Download In search of the right word: a statement of the HEART Group on

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Cardiac contractility modulation wikipedia , lookup

Quantium Medical Cardiac Output wikipedia , lookup

Cardiac surgery wikipedia , lookup

Coronary artery disease wikipedia , lookup

Remote ischemic conditioning wikipedia , lookup

Cardiovascular disease wikipedia , lookup

Saturated fat and cardiovascular disease wikipedia , lookup

Transcript
THE EDITOR’S PAGE
European Heart Journal (2013) 34, 7–9
doi:10.1093/eurheartj/ehs387
In search of the right word: a statement of the
HEART Group on scientific language
Thomas F. Lüscher*
Editorial Office, European Heart Journal, Zurich Heart House, Moussonstreet 4, 8091 Zürich, Switzerland
This editorial refers to ‘Statement on matching language
to the type of evidence used in describing observational
studies vs. randomized trials†, by the Editors of the
Heart Group Journals, on page 20
Facts and precision
To improve language, means to improve thinking—nothing else!
Friedrich Nietzsche (1844–1900)
For scientists, the world consists of facts, as the seminal philosopher Ludwig Wittgenstein put it almost a century ago.1 Facts are
observed and measured by equipment and devices of ever
greater precision, and eventually described using highly accurate
and well-defined words—usually of Latin descent to give them
greater weight. In any case, the expressions we use should
match what they describe.2 Ever since its existence, science has
stood for precision, both in quantifying phenomena and with
regard to the language used. In contrast to fiction and poetry,
where uncertainty, double-meaning, and symbolism are part of
the art, scientific writing utilizes words with well-defined meanings.
Widely accepted definitions—from the Latin word definere for
restricting—are the basis of scientific communication, be it in
logic, mathematics, physics, life sciences, or medicine.
Facts and causes
What is beyond the realm of fact does not exist in the world of
science. This may sound rather restrictive, but it is not. Indeed,
we have come very far by restricting ourselves to measurable
facts. Impressively, in ,500 years, we advanced from anatomy to
physiology, and from early diagnostics to modern-day evidencebased medicine involving genetics, cell biology, large registries,
and randomized trials.3
Undoubtedly, the words and expressions scientists used over time
were part of the paradigms4 they used in their research. Accordingly,
their meanings changed as concepts advanced to today’s science. At
each stage of the scientific process, however, they were fundamental
for proper communication and for the growth of knowledge.
The discovery of causality was essential for the advancement of
science and medicine. If the cause of a disease was discovered, a
remedy was in sight. The first physician to take this seriously was
James Lind (1716–1794), a naval physician and native of Edinburgh,
who developed the theory that citrus fruits could cure scurvy, a
then major problem for the Royal Navy as well as the French
and Spanish fleets when on the high seas. At sea, Lind divided 12
scorbutic sailors into six treatment groups. They all received the
same diet but, in addition, group 1 was given a quart of cider
daily, group 2, were given 25 drops of elixir of sulfuric acid,
group 3 were give six spoons of vinegar, group 4 were given half
a pint of seawater, group 5 were given oranges and lemon, and
the last group were given a spicy paste plus barley water. The
treatment of group 5 stopped after 6 days when they ran out of
fruit, but by that time one sailor was fit for duty, while the other
had almost recovered.5 While today, such a small sample size
would lead to immediate rejection of such a study by any recognized journal, including the European Heart Journal,6 Lind made
history with his experiments.
Today, such trials are usually based on experimental data and
tested in much larger trials. For instance, Anitchkow’s seminal
experiments with rabbits fed a high fat diet provided the experimental evidence for the cholesterol theory of atherosclerosis7 put
forward already by Rudolf Virchow in the 19th century. But a
rabbit is a rabbit, not a human. The Framingham study then provided
epidemiological data that indeed showed that in apparently healthy
humans, plasma cholesterol levels were predictive of the outcome,
and specifically of the clinical consequences, of atherosclerosis
such as myocardial infarction, stroke, and cardiovascular death.8
Associations and causes
However, as outlined by the statement of the HEART Group, an
informal group of all editors of cardiovascular journals,9 associations—such as those provided by epidemiological studies—are
not necessarily proof of causality. Indeed, up until the late 1980s,
many eminent clinical scientist—among them, Sir Michael Oliver
as one of the most outspoken10—put the cholesterol hypothesis
in doubt and—based on the early trials with fibrates such as clofibrate—claimed that cholesterol lowering would lead to depression,
suicide, accidents, and death, all events seemingly associated with
low cholesterol in early studies.
* Corresponding author. Tel: +44 255 21 21, Fax: +44 255 42 51, Email: [email protected]
†
doi:10.1093/eurheartj/ehs386.
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2012. For permissions please email: [email protected]
8
The Editor’s Page
Table 1
Comparison of randomized clinical trials and observational studies and registries
Randomized clinical trials
Observational studies and prospective registries
...............................................................................................................................................................................
Inclusion criteria
No or few inclusion criteria
Exclusion criteria
Standarized and blinded treatment
No or few exclusion criteria
Treatment according to discretion of physician
Defined outcome measures
Defined outcome measures
Well defined and monitored data collection
Short duration
Data collection often less complete and less perfect
Usually prolonged duration
Real-world data
High risk patients ideally well represented
Unbiased comparison of treatments groups
Confounding variables
Straight forward statistics with comparison of groups
Very expensive
Complex statistics with correction of confounding variables (multivariate and propensity analysis)
Less expensive
Things started to change as Michael Brown and Joseph Goldstein
provided the understanding of cholesterol uptake and synthesis by
the liver11 and when Akiro Endo isolated the first compounds inhibiting the 3-hydroxy-3-methylglutaryl coenzyme A reductase
pathway.12 Eventually the seminal 4S study involving 4444 patients
with or at risk of cardiovascular disease13—and thereafter many
other large randomized trials14—proved beyond reasonable
doubt that lowering cholesterol with statins reduced major
cardiac events.
As pointed out in table 1 of the HEART group statement published in this issue of the European Heart Journal,15 the appropriate
description for epidemiological data would be ‘in subjects with
lower cholesterol levels, a lower cardiovascular risk was observed’,
while 4S and the later randomized trials showed that ‘statins
reduce cardiovascular events’. While the former describes an
association, the latter proves causality.
2,000
1.0
1,500
0.75
1,000
0.5
1965
1970
1975
Millions of newborn babies ( )
Continued observation periods
Not generalizable results
High-risk patients often excluded
Pairs of brooding stocks ( )
(Premature) termination when outcome reached
1980
Year
Figure 1 Relationship between pairs of brooding storks and
the number of newborn babies (in millions) over time (modified
from Sies16). Reprinted by permission from Macmillan Publishers
Ltd: Nature ‘A new parameter for sex education’. & 1988.
The importance of proper wording
This distinction is important for the proper practice of medicine:
indeed, to the surprise of many clinicians, the CAST study
showed that while antiarrhythmics suppressed extrasystoles effectively, the drugs increased mortality. Thus, markers of disease are
not necessarily its cause and hence not always an appropriate
target of therapy. Similar observations have been made with activators of cAMP in heart failure where the drugs improved physical
performance of highly symptomatic patients, but increased mortality. Finally, homocysteine, while a highly predictive marker of
outcome in primary prevention, proved not to be a therapeutic
target since, in large intervention trials, a reduction of its plasma
levels by chronic supplementation with folic acid had no effect
on major cardiovascular events in the participating subjects.
Judgement and evidence
Hence, it became clear that only well-designed and properly performed randomized clinical trials comparing a novel remedy with
placebo were able to provide convincing proof of causality—and
this made them the basis of modern medicine and the guidelines
we use.15 Obviously, we intuitively take associations frequently
for causality. For instance, the change in the number of pairs of
breeding storks and the millions of newborn babies in Europe
show a strong correlation over time (Figure 1).16 Unfortunately,
this does not confirm the popular fairy tale.
Nevertheless, observational studies and prospective registries
are not without value (Table 1). Indeed, if properly performed,
registries reflect the real-world situation much more closely than
randomized trials since no or few inclusion criteria are used and
treatments regimens are those of current clinical practice. Of
note, event and mortality rates are considerably higher in registries
than they are in randomized trials. Hence, data obtained under
real-world conditions are more generalizable than those of randomized trials which may be applicable only to a highly defined group
of patients. On the other hand, the results of registries are prone
to unmeasured confounders. Additionally, data collection may be
less complete and of lower quality as compared with randomized
and well monitored trials. Therefore, while novel statistical
9
The Editor’s Page
methods such as multivariate and propensity analysis may partially
account for confounding variables, results from registries must be
interpreted with more caution.
7.
Take-home message
8.
What is the take-home message of these statements? We should
be aware of what we say and what words we use to describe
which propositions. Only generally accepted definitions will allow
us to communicate results properly, and, hence, we should
adhere to it. And what we cannot speak about, as Ludwig Wittgenstein stated at the end of his Tractatus Logico-Philisophicus, we must
pass over in silence.17
9.
References
1.
2.
3.
4.
Wittgenstein L. Tractatus Logico-Philosophicus. New York: Routledge; 2005. p5.
Lüscher TF. Good scientific publishing. Eur Heart J 2012;33:557 –561.
Braunwald E. The rise of cardiovascular medicine. Eur Heart J 2012;33:838–845.
Kuhn TS. The Structure of Scientific Revolutions. 3rd ed. Chicago: The University of
Chicago Press; 1996.
5. Lind J. A treatise of the scurvy. Nutr Rev 1983;41:155 –157.
6. Winnik SH, Raptis DA, Walker JH, Hasun M, Speer T, Clavien P-A, Komajda M,
Bax JJ, Tandera M, Fox K, Van De Werf F, Mundow C, Lüscher TF,
Ruschitzka F, Matter CM. From abstract to impact in cardiovascular research:
10.
11.
12.
13.
14.
15.
16.
17.
factors predicting scientific quality. Eur Heart J. Advance Access published June
5, 2012, doi: 10.1093/eurheartj/ehs113.
Nikolai Anitschkov N. A history of experimentation on arterial atherosclerosis in
animals. In: Blumenthal HT, ed. Cowdry’s Atherosclerosis. A Survey of the Problem.
Springfield, IL: Charles C. Thomas; 1933. 21 –44.
Dawber TR, Meadors Gilcin F., Moore FE. Epidemiological approaches to
heart disease: the Framingham Study. Am J Publ Health Nations Health 1951;41:
279 –286.
Editors of the Heart Group Journals. Statement on matching language to the type
of evidence used in describing observational studies vs. randomized trials. Eur
Heart J 2013;34:20 –21.
Oliver M. Doubts about prevention coronary heart disease. BMJ 1992;304:
3939 –3940.
Brown MS, Goldstein JL. A receptor-mediated pathway for cholesterol homeostasis. Science 1986;232:34 –47.
Endo A. Biological and pharmacological activity of inhibitors of 3-hydroxy3-methylglutaryl coenzyme A reductase. Trends Biochem Sci 1981;6:10 –13.
The 4S investigators. Baseline serum cholesterol and treatment effect in the Scandinavian Simvastatin Survival Study (4S). Lancet 1995;345:1274 –1275.
Cholesterol Treatment Trialists’ (CTT) Collaboration. Efficacy and safety of
more intensive lowering of LDL cholesterol: a meta-analysis of data from
170 000 participants in 26 randomized trials. Lancet 2010;376:1670 –1681.
Lüscher TF, Gersh B, Hendricks G, Landmesser U, Ruschitzka F, Wijns W. The
best of European Heart Journal: looking back with pride. Eur Heart J 2012;33:
1161 –1171.
Sies H. A new parameter for sex education. Nature 1988;332:495.
Wittgenstein L. Tractatus Logico-Philosophicus. New York: Routledge; 2005. p89.