
Required for next week

  1. Choice(s) of essay topics due next week.
  2.  No new reading for next week. Please have another look at the second
     hand smoke papers, and the cheating papers.

Some notes on the smoking video

(Program Tape 11 from Against All Odds)

Prospective and retrospective studies

A distinction is made in the video between prospective and retrospective
studies. A retrospective study identifies a group of people with a disease
(or other outcome), and tries to ascertain potential risk factors in
retrospect. This is usually done by identifying another group of people who
do not have the disease in question, and comparing these two groups on their
exposure to a possible risk factor. In medical applications, this type of
study is often called a case-control study: the cases are the people with
the disease, and the controls are the disease-free comparison group. For
example, one study of the effect of second-hand smoke on spouses ([ JAMA]),
identified 653 non-smoking women with lung cancer, and collected data on how
many of these were married to smokers. They identified a further group of
1,253 non-smoking women without lung cancer, and also collected data on how
many of these were married to smokers. A prospective study identifies a
group of healthy people and follows them over time, to ascertain who gets
the disease and who doesn't, and then compares these two groups on their
potential risk factors. In medical applications a prospective study is often
called a cohort study. The smoking video referred to early evidence from
retrospective studies being confirmed in a large prospective study.

(An opinion poll or other type of survey is more like a prospective study,
although the data from particular individuals is usually only collected at
one time point.)

A major disadvantage of a case-control study is that the controls are
usually chosen by convenience. Very often the controls are patients in the
same hospital, who have been hospitalized for a condition unrelated to the
disease under study. Thus there is no guarantee that the controls are really
comparable to the cases. In a prospective study, effort is usually made to
measure many variables potentially related to the disease, so that the
comparison can be fine-tuned at the end of the study. Another disadvantage
of a case-control study is that people are asked about their exposure to a
risk factor in retrospect, and this can provide quite unreliable data. Both
these criticisms were made of the initial studies suggesting a link between
smoking and lung cancer, and both these criticisms are made by Gross in his
article about second-hand smoke (last week's reading).

A major disadvantage of prospective studies is that it is necessary to
follow a very large group of people over a long period of time, especially
when investigating rare diseases or diseases that take a long time to
appear. This is not only expensive, it is also very difficult to get
complete data, and biases can result if loss to followup is related to the
outcome of interest.

Both prospective and retrospective studies are observational studies, as
opposed to experiments. Experiments require active intervention on the part
of the researchers, something often not possible in medical research or
other research involving human subjects.

Confounding variables

All observational studies can potentially be skewed by confounding
variables. These are variables that are not of primary interest, and may not
even be measured, but are correlated with the response of interest. For
example, in the smoking video, the possibility was mentioned that alcohol
consumption and lung cancer incidence were associated. Since we might also
expect that smoking and alcohol consumption are related, the observed
increase in lung cancer among smokers might only reflect the association of
lung cancer and alcohol consumption.

In the polling for the Quebec referendum, potential confounding variables
that were mentioned (and adjusted for when allocating the undecideds)
included gender, age, and first language.

In observational studies effort is usually made to identify all possible
confounding variables, and adjust for them in the analysis of the data. But
it is impossible to adjust for confounding variables that no one has thought
of yet.

Criteria for causality

It can be argued that observational studies can never establish a causal
relationship between two variables, such as smoking and lung cancer: that
causality can only be established by experimentation involving direct
intervention. However, the science of epidemiology, which studies various
aspects of public health, deals almost exclusively with observational
studies, and as a result have identified a series of criteria for deciding
that a causal relationship is very likely. In fact, these criteria were
originally developed by Sir Richard Doll in connection with studies on lung
cancer and smoking in Britain in the fifties. The five criteria mentioned on
the video are:

   *  consistency of the association
   *  strength of the association
   *  specificity of the association
   *  temporal relationship between potential cause and effect
   *  coherence of the association

Simpson's paradox

A particularly intriguing type of confounding occurs when a confounding
variable, once exposed, completely turns around the observed association.
Here is an example, from [ Rad], on the relationship between race and the
imposition of the death penalty for convicted first-degree murderers.

race of         death penalty   death penalty
defendant       imposed         not imposed     percentage
----------------------------------------------------------
white           19              141             11.88%
black           17              149             10.24%

The imposition of the death penalty is about the same rate for white and
black defendants, in fact, slightly higher for white defendants. However,
when the race of the victim is taken into account, a quite different picture
emerges:

                        white victim

race of         death penalty   death penalty
defendant       imposed         not imposed     percentage
----------------------------------------------------------
white           19              132             12.58%
black           11              52              17.46%

                        black victim

race of         death penalty   death penalty
defendant       imposed         not imposed     percentage
----------------------------------------------------------
white           0               9               0%
black           6               97              5.83%

References

JAMA
     Reported in Chance News 3.08 , J. American Medical Association, June 8,
     1994.
Rad
     Radelet, M. (1981) Racial characteristics and imposition of the death
     penalty. American Sociological Review 46, 918--927. There is a related
     article in Chance News 4.04 from the New York Times, February 24, 1995.
[]
     The book Statistics: concepts and controversies by Moore has a nice
     section on causality, smoking and cancer: Chapter 6, Section 3.

In the Globe and Mail this week

   *  ``Procedure helps disease sufferers", Nov. 24 (A10). A surgical
     procedure called palliodotomy may help sufferers of Parkinson's
     disease. It has been performed on 80 patients in the past 3 1/2 years:
     results of a study on the first 14 patients was published in the
     November 25 issue of Lancet.
   *  ``Discovery may slow heart failure", Nov. 23 (A9). A new drug for
     treating high blood pressure has been undergoing tests in several
     Canadian hospitals. An unexpected finding is that the drug appears to
     be effective for congestive heart disease: the death rate in patients
     with congestive heart failure was reduced by 45 \%. Although the result
     has yet to be reported in a medical journal, doctors have immediately
     moved into a second test using the drug specifically on patients with
     CHD.
   *  ``When the big shift in spending took place", Nov. 20 (A8). A rather
     confusing article with a really confusing graphic, arguing (I think)
     that Ottawa's share of spending has been around its current level of
     40\% fairly consistently over the past 30 years.
   *  ``Canadians clamour for illegal 'cure-all'", Nov. 18, (A1) and (A13).
     Melatonin is being advertised as a sleep aid and a potential cure for a
     range of problems. It is available as a dietary supplement in the U.S.,
     and although it is illegal to sell it in Canada, it is available by
     mail order and through some health food stores. A book is mentioned,
     rather disparagingly: The Melatonin Miracle, by W. Regelson.
   *  ``Canadian imbibing habits change", Nov. 18. "A Health Canada survey
     ... found that the number of Canadians describing themselves as
     'current drinkers' fell to 72.3 \% in 1994 from 77.7 \% in 1989... Few
     drinkers feel that their alcohol consumption has ever caused them harm;
     almost 80 \% said it had not. However 73.4\% of those surveyed said
     they had been harmed in some way at some time by another's drinking."
   *  A full page ad on page A7, Saturday, November 18 by Bristol-Myers
     Squibb, announcing that ``this week the results of a long awaited
     landmark study which measure the effect of cholesterol-lowering
     medication on 6,595 patients, were released. The outcome of this study
     conducted by the University of Glasgow, in the West of Scotland, showed
     that a specific drug was associated with an early and lasting reduction
     in the risk of a first heart attack and death. Initial effects were
     seen within six months of treatment with few side effects.'' An article
     about the study appeared in the New York Times on Nov.~16, 1995, and is
     available in Chance News 4.15 The study results were reported in that
     week's New England Journal of Medicine. From Chance News:``the study
     was supported by a grant from the Bristol--Myers Squibb Company, which
     makes pravastatin [the drug that was tested in the study] and sells in
     under the name Pravachol... an accompanying editorial [in the NEJM]
     comments that these drugs are expensive, costing about \$800 a year per
     person. The editorial suggested pursuing less expensive solutions such
     as using certain kinds of margarine that have been shown to have an
     ability to lower cholesterol"

Technical note: relative risk

The relative risk for an event or outcome, such as lung cancer, due to a
risk factor, such as smoking, is the ratio of the probability of the event,
given exposure to the risk factor to the probability of the event, given
non-exposure to the risk factor. If you like formulas:

                        Prob(event|exposure)
relative risk  =     ----------------------------
                        Prob(event|non-exposure)

If the relative risk is equal to 1, then there is no (apparent) increase in
the probability of disease, due to the risk factor. If the relative risk is
greater than 1, then exposure to the risk factor does increase the
probability of disease, and if the relative risk is less than 1, exposure
decreases the probability of disease. Of course in studies, the relative
risk can only be estimated, and there is always an associated margin of
error.

In the smoking and lung cancer studies, the relative risk for lung cancer
identified with smoking was 9, for one-pack-a-day smokers, and 30 for two
pack-a-day-smokers. In the ETS studies, the relative risk for lung cancer
identified with exposure to second-hand smoke was between 1 and 2 in most
studies, and overall was about 1.13. This means an increase of 13\% in the
probability of lung cancer due to exposure to ETS. Since the lung cancer
incidence is already very small, about 1/10,000 (?), this doesn't translate
into very many additional expected cases of lung cancer. (The EPA study
identified a relative risk of 2, which translated into an estimated 3000
additional cases of lung cancer in the U.S.; a guesstimate for Canada would
be 300, since the population is about 1/10 the size.)

Even more technical

In case-control studies, which all the ETS studies are, the relative risk
must be estimated indirectly, by the so-called odds ratio, which is the
ratio of the odds of the event, given exposure, to the odds of the event
given non-exposure:

                        odds of event|exposure
odds ratio  =  -----------------------------------
                        odds of event|non-exposure

                Prob(event|exposure)/Prob(non-event|exposure)
            =  -----------------------------------------------
                Prob(event|non-exposure)/Prob(non-event|non-exposure)

One further technical point is that the margin of error for the estimate of
relative risk is computed as a 'plus-or-minus' on the log-scale, which is
why Gross exhibits his summary of the studies this way.
