1. Evaluating Medical Evidence
for Journalists
Ivan Oransky, MD
Executive Editor, Reuters Health
Association of Health Care Journalists
Atlanta
April 19, 2012
2. Can You Trust Journal Studies?
• How good is peer review?
• Positive publication bias:
Publish a trial that will bring US$100,000 of
profit or meet the end-of-year budget by firing
an editor. -- Former BMJ editor Richard Smith
• Over-reliance on embargoed studies
• How often it turns out to be wrong
3. Embargoes and the Ingelfinger Rule
By the late 20th century, journals needed to compete not
just with each other but with newspapers and other
media…In 1969, the Journal articulated this relationship
in its Ingelfinger Rule, a policy against publishing anything
that had already appeared elsewhere. Other journals
followed suit. This rule, combined with embargo
policies, has led to a carefully choreographed
production in which medical journals and the popular
press work cooperatively and competitively to influence
the news cycle.
-- NEJM, April 19, 2012
12. Conference Pitfalls
• Conferences select presenters based on < 1000 words
• Urologists at U of Florida & Indiana U studied 126
randomized controlled trials presented in 2002-2003
13. Conference Pitfalls
• RCTs are the “gold standard” of medical evidence
• But the quality of that evidence wasn’t pretty
• No abstract said how trial subjects were randomly
assigned to different treatments or placebos
• None told how the study ensured that neither the
researchers nor their doctors knew which they got
• Only about a quarter said how long researchers
followed the subjects in the trial
15. Always Read the Study
Writing about a study after reading just a press
release or an abstract
– without reading the entire paper –
is journalistic malpractice
16. How to Get Studies
• www.EurekAlert.org for embargoed material
• Association of Health Care Journalists membership
includes access to Cochrane Library, Health Affairs,
JAMA, and many other journals
www.healthjournalism.org
• ScienceDirect (Elsevier) gives reporters free access to
hundreds of journals www.sciencedirect.com
• Open access journals (e.g., Public Library of Science
www.plos.org)
• Ask press officers, or the authors
17. How Good Was The Study?
• Was it:
– Peer-reviewed?
– Published? Where?
• Was it in humans?
– It’s remarkable there are any mice left with
cancer, depression, or restless leg syndrome
• Size matters
• Was it well-designed?
19. What’s Your Angle?
• Are you trying to help readers, listeners, and
viewers make better health care decisions?
• Covering a study because it has a good business
angle, or it’s about a local project, is perfectly OK,
but it doesn’t mean readers deserve less
evidence and skepticism
20. Who Could Benefit?
• How many people have the disease?
• Keep potential disease-mongering in mind
21. How Effective is the Treatment?
• Clinically significant endpoints, or surrogates –
does this matter?
• Preventing complications? How many?
• Always remember to quantify results, not just
“patients improved”
22. What Are The Side Effects?
• Every treatment has them
• Where to look:
– Go beyond press releases and abstracts
– Look at tables, charts, and results sections
23. Who Dropped Out?
• Why did they leave the trial?
• Intention to treat analysis
24. How Much Does it Cost?
• If it’s ready to be the subject of a story,
someone has projected the likely cost and
market.
– At least ask.
25. Who Has an Interest?
• Disclose conflicts
• PharmedOut.org
• Dollars For Docs series
http://projects.propublica.org/docdollars/
26. Are There Alternatives?
• Did the study compare the new treatment to
existing alternatives, or to placebo?
• What are the advantages and disadvantages
(and costs) of those existing alternatives?
27. Don’t Rely Only on Study Authors
• Find outside sources. Here’s how:
28. Use Anecdotes Carefully
• Is the story representative?
• Does the source of the story have any conflicts?
29. Watch Your Language
• Lifestyle/diet – are they randomized controlled
trials, or just observational?
• If observational, make the language fit the
evidence:
– YES: “tied,” “linked”
– NO: “reduces,” “causes”
30. Absolute vs. Relative Risk
• Consider the risk for blindness in a patient with
diabetes over a five-year period
• The risk for blindness is 2 in 100 (2%) in people
who get the conventional treatment and 1 in 100
(1%) with a new drug
• The absolute difference is derived by subtracting
the lower risk from the higher risk: 2% - 1% = 1%.
From Covering Medical Research, Schwitzer/AHCJ
31. Absolute vs. Relative Risk
• Expressed as an absolute difference, the new drug
reduces the five-year risk for blindness by 1%.
• The relative difference is the ratio of the two risks.
• Given the data above, the relative difference is:
1% ÷ 2% = 50%
• Expressed as a relative difference, the new drug
cuts the risk of blindness in half.
From Covering Medical Research, Schwitzer/AHCJ
32. Number Needed To Treat
• Same concept as number needed to screen
• Can be calculated from absolute risk:
– 100/absolute risk difference (as a percentage)
33. A Dirty Little Secret
Keep a biostatistician in your back pocket
Photo by Peyri Herrera, on Flickr