Related Experiment Video
Updated: Aug 24, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
A surplus of positive trials: weighing biases and reconsidering equipoise
David T Felson1, Leonard Glantz
1Boston University School of Medicine, Boston, Massachusetts, USA. dfelson@bu.edu
Abstract:
In this issue, Fries and Krishnan raise provocative new ideas to explain the surfeit of positive industry sponsored trials evaluating new drugs. They suggest that these trials were designed after so much preliminary work that they were bound to be positive (design bias) and that this violates clinical equipoise, which they characterize as an antiquated concept that should be replaced by a focus on subject autonomy in decision making and expected value for all treatments in a trial. We contend that publication bias, more than design bias, could account for the remarkably high prevalence of positive presented trials. Furthermore, even if all new drugs were efficacious, given the likelihood of type 2 errors, not all trials would be positive. We also suggest that clinical equipoise is a nuanced concept dependent on the existence of controversy about the relative value of two treatments being compared. If there were no controversy, then trials would be both unnecessary and unethical. The proposed idea of positive expected value is intriguing, but in the real world such clearly determinable values do not exist. Neither is it clear how investigators and sponsors, who are invested in the success of a proposed therapy, would (or whether they should) develop such a formula.
Related Concept Videos
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Confirmation Biases
Bias in Epidemiological Studies
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Confounding in Epidemiological Studies