Advances in risk-benefit evaluation using probabilistic simulation methods: an application to the prophylaxis of deep vein thrombosis

被引:50
作者
Lynd, LD [1 ]
O'Brien, BJ
机构
[1] St Josephs Hosp, Ctr Evaluat Med, Hamilton, ON, Canada
[2] McMaster Univ, Dept Clin Epidemiol & Biostat, Program Assessment Technol Hlth, Hamilton, ON L8H 1P1, Canada
关键词
risk; risk assessment; Monte Carlo method; uncertainty; data interpretation; statistical;
D O I
10.1016/j.jclinepi.2003.12.012
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective: To demonstrate the use of probabilistic simulation modeling to estimate the joint density of therapeutic risks and benefits. Published data are used to introduce the risk-benefit acceptability curve as a novel method of illustrating risk-benefit analysis. Study Design and Setting: Using published data, we performed a second-order Monte Carlo simulation to estimate the joint density of major bleeding and deep vein thrombosis (DVT) secondary to enoxaparin or unfractionated heparin. Within a Bayesian framework, beta-distributions for the probabilities of experiencing a DVT and major bleed were derived from the clinical trial, and incremental probabilities were calculated. Results: The incremental risk-benefit pairs from 3,000 simulations are presented on a risk-benefit plane. To accommodate different risk preferences, the results are also illustrated using a risk-benefit acceptability curve, which incorporates different risk-benefit acceptability thresholds (mu), or the number of major bleeds one is willing to accept in order to avert one DVT. Finally, a net-benefit curve is used to illustrate the risk-benefit ratio and the derivation of 95% confidence intervals around the ratio. Conclusion: Modern simulation methods permit the estimation of the joint density of risks and benefits with their associated uncertainty, and within a Bayesian framework, facilitate the estimation of the probability that a therapy is net-beneficial over different preference thresholds for risk-benefit trade-offs. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:795 / 803
页数:9
相关论文
共 18 条
[1]   Calculating confidence intervals for the number needed to treat [J].
Bender, R .
CONTROLLED CLINICAL TRIALS, 2001, 22 (02) :102-110
[2]   THE CE PLANE - A GRAPHIC REPRESENTATION OF COST-EFFECTIVENESS [J].
BLACK, WC .
MEDICAL DECISION MAKING, 1990, 10 (03) :212-214
[3]  
Briggs AH, 1997, HEALTH ECON, V6, P327, DOI 10.1002/(SICI)1099-1050(199707)6:4<327::AID-HEC282>3.0.CO
[4]  
2-W
[5]   The death of cost-minimization analysis? [J].
Briggs, AH ;
O'Brien, BJ .
HEALTH ECONOMICS, 2001, 10 (02) :179-184
[6]   Thinking outside the box: Recent advances in the analysis and presentation of uncertainty in cost-effectiveness studies [J].
Briggs, AH ;
O'Brien, BJ ;
Blackhouse, G .
ANNUAL REVIEW OF PUBLIC HEALTH, 2002, 23 :377-401
[7]   Handling uncertainty in cost-effectiveness models [J].
Briggs, AH .
PHARMACOECONOMICS, 2000, 17 (05) :479-500
[8]   Stratified cost-effectiveness analysis: a framework for establishing efficient limited use criteria [J].
Coyle, D ;
Buxton, MJ ;
O'Brien, BJ .
HEALTH ECONOMICS, 2003, 12 (05) :421-427
[9]   A comparison of low-dose heparin with low-molecular-weight heparin as prophylaxis against venous thromboembolism after major trauma [J].
Geerts, WH ;
Jay, RM ;
Code, KI ;
Chen, EL ;
Szalai, JP ;
Saibil, EA ;
Hamilton, PA .
NEW ENGLAND JOURNAL OF MEDICINE, 1996, 335 (10) :701-707
[10]   Users' guides to the medical literature - XVI. How to use a treatment recommendation [J].
Guyatt, GH ;
Sinclair, J ;
Cook, DJ ;
Glasziou, P .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1999, 281 (19) :1836-1843