The evolving attitude towards HT, from a treatment many believed unethical not to prescribe to post-menopausal women to one associated with negligible benefit and moderate risk, is a good example of how scientific thinking about a drug may change over time.
DISCUSSION
The
evolving attitude towards HT, from a treatment many believed unethical not to prescribe to post-menopausal
women to one associated with negligible benefit and moderate risk, is a good
example of how scientific thinking about a drug may change over time. The HT
debate illustrates the various scientific meth-ods used to understand drug
safety and how each can either increase understanding or produce confusion.
While it is difficult to make decisions on HT use now because of uncertainty,
the evolution of knowledge about HT provides a good example of current thinking
about the tradeoffs of using data from observational studies or clinical trials
to understand the population impact of drug treatment. Some of these principles
are discussed below using examples from the study of HT.
Despite
their strengths, which make them valuable tools in attempting to determine
relationships between drugs and outcomes, observational epidemiologic studies
have a number of limitations. These limita-tions are a large part of the reason
that clinical trials remain the gold standard for evaluating drug-outcome
relationships.
A
major concern with observational studies is that they are not randomized and
treatment may well vary according to characteristics linked to the disease
process. This could occur through selective prescribing or through issues
related to medical care access. Confounding by demographics, socio-economic
status, and variables related to health, as described previously, can be a
substantial problem in observational studies.
A
second problem with observational epidemiology studies, especially the larger
ones, is that they tend to have less robust ways of evaluating endpoints than
clinical trials, relying on self-report or simple clin-ical reports, rather
than a methodical AE reporting system. Short-term effects of treatment may be
partic-ularly difficult to ‘capture’ in observational settings. There may also
be inconsistent endpoint definitions between studies, making comparability
difficult. This problem may have contributed to the divergent esti-mates of CHD
in women taking HT in the NHS and Framingham studies, which defined CHD
differently.
In
addition to problems ascertaining outcomes, observational studies also
frequently have poor or limited characterization of health status or lifestyle
factors, particularly those that change over time. For example,
over-the-counter medications that can affect outcomes are not always
ascertained and variables such as physical activity levels and diet are often
not measured as often or with as much precision as would be desirable. Because
of potential differences in these factors between those prescribed and those
not prescribed drugs, residual confounding is likely to be present in
observational studies. If some of the rele-vant confounding variables are
measured at baseline (and, if possible, throughout the study), adjustment for
some confounding is certainly possible, but residual confounding remains
likely.
Another
potential limitation of observational studies is assessment of drug exposure, in
terms of both dose and duration. The duration of use of a drug is some-times
poorly defined in observational studies. Often treatment use is measured at the
beginning of the study or only at irregular periods throughout the study, and
constant use is assumed, whether this is valid or not. Observational studies
often have poor information on the dose or particular formulation of a drug
that is being used. Strategies, including having patients bring all of their
medicines with them to intake visits, have been developed to help with this
problem, but many studies, particularly those that are survey-based, have
limitations related to exposure assessment. Clinical trials, on the other hand,
frequently employ systems such as pill counts or blood level monitoring that
allow researchers to monitor actual dose received on an ongoing basis.
Finally,
in observational studies, particularly cross-sectional, case-control and
prevalence studies, it is often not possible to establish a temporal
relation-ship between drug and disease, which is crucial to establishing
cause-and-effect relationships, rather than simple associations. This
limitation can impede inter-pretation, such as when a drug improves survival
with a condition or increases its latency period, both bene-fits, rather than
causing the condition itself.
As
shown by some of the analyses from the WHI, confounding can be a problem even
in clinical trials, especially when the blind is imperfect. This can lead to
some problems of differential follow-up and ascertain-ment, but these are
usually less prominent than those seen in observational epidemiologic studies.
Critics cite this as a potential flaw of the WHI that may, in addition to other
factors (such as the age structure of the population the trial was conducted
in), have biased the results.
Though
the WHI looked at hard outcomes, many clinical trials use surrogates as their
primary outcomes of interest. This can cast doubt about whether the results of
such trials are clinically meaningful. By contrast, observational epidemiologic
studies can, and usually do, look at ‘real’ events (such as MI) rather than
their surrogates (e.g., cholesterol). This is due in part to the fact that,
unlike clinical trials, they can be retrospective (mitigating the need for
costly follow-up) or long-term prospective follow-up of a large-scale cohort
may be feasible.
The
WHI, which looked at actual events in a large population of women over a long
time period, had many of the advantages of a large-scale prospective follow-up
usually associated with observational stud-ies rather than with clinical
trials, but duration of follow-up tended to be shorter than in many
observa-tional studies. However, some of the earlier, smaller clinical trials
that form an important part of the evidence base about the risks and benefits
of HT used surrogate endpoints and were limited to very short-term follow-up.
Thus, the duration of obser-vational studies is frequently longer than is
feasible for clinical trials, which allows evaluation of ‘hard’ outcomes
instead of surrogates and of rare or time-delayed effects. Part of the
controversy following the results of the early, short-term randomized
controlled trials of HT stemmed from their short duration (espe-cially compared
to some of the observational studies) and, in some trials, use of surrogate
markers rather than clinical disease states for some outcomes.
Another
strength is that observational studies occur in ‘real life’, using drugs in the
particular dose and schedule used by patients in the field. This may more
appropriately represent usage patterns than more controlled studies. One
criticism of the WHI is that only one combination of oestrogen and progestin
was evaluated, though other doses and formulations exist. Arguably, the effects
of a drug, in terms of both risks and benefits, may vary by the dose, duration
of expo-sure and route of administration, as well as the demo-graphics and
health status of those treated. Thus, an observational study may be better
equipped to eval-uate several factors that are relevant to usage of the drug in
‘real life’.
Finally,
because of their decreased demands in terms of cost, observational studies,
particularly large simple studies, often allow for larger sample sizes and
longer duration of follow-up than clinical trials. Although some consider
observational studies more ‘cost-effective’, tradeoffs related to confounding
and selection biases must be given careful consideration, as discussed above.
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