#143 - John Ioannidis, M.D., D.Sc.: Why most biomedical research is flawed, and how to improve it

Jan 4, 2021

In this engaging conversation, John Ioannidis, a Stanford University professor and a leading expert in meta-research, reveals startling insights about the flaws in biomedical research. He discusses how most published findings are incorrect, highlighting issues like biases, underpowered studies, and the challenges of nutritional epidemiology versus genetics research. John also shares how our pre-existing beliefs can distort scientific outcomes and stresses the necessity for better research practices. This discussion is a crucial wake-up call for anyone interested in the credibility of scientific studies.

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INSIGHT

Why Most Published Research is False

Most published research findings are false due to various factors like bias, small study sizes, and the sheer volume of research.
These factors increase the likelihood of false positives, making it crucial to evaluate research critically.

INSIGHT

Statistical vs. Clinical Significance

Statistical significance doesn't equate to clinical significance. A p-value indicates the probability of observing a result as extreme, assuming no real effect.
Clinical significance considers the practical impact on patients, which should be the focus in medicine.

INSIGHT

The Problem with Underpowered Studies

Underpowered studies risk both false negatives and exaggerated effect sizes. This is due to the pressure to publish positive results despite limited resources.
Scientists often conduct multiple small studies instead of one large, definitive study, increasing the risk of false positives.

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John Ioannidis is a physician, scientist, writer, and a Stanford University professor who studies scientific research itself, a process known as meta-research. In this episode, John discusses his staggering finding that the majority of published research is actually incorrect. Using nutritional epidemiology as the poster child for irreproducible findings, John describes at length the factors that play into these false positive results and offers numerous insights into how science can course correct. We discuss:

John’s background, and the synergy of mathematics, science, and medicine (2:40);
Why most published research findings are false (10:00);
The bending of data to reach ‘statistical significance,’ and the how bias impacts results (19:30);
The problem of power: How over- and under-powered studies lead to false positives (26:00);
Contrasting nutritional epidemiology with genetics research (31:00);
How to improve nutritional epidemiology and get more answers on efficacy (38:45);
How pre-existing beliefs impact science (52:30);
The antidote to questionable research practices infected with bias and bad incentive structures (1:03:45);
The different roles of public, private, and philanthropic sectors in funding high-risk research that asks the important questions (1:12:00);
Case studies demonstrating the challenge of epidemiology and how even the best studies can have major flaws (1:21:30);
Results of John’s study looking at the seroprevalence of SARS-CoV-2, and the resulting vitriol revealing the challenge of doing science in a hyper-politicized environment (1:31:00);
John’s excitement about the future (1:47:45); and
More.

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