Title: Explaining risk and study design
Article: » print
20 April 2007
Publication of the results of the Women’s Health Initiative
(WHI) and Million Women Study (MWS) since 2002 have led to considerable uncertainties
about the role of hormone replacement therapy (HRT) among health professionals
and women. This fact sheet will discuss how to explain risk and will describe
different types of study design.
Relative risk, absolute risk, attributable risk
Patients, the media and health professionals often confuse the terms “relative
risk”, “absolute risk” and “attributable risk”.
An understanding of the precise definitions of these terms is important in
order to judge the actual magnitude of risks involved. Epidemiological data
that examine the risk of a disease often report “relative risk” statistics
to determine statistical significance. In other words, they report the risks
run by a patient on a treatment relative to the risks run by a patient taking
no treatment. This method provides substantial statistical power to detect
effects of these agents, which might be quite small in magnitude. However it
does not take into account the actual frequency of the condition in the untreated
group. For example, a relative risk of 2 – often reported in the press
as “a doubling of risk” – could describe something that increases
the risk of a disease from one in a million to two in a million or something
that increases the risk of a disease from four people in 10 to eight people
in 10. Thus “absolute risk” and “attributable risk” which
take into account the frequency of the condition are better methods of presenting
Relative risk is defined as the rate of disease among the treated group
divided by the rate of the disease among the untreated group.
Absolute risk is determined by multiplying the usual rate of the condition
in the untreated group by the relative risk.
Attributable risk is an absolute measure of the excess risk attributed
to treatment. It is calculated as the difference in risk of a particular
condition between those who are treated and those who are not.
Hazard ratio and odds ratio
Risk also can be expressed as hazard and odds ratios. Hazard ratios (HR) are
broadly equivalent to relative risk and are useful when the risk is not constant
with respect to time. They use information collected at different times and
were used in the publications from the WHI studies. The term typically is
used in the context of survival over time. If the HR is 0.5, the relative
risk of dying in one group is half the risk of dying in the other group.
The odds ratio is the odds of an event happening in the treated
group expressed as a proportion of the odds of an event happening in the untreated
group. When events are rare, the OR is analogous to the relative risk (RR),
but as event rates increase, the OR and RR diverge.
Designs of clinical trials
Primary and secondary prevention trials
Primary prevention trials are those undertaken in healthy people, whereas secondary
prevention trials involve participants with established medical conditions,
such as cardiovascular disease and osteoporosis. It is important to distinguish
between these two types of trials, as the responses may differ. For example,
in women with cardiovascular disease, an endothelium with established atherosclerotic
plaques is likely to respond differently from one without such plaques.
Randomized trials and cohort and case-control studies
Randomized controlled trials (RCTs) are considered the best method for providing
evidence on efficacy of an intervention. A perfectly randomized method to allocate
participants to the study groups does not, however, protect an RCT from selection
bias. Participants may not be typical of the whole population. In addition,
differences may still exist between the groups studied – for example,
in the number of smokers or types of drugs taken – and these can influence
outcome. Randomized controlled trials, even if perfectly designed, can tell
us which treatment is better, but they cannot tell us for whom it is better.
How and whether to generalize the results of a single trial to an individual
patient is one of the most complex issues in health care. The findings that
relate to a single drug treatment in a particular population thus cannot necessarily
be extrapolated to all people. For example, the results of the WHI studies
of HRT undertaken in women older than 50 years cannot be applied to women with
a premature menopause.
In addition, RCTs tend to be short-term trials, and some interventions
may take several years to have an effect. Also the behaviour of volunteer patients
in trials may differ from those treated among the general public. Some of these
problems can be overcome by cohort studies.
Cohort studies can be thought of as natural experiments in which outcomes are
measured in the real world rather than in experimental settings. They can
evaluate large groups of diverse people, follow them for long periods and
provide information on a range of outcomes, including rare adverse events.
The promise of cohort studies as a useful source of evidence needs to be
balanced, however, against concerns about the validity of that evidence.
Cohort studies are similar to randomized controlled trials in that they compare
outcomes in groups that did and did not receive an intervention. The main
difference is that allocation of individuals is not by chance, so cohort
studies are vulnerable to selection bias, which leads to criticism of the “healthy
user” effect, in which people with innately lower risks of an endpoint
(such as myocardial infarction) as a result of good dietary and exercise
habits may preferentially take the intervention under study – which
then falsely gains credit for a favourable outcome. In cohort studies, therefore,
factors that determine whether a person receives the intervention could result
in the groups differing in factors related to the outcome – because
people are selected preferentially to receive one treatment or because of
choices they made. These baseline differences in prognosis could confound
assessment of the effect of the intervention.
In a case-control study, patients with a particular disease or condition (cases)
are identified and “matched” with controls (patients with some
other disease, the general population, neighbours or relatives). Data then
are collected (for example, by examining these people’s medical records
or asking them to recall their own history) about past exposure to a possible
causal agent for the disease. Just as in cohort studies, case–control
studies generally are concerned with the aetiology of a disease rather than
its treatment. They lie lower down the hierarchy of evidence, but this design
usually is the only practical option when studying rare conditions.
All observational studies, be they case–control or cohort
in design, cannot prove causality – only association.
Women’s Health Initiative and Million Women Studies
Women’s Health Initiative
The WHI is a large and complex clinical series of investigations of strategies
for the prevention and control of some of the most common causes of morbidity
and mortality among postmenopausal women, including cancer, cardiovascular
disease and osteoporotic fractures. It was initiated in 1992, with a planned
completion date of 2007. Postmenopausal women ranging in age from 50 to 79
years were enrolled at one of 40 clinical centres in the US into a clinical
trial (CT) or observational study (OS). The CT was designed to allow randomized
controlled evaluation of three distinct interventions.
- HRT (unopposed and combined) – hypothesized to reduce the risk of
coronary heart disease (CHD) and other cardiovascular diseases and, secondarily,
to reduce the risk of hip and other fractures, with increased risk of breast
cancer being studied as a possible adverse outcome
- low-fat eating pattern – hypothesized to prevent breast cancer and
colorectal cancer and, secondarily, to prevent CHD
- supplementation with calcium and vitamin D – hypothesized to prevent
hip fractures and, secondarily, to prevent other fractures and colorectal
In the CT, the mean age of the women was 63 years.
The cohort of the OS comprised clinical trial screenees who were
ineligible or unwilling to participate in the CT. The major clinical outcomes
of interest in the OS are CHD, stroke, breast cancer, colorectal cancer, osteoporotic
fractures, diabetes and total mortality.
Million Women Study
The MWS is an observational study that has evaluated the risk of breast cancer
with respect to differences in HRT regimen and routes of administration (with
the exception of vaginal preparations). Women invited to attend the NHS Breast
Screening Programme (NHSBSP) were sent a self-administered questionnaire
that asked them to document details about personal medical history and lifestyle
factors, including the use of HRT. The study data were recorded from these
questionnaires (which were returned before initial mammography), and women
were followed to determine the incidence of cancer and death. A total of
1084,110 women were recruited between 1996 and 2001; about half had ever
used HRT. The average duration of follow up was 2.6 years. Several publications
have questioned its design, analysis and conclusions, and a selection of
comments is given below.
- The study reported a lower risk of breast cancer for perimenopausal and
postmenopausal women than premenopausal women, despite the well-established
fact that the risk of breast cancer increases with age.
- Many differences were present when women who used and did not use HRT were
compared, and this required multiple adjustments.
- Use or non-use of HRT was established only at study entry and changes were
not recorded during follow up. Lack of prospective follow up of exposure
to HRT means that uncertainty exists as to whether women switched preparations
or started or stopped HRT during the study’s follow-up period.
- Validation of the questionnaire data was based on information obtained
from only 570 women. Curiously, although the risk of endometrial cancer with
unopposed oestrogen is well established, 14,024 non-hysterectomized women
were documented as having taken HRT that contained oestrogen alone.
- Mortality from breast cancer was assessed after an average of 4.1 years
of follow up and on the basis of a total of 517 deaths; however, breast cancer
was diagnosed very rapidly, after a mean of 1.2 years, and deaths occurred
swiftly (within an average of 1.7 years). This can be attributed to an underestimation
of the total duration of exposure to HRT, as the risks presented were estimated
on the basis of the use of HRT at recruitment. The study investigators did
not adjust the total duration of use to account for the likely continued
use of HRT in the period between recruitment and diagnosis of cancer (that
is, a mean of 1.2 years). Current users and past users of HRT were compared
with never users, and, although the risk of mortality was increased, it was
not significant (RR 1.22, 95% confidence interval 1.00 to 1.48).
This finding was highlighted because it differed from consistent reports
in the literature over a decade that women who take hormones have better
survival rates. The MWS calculated the risk of mortality by dividing deaths
from breast cancer by the total number of women who used HRT or those who
did not. If the risk is recalculated by dividing deaths from breast cancer
by the total number of cases of breast cancer in women who did and did not
use HRT, the results agree with the literature – the risk of mortality
was reduced by about 27% in the women who took hormones.
- The higher estimates of risk reported compared with those from the randomized
WHI study – especially the oestrogen alone arm, which found a reduced
risk – probably reflects the observational nature of the MWS and suggests
that the latter study probably grossly overestimated the risk of breast cancer.
- The data provided probably are representative of about 25% of all women
aged 50–64 years in the UK (on the basis of uptake for the first prevalent
NHSBSP round of 75%, completion of the MWS’ questionnaire by 50% of
attendees and the number of screening centres in the UK that participated
in the study (66/94)). Differences between women who did and did not attend
the NHSBSP and between attendees who agreed – or declined – to
participate in the study cannot easily be controlled for.
Rees M, Purdie DW. Management of the Menopause. The Handbook.
4th ed. 2006 RSM press.
Whilst great care has been taken to ensure the accuracy of information contained
in the fact sheets, the authors and the BMS cannot accept any responsibility
for any errors omissions, mis-statements or mistakes or for any loss or damage
arising from actions or decisions based on information contained in this publication.
Ultimate responsibility for the treatment of patients and interpretation of
published material lies with the medical practitioner. The opinions expressed
are those of the authors, not necessarily those of the BMS. The inclusion in
the publication of material relating to a particular product, method or technique
does not amount to an endorsement of its value or quality, or of claims made
by its manufacturer.
Margaret Rees and Sally Hope January 2008
« go back
Scientific papers, charts, presentations etc are available in the members
area. » Join here