Disinformation threatens to overpower medical reasoning. From year to
year medicine becomes more and more complex and splits into many sub-specialties
which focus on diseases while tending to ignore the patient himself. Amidst
this schism epidemiology thrives. Surrounded by an aura of genuine science it
seems to provide the desired unifying principle for medicine. Yet a closer look
at its basic premises reveals the opposite. Epidemiology is in a state of
a profound confusion (1-4) that is still unnoticed by the medical establishment
which regards epidemiology as its oracle.
Take the prestigious topic of smoking and cancer (4). Obviously in heavy smokers
lung cancer is more prevalent than in non smokers; yet epidemiology lacks the
means to prove that smoking causes cancer. At best it can state that lung
cancer is associated or correlated with smoking. However an association
between two variables has at least three interpretations: either smoking
initiates cancer, or cancer triggers an urge to smoke, or the two may never
interact and their observed association results from a third process that was
not considered in the study. Epidemiology is incapable of distinguishing between
the three. The conclusion is in the hands of medicine. In order to distinguish
between them epidemiology should consider all factors that might contribute
to an association between smoking an cancer, e.g., patient's history and mental
state, clinical check-up, post-mortem reports etc. Instead of considering the
relationship between smoking and cancer in its entire complexity, epidemiology
focuses on a small number of variables, dismissing the rest as negligible, which
is unfortunate since for the individual patient nothing is negligible.
The same approach underlies many epidemiological studies, particularly clinical
trials, that involve simplifications and presumptions which breed false conclusions
and should be regarded by the medical community with suspicion. As long as epidemiological
statements do not contradict medical experience the harm to the patient may
be small since they can always be corroborated by clinical observation. Yet
epidemiology threatens to impose its deceptive reasoning on medical issues that
are far less obvious, e.g., cancer treatment which today is directed by clinical
trials.
From the viewpoint of medicine most of the basic premises of epidemiology are
wrong. For instance, in order to apply parametric-multivariate models to medical
phenomena, the variables have to be distributed normally and their variances
equal. This requirement is seldom met. The organism is extremely complex, all
its components interact, and none is distributed normally. Epidemiology assumes
that the variables can be transformed so as to be distributed normally, which
is generally incorrect. Since many distributions are skewed it appears as if
they can be normalized by the log-normal transformation. In many cases the distribution
becomes symmetric, yet this apparently harmless transformation changes the meaning
of the variables. While in the normal distribution they are independent, in
the log-normal they become proportional. Instead of testing the variables in
their native form, epidemiology distorts them and ignores the consequences.
Thus, although epidemiological tests are mathematically consistent, they
do not meet the basic requirements that are necessary for applying them to medicine.
This is the essence of the confusion in epidemiology. They stun medicine with
the consistency of their mathematics and hide the fact that most models are
irrelevant. This is also the nature of epidemiological disinformation, since
most epidemiological statements are neither true nor false. Epidemiological
disinformation is a manifestation of iatrogenesis, particularly since it aims
to direct patient treatment. It is therefore hazardous to the patient. Generally,
statistical analyses on a small number of variables involving traditional tests,
e.g., t-tests, chi square etc, are still acceptable. As a rule of thumb, it
is advisable to ignore epidemiological statements based on observations involving
more than five variables, particularly if contradicting medical intuition. This
applies also to clinical trials and meta-analyses.
Epidemiology gained its name and glory from the study of epidemics. Now that
epidemics are rare, its mission is nearly accomplished, and epidemiology should
therefore vanish.
G. Zajicek
References
1 Zajicek G. Progress against cancer. are we winning the war? Cancer J. 3:2,1990
2 Zajicek G. Cancer wars. Cancer J. 4:4-5,1991
3 Zajicek G. Meta-analysis and chaos Cancer J. 4: 152- 153, 1991
4 Zajicek G. To smoke or not to smoke? Cancer J. 5: 70, 1992