Joint distribution approaches to simultaneously quantifying benefit and risk.
BACKGROUND
The benefit-risk ratio has been proposed to measure the tradeoff between benefits and risks of two therapies for a single binary measure of efficacy and a single adverse event. The ratio is calculated from the difference in risk and difference in benefit between therapies. Small sample sizes or expected differences in benefit or risk can lead to no solution or problematic solutions for confidence intervals.


METHODS
Alternatively, using the joint distribution of benefit and risk, confidence regions for the differences in risk and benefit can be constructed in the benefit-risk plane. The information in the joint distribution can be summarized by choosing regions of interest in this plane. Using Bayesian methodology provides a very flexible framework for summarizing information in the joint distribution.


RESULTS
Data from a National Institute of Child Health & Human Development trial of hydrocortisone illustrate the construction of confidence regions and regions of interest in the benefit-risk plane, where benefit is survival without supplemental oxygen at 36 weeks postmenstrual age, and risk is gastrointestinal perforation. For the subgroup of infants exposed to chorioamnionitis the confidence interval based on the benefit-risk ratio is wide (Benefit-risk ratio: 1.52; 90% confidence interval: 0.23 to 5.25). Choosing regions of appreciable risk and acceptable risk in the benefit-risk plane confirms the uncertainty seen in the wide confidence interval for the benefit-risk ratio--there is a greater than 50% chance of falling into the region of acceptable risk--while visually allowing the uncertainty in risk and benefit to be shown separately. Applying Bayesian methodology, an incremental net health benefit analysis shows there is a 72% chance of having a positive incremental net benefit if hydrocortisone is used in place of placebo if one is willing to incur at most one gastrointestinal perforation for each additional infant that survives without supplemental oxygen.


CONCLUSIONS
If the benefit-risk ratio is presented, the joint distribution of benefit and risk also should be shown. These regions avoid the ambiguity associated with collapsing benefit and risk to a single dimension. Bayesian methods allow even greater flexibility in simultaneously quantifying benefit and risk.
Shaffer
Michele L
ML
Department of Health Evaluation Sciences, Penn State College of Medicine, Hershey, PA, USA. mshaffer@hes.hmc.psu.edu
Watterberg
Kristi L
KL
D000893:Anti-Inflammatory Agents / Q000009:adverse effects / Q000627:therapeutic use; D001499:Bayes Theorem; D002821:Chorioamnionitis / Q000188:drug therapy; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D006854:Hydrocortisone / Q000009:adverse effects / Q000627:therapeutic use; D052577:Infant, Extremely Low Birth Weight; D007231:Infant, Newborn; D007416:Intestinal Perforation / Q000139:chemically induced; D015233:Models, Statistical; D015337:Multicenter Studies as Topic; D010102:Oxygen Inhalation Therapy; D010919:Placebos; D011247:Pregnancy; D016032:Randomized Controlled Trials as Topic; D018570:Risk Assessment / Q000379:methods*; D016019:Survival Analysis; D035501:Uncertainty
D000893:Anti-Inflammatory Agents; D010919:Placebos; D006854:Hydrocortisone