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Serious Medical Fraud


In [http://chance.dartmouth.edu/chancewiki/index.php/Chance_News_22#I_wasn.27t_making_up_data.2C_I_was_imputing.21 an earlier Chance News wiki] can be found a detailed  treatment of the scientific fraud perpetrated by Eric Poehlman of the University of Vermont.  In [http://chance.dartmouth.edu/chancewiki/index.php/Chance_News_22#Predecessors_of_Poehlman that same issue of Chance News] there is a discussion of Poehlman predecessors who, it is claimed, were even more egregious producers of fraudulent data.  But now we have another contender for the title, Scott S. Reuben of Tufts University and Baystate Medical Center.


According to [http://www.anesthesiologynews.com/index.asp?ses=ogst&section_id=3&show=dept&article_id=12634 Anesthesiology News],
==Forsooth==


Scott S. Reuben, MD, of Baystate Medical Center in Springfield, Mass., a pioneer in the area of multimodal analgesia, is said to have fabricated his results in at least 21, and perhaps many more, articles dating back to 1996. The confirmed articles were published in Anesthesiology, Anesthesia and Analgesia, the Journal of Clinical Anesthesia and other titles, which have retracted the papers or will soon do so, according to people familiar with the scandal. The journals stressed that Dr. Reuben's co-authors on those papers have not been accused of wrongdoing.
==Quotations==
“We know that people tend to overestimate the frequency of well-publicized, spectacular
events compared with more commonplace ones; this is a well-understood phenomenon in
the literature of risk assessment and leads to the truism that when statistics plays folklore,
folklore always wins in a rout.”
<div align=right>-- Donald Kennedy (former president of Stanford University), ''Academic Duty'', Harvard University Press, 1997, p.17</div>


In addition to allegedly falsifying data, Dr. Reuben seems to have committed publishing forgery. Evan Ekman, MD, an orthopedic surgeon in Columbia, S.C., said his name appeared as a co-author on at least two of the retracted papers, despite his having had no hand in the manuscripts. "My names were forgeries on the documents," Dr. Ekman told Anesthesiology News.
----


The reason Reuben’s fraud is so serious is because
"Using scientific language and measurement doesn’t prevent a researcher from conducting flawed experiments and drawing wrong conclusions — especially when they confirm preconceptions."


1. Dr. Reuben has been an extremely active and visible figure in multimodal analgesia, particularly as an advocate for its use in minimally invasive orthopedic and spine procedures. His research has provided support for several mainstays of current anesthetic practice, such as the use of nonsteroidal anti-inflammatory drugs [NSAIDs] and neuropathic agents instead of opioids and preemptive analgesia. Dr. Reuben has also published and presented data suggesting that multimodal analgesia can significantly improve long-term outcomes for patients.
<div align=right>-- Blaise Agüera y Arcas, Margaret Mitchell and Alexander Todoorov, quoted in: The racist history behind facial recognition, ''New York Times'', 10 July 2019</div>


2.  From [http://www.sciam.com/article.cfm?id=...ist-faked-data here]: "We are talking about millions of patients worldwide, where postoperative pain management has been affected by the research findings of Dr. Reuben," says Steven Shafer, editor in chief of the journal Anesthesia & Analgesia, which published 10 of Reuben's fraudulent papers.
==In progress==
[https://www.nytimes.com/2018/11/07/magazine/placebo-effect-medicine.html What if the Placebo Effect Isn’t a Trick?]<br>
by Gary Greenberg, ''New York Times Magazine'', 7 November 2018


Paul White, another editor at the journal, estimates that Reuben's studies led to the sale of billions of dollars worth of the potentially dangerous drugs known as COX2 inhibitors, Pfizer's Celebrex (celecoxib) and Merck's Vioxx (rofecoxib), for applications whose therapeutic benefits are now in question. Reuben was a member of Pfizer's speaker's bureau and received five independent research grants from the company. The editors do not believe patients were significantly harmed by the short-term use of these COX2 inhibitors for pain management but they say it's possible the therapy may have prolonged recovery periods.
[https://www.nytimes.com/2019/07/17/opinion/pretrial-ai.html The Problems With Risk Assessment Tools]<br>
by Chelsea Barabas, Karthik Dinakar and Colin Doyle, ''New York Times'', 17 July 2019


From [http://online.wsj.com/article/SB123672510903888207.html the Wall Street Journal]:  
==Hurricane Maria deaths==
Laura Kapitula sent the following to the Isolated Statisticians e-mail list:


The [Baystate Medical Center] hospital has asked the medical journals to retract the 21 studies, some of which reported favorable results from the use of painkillers like Pfizer Inc.'s Bextra and Merc & Co.'s Vioxx -- both since withdrawn -- as well as Pfizer's Celebrex and Lyrica. Dr. Reuben's research work also claimed positive findings for Wyeth's antidepressant Effexor XR as a pain killer. And he wrote to the Food and Drug Administration, urging the agency not to restrict the use of many of the painkillers he studied, citing his own data on their safety and effectiveness.
:[Why counting casualties after a hurricane is so hard]<br>
:by Jo Craven McGinty, Wall Street Journal, 7 September 2018


Discussion
The article is subtitled: Indirect deaths—such as those caused by gaps in medication—can occur months after a storm, complicating tallies
Laura noted that
:[https://www.washingtonpost.com/news/fact-checker/wp/2018/06/02/did-4645-people-die-in-hurricane-maria-nope/?utm_term=.0a5e6e48bf11 Did 4,645 people die in Hurricane Maria? Nope.]<br>
:by Glenn Kessler, ''Washington Post'', 1 June 2018
 
The source of the 4645 figure is a [https://www.nejm.org/doi/full/10.1056/NEJMsa1803972 NEJM article].  Point estimate, the 95% confidence interval ran from 793 to 8498.
 
President Trump has asserted that the actual number is
[https://twitter.com/realDonaldTrump/status/1040217897703026689 6 to 18].
The ''Post'' article notes that Puerto Rican official had asked researchers at George Washington University to do an estimate of the death toll.  That work is not complete.
[https://prstudy.publichealth.gwu.edu/ George Washington University study]
 
:[https://fivethirtyeight.com/features/we-still-dont-know-how-many-people-died-because-of-katrina/?ex_cid=538twitter We sttill don’t know how many people died because of Katrina]<br>
:by Carl Bialik, FiveThirtyEight, 26 August 2015
 
----
[https://www.nytimes.com/2018/09/11/climate/hurricane-evacuation-path-forecasts.html These 3 Hurricane Misconceptions Can Be Dangerous. Scientists Want to Clear Them Up.]<br>
[https://journals.ametsoc.org/doi/abs/10.1175/BAMS-88-5-651 Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season]<br>
[https://www.nhc.noaa.gov/aboutcone.shtml Definition of the NHC Track Forecast Cone]
----
[https://www.popsci.com/moderate-drinking-benefits-risks Remember when a glass of wine a day was good for you? Here's why that changed.]
''Popular Science'', 10 September 2018
----
[https://www.economist.com/united-states/2018/08/30/googling-the-news Googling the news]<br>
''Economist'', 1 September 2018
 
[https://www.cnbc.com/2018/09/17/google-tests-changes-to-its-search-algorithm-how-search-works.html We sat in on an internal Google meeting where they talked about changing the search algorithm — here's what we learned]
----
[http://www.wyso.org/post/stats-stories-reading-writing-and-risk-literacy Reading , Writing and Risk Literacy]
 
[http://www.riskliteracy.org/]
-----
[https://twitter.com/i/moments/1025000711539572737?cn=ZmxleGlibGVfcmVjc18y&refsrc=email Today is the deadliest day of the year for car wrecks in the U.S.]
 
==Some math doodles==
<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>
 
<math>P(E)  = {n \choose k} p^k (1-p)^{ n-k}</math>
 
<math>\hat{p}(H|H)</math>


1.  The Anesthesiology News article provided this intriguing statistical insight: "Interestingly, when you look at Scott's output over the last 15 years, he never had a negative study," said one colleague, who spoke on the condition of anonymity. "In fact, they were all very robust results--where others had failed to show much difference. I just don't understand why anyone would do this or how anyone could pull this off for so long."  How is this similar to the Madoff scandal?
<math>\hat{p}(H|HH)</math>


2.  The fraud was uncovered in a strange way.  During a routine audit at Baystate, two of Reuben’s abstracts had not been approved by the hospital’s institutional review board (IRB), causing a possible breach of ethics because, whenever patients are involved, IRB approval is required.  It turned out that IRB approval was not needed “because the data were fabricated” according to Dr. Jenson, chief academic officer of Baystate.  “He told Anesthesiology News that simply put, Dr. Reuben had concocted the data—and in many cases the patients themselves—out of vapor.”  Use Google to see the similarity and differences between this and that of the famous Cyril Burt fraud involving identical twins putatively separated at birth. 
==Accidental insights==


3.  From [http://www.sciam.com/article.cfm?id=...ist-faked-data here]: In hindsight, Anesthesia & Analgesia editors Shafer and White admit that it should have been a "red flag" that Reuben's studies were consistently favorable to the drugs he studied. White, who has also received drug company educational grants, says that such funding comes with "subtle pressure" to give the companies the results they want. For now, at least, neither the drug companies nor Reuben's co-authors are officially sharing in the blame, but that's expected to change. "There's a lot of responsibility to pass around," White says, "It's all being focused on Scott Reuben, but the reality is there are many other responsible parties."  What might be the subtle and not-so-subtle pressures of the sponsoring agencies and the institution itself?
My collective understanding of Power Laws would fit beneath the shallow end of the long tail. Curiosity, however, easily fills the fat end.  I long have been intrigued by the concept and the surprisingly common appearance of power laws in varied natural, social and organizational dynamics. But, am I just seeing a statistical novelty or is there meaning and utility in Power Law relationships? Here’s a case in point.


4. Reuben’s journal articles are full of very small p-values and clinically significant effect sizes indicating that NSAIDs are safe and effective for pain medication after surgery. Indeed, his journal articles have the exquisite appearance of how proper comparisons should be presented.  Below is a figure taken from an article supposedly co-authored with Ekman. What does this indicate about the peer review process?
While carrying a pair of 10 lb. hand weights one, by chance, slipped from my grasp and fell onto a piece of ceramic tile I had left on the carpeted floor. The fractured tile was inconsequential, meant for the trash.  
<center>[[File:BrokenTile.jpg | 400px]]</center>
As I stared, slightly annoyed, at the mess, a favorite maxim of the Greek philosopher, Epictetus, came to mind: “On the occasion of every accident that befalls you, turn to yourself and ask what power you have to put it to use.” Could this array of large and small polygons form a Power Law? With curiosity piqued, I collected all the fragments and measured the area of each piece.


Fig. 1 Illustration depicting the dose of morphine at each postoperative time-interval. The placebo group is represented by the straight line, and the celecoxib group is represented by the dashed line. The boxes represent the twenty-fifth to seventy-fifth percentiles, the horizontal lines represent the means, and the extended I-bars represent the fifth to ninety-fifth percentiles. Outliers, as shown by the solid circles, represent values that are >1.5 times the box length. The mean morphine dose at the first six postoperative time-intervals was significantly increased in the placebo group compared with the celecoxib group, as indicated by the double asterisks (p < 0.0001). The mean morphine dose at twenty-four hours was significantly increased in the placebo group compared with the celecoxib group, as indicated by the single asterisk (p < 0.003).
<center>
{| class="wikitable"
|-
! Piece !! Sq. Inches !! % of Total
|-
| 1 || 43.25 || 31.9%
|-
| 2 || 35.25 ||26.0%
|-
|  3 || 23.25 || 17.2%
|-
| 4 || 14.10 || 10.4%
|-
| 5 || 7.10 || 5.2%
|-
| 6 || 4.70 || 3.5%
|-
| 7 || 3.60 || 2.7%
|-
| 8 || 3.03 || 2.2%
|-
| 9 || 0.66 || 0.5%
|-
| 10 || 0.61 || 0.5%
|}
</center>
<center>[[File:Montante_plot1.png | 500px]]</center>
The data and plot look like a Power Law distribution. The first plot is an exponential fit of percent total area. The second plot is same data on a log normal format. Clue: Ok, data fits a straight line.  I found myself again in the shallow end of the knowledge curve. Does the data reflect a Power Law or something else, and if it does what does it reflect?  What insights can I gain from this accident? Favorite maxims of Epictetus and Pasteur echoed in my head:
“On the occasion of every accident that befalls you, remember to turn to yourself and inquire what power you have to turn it to use” and “Chance favors only the prepared mind.”
 
<center>[[File:Montante_plot2.png | 500px]]</center>
   
   
My “prepared” mind searched for answers, leading me down varied learning paths. Tapping the power of networks, I dropped a note to Chance News editor Bill Peterson. His quick web search surfaced a story from ''Nature News'' on research by Hans Herrmann, et. al. [http://www.nature.com/news/2004/040227/full/news040223-11.html Shattered eggs reveal secrets of explosions].  As described there, researchers have found power-law relationships for the fragments produced by shattering a pane of glass or breaking a solid object, such as a stone. Seems there is a science underpinning how things break and explode; potentially useful in Forensic reconstructions.
Bill also provided a link to [http://cran.r-project.org/web/packages/poweRlaw/vignettes/poweRlaw.pdf a vignette from CRAN] describing a maximum likelihood procedure for fitting a Power Law relationship. I am now learning my way through that.
Submitted by William Montante


Submitted by Paul Alper
----

Latest revision as of 20:58, 17 July 2019


Forsooth

Quotations

“We know that people tend to overestimate the frequency of well-publicized, spectacular events compared with more commonplace ones; this is a well-understood phenomenon in the literature of risk assessment and leads to the truism that when statistics plays folklore, folklore always wins in a rout.”

-- Donald Kennedy (former president of Stanford University), Academic Duty, Harvard University Press, 1997, p.17

"Using scientific language and measurement doesn’t prevent a researcher from conducting flawed experiments and drawing wrong conclusions — especially when they confirm preconceptions."

-- Blaise Agüera y Arcas, Margaret Mitchell and Alexander Todoorov, quoted in: The racist history behind facial recognition, New York Times, 10 July 2019

In progress

What if the Placebo Effect Isn’t a Trick?
by Gary Greenberg, New York Times Magazine, 7 November 2018

The Problems With Risk Assessment Tools
by Chelsea Barabas, Karthik Dinakar and Colin Doyle, New York Times, 17 July 2019

Hurricane Maria deaths

Laura Kapitula sent the following to the Isolated Statisticians e-mail list:

[Why counting casualties after a hurricane is so hard]
by Jo Craven McGinty, Wall Street Journal, 7 September 2018

The article is subtitled: Indirect deaths—such as those caused by gaps in medication—can occur months after a storm, complicating tallies

Laura noted that

Did 4,645 people die in Hurricane Maria? Nope.
by Glenn Kessler, Washington Post, 1 June 2018

The source of the 4645 figure is a NEJM article. Point estimate, the 95% confidence interval ran from 793 to 8498.

President Trump has asserted that the actual number is 6 to 18. The Post article notes that Puerto Rican official had asked researchers at George Washington University to do an estimate of the death toll. That work is not complete. George Washington University study

We sttill don’t know how many people died because of Katrina
by Carl Bialik, FiveThirtyEight, 26 August 2015

These 3 Hurricane Misconceptions Can Be Dangerous. Scientists Want to Clear Them Up.
Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season
Definition of the NHC Track Forecast Cone

Remember when a glass of wine a day was good for you? Here's why that changed. Popular Science, 10 September 2018

Googling the news
Economist, 1 September 2018

We sat in on an internal Google meeting where they talked about changing the search algorithm — here's what we learned

Reading , Writing and Risk Literacy

[1]

Today is the deadliest day of the year for car wrecks in the U.S.

Some math doodles

<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>

<math>P(E) = {n \choose k} p^k (1-p)^{ n-k}</math>

<math>\hat{p}(H|H)</math>

<math>\hat{p}(H|HH)</math>

Accidental insights

My collective understanding of Power Laws would fit beneath the shallow end of the long tail. Curiosity, however, easily fills the fat end. I long have been intrigued by the concept and the surprisingly common appearance of power laws in varied natural, social and organizational dynamics. But, am I just seeing a statistical novelty or is there meaning and utility in Power Law relationships? Here’s a case in point.

While carrying a pair of 10 lb. hand weights one, by chance, slipped from my grasp and fell onto a piece of ceramic tile I had left on the carpeted floor. The fractured tile was inconsequential, meant for the trash.

BrokenTile.jpg

As I stared, slightly annoyed, at the mess, a favorite maxim of the Greek philosopher, Epictetus, came to mind: “On the occasion of every accident that befalls you, turn to yourself and ask what power you have to put it to use.” Could this array of large and small polygons form a Power Law? With curiosity piqued, I collected all the fragments and measured the area of each piece.

Piece Sq. Inches % of Total
1 43.25 31.9%
2 35.25 26.0%
3 23.25 17.2%
4 14.10 10.4%
5 7.10 5.2%
6 4.70 3.5%
7 3.60 2.7%
8 3.03 2.2%
9 0.66 0.5%
10 0.61 0.5%
Montante plot1.png

The data and plot look like a Power Law distribution. The first plot is an exponential fit of percent total area. The second plot is same data on a log normal format. Clue: Ok, data fits a straight line. I found myself again in the shallow end of the knowledge curve. Does the data reflect a Power Law or something else, and if it does what does it reflect? What insights can I gain from this accident? Favorite maxims of Epictetus and Pasteur echoed in my head: “On the occasion of every accident that befalls you, remember to turn to yourself and inquire what power you have to turn it to use” and “Chance favors only the prepared mind.”

Montante plot2.png

My “prepared” mind searched for answers, leading me down varied learning paths. Tapping the power of networks, I dropped a note to Chance News editor Bill Peterson. His quick web search surfaced a story from Nature News on research by Hans Herrmann, et. al. Shattered eggs reveal secrets of explosions. As described there, researchers have found power-law relationships for the fragments produced by shattering a pane of glass or breaking a solid object, such as a stone. Seems there is a science underpinning how things break and explode; potentially useful in Forensic reconstructions. Bill also provided a link to a vignette from CRAN describing a maximum likelihood procedure for fitting a Power Law relationship. I am now learning my way through that.

Submitted by William Montante

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