Patients that frequently participate in multiple research studies to generate income may be a hazard to data quality and study results, and companies and organizations that sponsor clinical trials need to be prepared, according to recent studies of so-called professional patients.
There are a number of problems related to professional patients enrolling in multiple studies, foremost a legitimate concern about their health or potential drug interactions from studies. However, deception rates is another problem linked to professional patients that is less frequently discussed in the life sciences industry.
The current policies of the Food and Drug Administration (FDA) do not actively prevent participants from enrolling in multiple studies. Although it is a standard practice of the FDA to exclude participants who are taking part in other clinical trials, this information isn’t frequently verified. Instead, the self-reporting of subjects who claim to not be participating in any other trials is taken at face value and not investigated any further.
The approval of most drugs is based on two independent clinical trials. If there are patients who are in both studies, the trials are no longer fully independent. As long as this isn't the case, participating in a number of studies isn't necessarily a problem. Some people may be genuinely motivated by contributing to medical knowledge. But the bigger issue at hand is the potential deception rates of some of these participants.
Building on past research findings that uncovered high fabrication rates by professional patients, researchers at Boston University School of Medicine and Fairleigh Dickinson University collaborated to study the prevalence of deception used by these subjects and found “significant correlations between deception rates and monetary reward, risk to health and age scores.”
The researchers ran a study consisting of 100 subjects who had participated in at least two studies in the past year.
The study uncovered a number of key findings, but one result stood apart from the rest. In the population sampled, 75% of the frequent study participants admitted withholding or hiding information at least once out of fear that they wouldn’t be admitted into a study. In addition, 32% of the subjects hid health problems, 28% concealed use of prescribed medications and 20% were not honest about recreational drug use, according to the patients. In addition, 25% admitted exaggerating symptoms and 14% pretended to have a health condition in order to participate in a study.
Professional patients who were deceptive were also likely to be motivated by financial incentives of trial participation. The logic follows that if participants are relying on study participation to generate income, they may stretch the truth as needed to be admitted into a study.
The Boston University and Fairleigh Dickinson researchers found that professional patients who make up false information are more of a threat to a study validity than patients who hide information. This is especially true when the disease or the conditions being measured cannot be verified objectively. For instance, there isn’t any way to measure a patient’s level of depression or amount of physical pain. Instead, the information is typically accepted at face value as true.
In more extreme cases, some frequent study participants even mentioned taking an extra step to access shared information and qualify for a study. In these instances, a “research kingpin” was paid by the professional patients for a list of answers to successfully pass the screening questions. The price can vary depending on how much the study pays. If the study participant doesn’t pay the fee in these cases, they will not be allowed to receive similar information in the future.
Moving forward, clinical research associates need to be able to identify professional patients and monitor the data to avoid deception and other problems. One school of thought advocates using 100% source data verification (SDV), however this isn’t the most effective method to spot professional patients. Instead, only by taking a step back and looking at all of the data in the aggregate is it easiest to spot these study participants. In recent years pharma industry association TransCelerate has called for companies to move away from SDV and towards risk-based monitoring (RBM) activities that concentrate on what is critical for studies and sites.
The Boston University-Fairleigh Dickinson results support the hypothesis that generalized SDV has limited value as a quality control measure and reinforce the value of other risk-based monitoring activities.
Only through a birdseye view of the region will it be possible to identify individuals that participate in more than one study or other data anomalies.
[A version of this article originally appeared on Geeks Talk Clinical.]
