The commitment By Hirschel D. McGinnis, MD, FSIR
The language of bias I
n recent years, discussions regarding the manifestations and prevalence of healthcare disparities have noticeably increased in medical literature. One cause of these disparities is bias, which challenges us to question how much we really understand the nature of how bias is shown.
The fundamentals of bias Bias is defined as an unreasoned and unfair distortion of judgment that may be exercised in favor of or against one person, thing or group compared to another. While the word itself is neutral, bias is typically regarded as negative or unfair. Bias can be possessed by an individual, a group, an institution or, in its broadest form, a society.
There are two common forms of bias: conscious bias, also known as explicit bias, and unconscious bias, also known as implicit bias. Explicit bias is a consciously held prejudicial belief or attitude, and it is the traditional form of bias most people conceive when they think about this topic. While explicit bias is possessed within the awareness of the individual, it may or may not be acted upon. In fact, awareness is a powerful force in mitigating its effects.1
Implicit bias is an unknown or unacknowledged form of bias. The holder of implicit bias is unaware they possess partiality, allowing themself the illusion of being fair. However, objective examination of their acts may reveal a very different reality. Implicit bias most often manifests in the form of prejudicial instincts about groups of people. This is a universal phenomenon believed to be a part of human psychology rooted in mental maps and automatic processing. Essentially, these processes allow individuals to quickly sort others into recognizable groups with stereotypical
traits. This phenomenon is imperfectly understood but is an inherent part of human behavior. Implicit bias is far more commonly expressed than explicit bias and is insidious in nature.
It’s important to appreciate that implicit bias does not require animus. It is expressed automatically in a subconscious manner. All that’s required is knowledge of and belief in a stereotype or implicit attitude.
Bias in medical research and applications Within medical research, biases and confounders may impair us from understanding the truth of what is being studied and can steer us from knowing what best practices should be.
Information bias is defined as “Any systematic difference from the truth that arises in the collection, recall, recording and handling of information in a study, including how missing data is treated.”1 These variations are most often due to:
• Misclassification bias: categorization of a subject into an incorrect cohort which may alter the observed outcome between groups and the outcome being studied.
• Observer bias: discrepancies from the truth that are observed or recorded into the data.
• Recall bias: systematic errors that become part of the recorded data due to participants recalling previous events inaccurately or incompletely.
Selection bias is another significant source of distortion in research. This type of bias “occurs when individuals or groups in a study differ systematically from the population of interest leading to a systematic error in an association or outcome.”1
We commonly see such bias in clinical trials where the group being studied varies in its composition significantly from the overall population. Data from the 2020 census captured that approximately 40% of the United States population identified as non- white. However, in the Federal Drug Administration’s 2020 data snapshot on diversity and inclusion in clinical drug trials, only 25% of participants were non-white.2
The FDA approved
50 new therapies in 2021. Of the 50 clinical trials, there were only 7 where patients who identify as Black, Asian or Hispanic all participated in percentages that approximated or exceeded their societal representation. Disparities in representation were most noticeable in oncology trials with Black participation at 4.1% and Hispanic participation at 6.9%. A retrospective study of all registered U.S. clinical trials from 2000–2020 (20,692 studies; ~4.76 million enrollees) revealed that only 43% reported data regarding race and ethnicity.5
The median combined
participation by racial and ethnic minorities was well-below census representation at 27.6% (36% in the 2010 U.S. Census).6,7
Within radiology, adjustments were recently made regarding the inclusion criteria for Low Dose Lung Cancer Screening (LDLCS) by the United State Preventative Services Task Force (USPSTF). The National Lung Screening Trial (NLST) conducted between 2002– 2004 had 53,452 participants; however, only 4.4% of enrollees identified as Black (2,376). The NLST demonstrated a 16% reduction in lung cancer mortality with the use of LDLCS in patients 55–80 years old with a 30 pack-year smoking exposure who were active smokers or had quit within the past 12 years. In 2021,
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