontology, Johns Hopkins School of Medicine, 5200 Eastern Avenue, Baltimore, MD 21224, USA. 4. Division of General Internal Medicine, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, USA. 5. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA; Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, Switzerland.
Abstract
OBJECTIVES: To describe challenges and make recommendations for researchers in how they select evidence to quantitatively assess a prescription drug's benefits and harms. STUDY DESIGN AND SETTING: These challenges and recommendations are based on our recent experience conducting a benefit-harm assessment for the prescription drug roflumilast. We considered the selection of evidence to quantify (1) the drug's treatment effects in patients, (2) the patient population's baseline risks for beneficial and harmful outcomes without treatment, and (3) the patient population's preferences for these beneficial effects and harms. These are fundamental steps for most benefit-harm assessment methods. RESULTS: We identify critical issues in selecting evidence for each of these steps. We justify in particular the need to incorporate (1) clinical trials for the drug's specific treatment effect; (2) observational studies with the most valid, precise, and applicable effect estimates for the baseline risk; and (3) flexible weighting approaches for balancing the drug benefits and harms. CONCLUSION: We identify challenges and make recommendations for selecting evidence at the critical steps in a prescription drug's benefit-harm assessment. Our findings should assist other researchers conducting these assessments for prescription drugs, which could help regulators, medical professionals, and patients make better decisions about prescription drug use.
OBJECTIVES: To describe challenges and make recommendations for researchers in how they select evidence to quantitatively assess a prescription drug's benefits and harms. STUDY DESIGN AND SETTING: These challenges and recommendations are based on our recent experience conducting a benefit-harm assessment for the prescription drug roflumilast. We considered the selection of evidence to quantify (1) the drug's treatment effects in patients, (2) the patient population's baseline risks for beneficial and harmful outcomes without treatment, and (3) the patient population's preferences for these beneficial effects and harms. These are fundamental steps for most benefit-harm assessment methods. RESULTS: We identify critical issues in selecting evidence for each of these steps. We justify in particular the need to incorporate (1) clinical trials for the drug's specific treatment effect; (2) observational studies with the most valid, precise, and applicable effect estimates for the baseline risk; and (3) flexible weighting approaches for balancing the drug benefits and harms. CONCLUSION: We identify challenges and make recommendations for selecting evidence at the critical steps in a prescription drug's benefit-harm assessment. Our findings should assist other researchers conducting these assessments for prescription drugs, which could help regulators, medical professionals, and patients make better decisions about prescription drug use.
Authors: Henock G Yebyo; Sofia Zappacosta; Hélène E Aschmann; Sarah R Haile; Milo A Puhan Journal: BMC Cardiovasc Disord Date: 2020-09-17 Impact factor: 2.298
Authors: Brian S Alper; Peter Oettgen; Ilkka Kunnamo; Alfonso Iorio; Mohammed Toseef Ansari; M Hassan Murad; Joerg J Meerpohl; Amir Qaseem; Monica Hultcrantz; Holger J Schünemann; Gordon Guyatt Journal: BMJ Open Date: 2019-06-04 Impact factor: 2.692