The New York Times has an informative summary of a recent research scandal involving a
prominent researcher at the University of Vermont, Eric Poehlman.
-
An Unwelcome Discovery, by Jeneen Interlandi, October 22, 2006.
The Poehlman scandal represents perhaps the biggest cases of research fraud in recent
history.
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.
The first person to speak up about the possibility of fraud in Poehlman's work was one of
his research assistants, Walter DeNino.
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.
Although DeNino trusted his boss implicitly, the change was too great to be explained
by a handful of improperly entered numbers, which was all Poehlman claimed to have
fixed. DeNino pulled up the original figures and compared them with the ones Poehlman
had just given him. In the initial spreadsheet, many patients showed an increase in HDL
from the first visit to the second. In the revised sheet, all patients showed a
decrease. Astonished, DeNino read through the data again. Sure enough, the only numbers
that hadn't been changed were the ones that supported his hypothesis.
When Poehlman brushed DeNino's concerns aside, so DeNino started asking around and other
graduate students and postdocs had similar concerns. He got some cautionary advice from a
former postdoctoral fellow
Being associated with either falsified data or a frivolous allegation against a
scientist as prominent as Poehlman could end DeNino's career before it even began.
and a faculty member who shared lab space with Poehlman advised
If you're going to do something, make sure you really have the evidence.
So DeNino started looking for the evidence.
DeNino spent the next several evenings combing through hundreds of patients' records
in the lab and university hospital, trying to verify the data contained in Poehlman's
spreadsheets. Each night was worse than the one before. He discovered not only reversed
data points, but also figures for measurements that had never been taken and even
patients who appeared not to exist at all.
DeNino presented his evidence to the university counsel and the response of Poehlman to
his department chair, Burton Sobel, was rather startling.
The accused scientist gave him the impression that nothing was wrong and seemed
mostly annoyed by all the fuss. In his written response to the allegations, Poehlman
suggested that the data had gotten out of hand, accumulating numerous errors because of
handling by multiple technicians and postdocs over the years. 'I found that noncredible,
really, for an investigator of Eric's experience,' Sobel later told the investigative
panel. 'There had to be a backup copy that was pure,' Sobel reasoned before the panel.
'You would not have postdocs and lab techs in charge of discrepant data sets.' But
Poehlman told Sobel that there was no master copy.
At the formal hearing, Poehlman had a different defense.
First, he attributed his mistakes to his own self-proclaimed ineptitude with Excel
files. Then, when pressed on how fictitious numbers found their way into the spreadsheet
he'd given DeNino, Poehlman laid out his most elaborate explanation yet. He had imputed
data ' that is, he had derived predicted values for measurements using a complicated
statistical model. His intention, he said, was to look at hypothetical outcomes that he
would later compare to the actual results. He insisted that he never meant for DeNino to
analyze the imputed values and had given him the spreadsheet by mistake.
The New York Times article points out how pathetic this attempted explanation was.
Although data can be imputed legitimately in some disciplines, it is generally
frowned upon in clinical research, and this explanation came across as hollow and
suspicious, especially since Poehlman appeared to have no idea how imputation was done.
A large portion of the article examines how research fraud can occur in a system that is
supposed to be self-correcting.
First, the people who are mostly likely to notice fraud are junior investigators who are
subordinate to their research mentor. It's psychologically and emotionally difficult to
confront someone who has devoted time to your professional development. Even when an
investigator is emotionally willing to confront their mentor, they have their career concerns
to worry about.
The principal investigator in a lab has the power to jump-start careers. By writing
papers with graduate students and postdocs and using connections to help obtain
fellowships and appointments, senior scientists can help their lab workers secure
coveted tenure-track jobs. They can also do damage by withholding this support.
Every university will have a system in place to investigate claims of fraud. But there are
problems here as well.
All universities that receive public money to conduct research are required to have
an integrity officer who ensures compliance with federal guidelines. But policing its
scientists can be a heavy burden for a university. 'It's your own faculty, and there's
this idea of supporting and nurturing them,' says Ellen Hyman-Browne, a
research-compliance officer at the Children's Hospital of Philadelphia, a teaching
hospital. Moreover, investigations cost time and money, and no institution wants to
discover something that could cast a shadow on its reputation.
'There are conflicting influences on a university where they are the co-grantor and
responsible to other investigators,' says Stephen Kelly, the Justice Department attorney
who prosecuted Poehlman. 'For the system to work, the university has to be very
ethical.'
Poehlman himself was careful and chose areas where fraud would be especially difficult to
detect. He specialized in presenting longitudinal data, data that is very expensive to
replaicate. He also presented research results that confirmed what most researchers had
suspected, rather than results that would undermine existing theories of nutrition.
At his sentencing, Poehlman was sentenced to one year and one day in federal prison,
making him the first researcher to serve time in jail for research fraud.
'When scientists use their skill and their intelligence and their sophistication and
their position of trust to do something which puts people at risk, that is
extraordinarily serious,' the judge said. 'In one way, this is a final lesson that you
are offering.'
I'm going to submit this material to the Chance News wiki site.
07/08/2008.
