The New York Times Magazine has a piece about another instance of scientific fraud, this time by a clinical researcher:
Poehlman pleaded guilty to lying on a federal grant application and admitted to fabricating more than a decade’s worth of scientific data on obesity, menopause and aging, much of it while conducting clinical research as a tenured faculty member at the University of Vermont. He presented fraudulent data in lectures and in published papers, and he used this data to obtain millions of dollars in federal grants from the National Institutes of Health — a crime subject to as many as five years in federal prison. Poehlman’s admission of guilt came after more than five years during which he denied the charges against him, lied under oath and tried to discredit his accusers. By the time Poehlman came clean, his case had grown into one of the most expansive cases of scientific fraud in U.S. history.
I was initially surprised by this passage describing the alteration of data from one experiment:
The fall that DeNino returned to the lab, Poehlman was looking into how fat levels in the blood change with age. DeNino’s task was to compare the levels of lipids, or fats, in two sets of blood samples taken several years apart from a large group of patients. As the patients aged, Poehlman expected, the data would show an increase in low-density lipoprotein (LDL), which deposits cholesterol in arteries, and a decrease in high-density lipoprotein (HDL), which carries it to the liver, where it can be broken down. Poehlman’s hypothesis was not controversial; the idea that lipid levels worsen with age was supported by decades of circumstantial evidence. Poehlman expected to contribute to this body of work by demonstrating the change unequivocally in a clinical study of actual patients over time. But when DeNino ran his first analysis, the data did not support the premise.
When Poehlman saw the unexpected results, he took the electronic file home with him. The following week, Poehlman returned the database to DeNino, explained that he had corrected some mistaken entries and asked DeNino to re-run the statistical analysis. Now the trend was clear: HDL appeared to decrease markedly over time, while LDL increased, exactly as they had hypothesized.
From this it sounds like Poehlman took potentially interesting data that went against existing hypotheses, and changed it so that it lined up with the conventional wisdom in the field. In other words, he fabricated data to make his results less interesting. This is the opposite of how scientific fraud usually works—consider the Jan Hendrik Schön case in condensed matter physics, where Schön invented spectacular and unexpected results that other groups were unable to reproduce.
But reading further in the article, it makes sense: this is how Poehlman was able to present fraudulent data for so long without getting caught. His results seemed solid enough to be impressive, but not surprising enough to draw too much attention.
The length of time that Poehlman perpetrated his fraud — 10 years — and its scope make his case unique, even among the most egregious examples of scientific misconduct. Some scientists believe that his ability to beat the system for so long had as much to do with the research topics he chose as with his aggressive tactics. His work was prominent, but none of his studies broke new scientific ground. (This may also be why no other scientists working in the field have retracted papers as a result of Poehlman’s fraud.) By testing undisputed assumptions on popular topics, Poehlman attracted enough attention to maintain his status but not enough to invite suspicion. Moreover, replicating his longitudinal data would be expensive and difficult to do.
It’s a pretty sad story, and I wonder what medical discoveries might have already been made if this guy had not been obscuring these issues with fabricated data.