1. 1
EXPERIMENTAL EPIDEMIOLOGY
Maja Miškulin, Ivan Miškulin
1. An introduction to experimental epidemiology
Epidemiology is one of the core sciences of public health and medicine in general as well.
Unlike for example histology, which constitutes a basic area of knowledge, and for example
neurology, which is the study of a specific organ, epidemiology is a way of thinking and
methodology that can be used to learn about and to resolve a very wide range of research
questions. Every research is a process that aims to provide empirical evidence related to specific
research topic.
Every research begins by asking a research question. The basic components of every research
include the background of a research, the study design, materials of the study or study
participants, variables (data to be collected and the properties to be measured), and statistical
issues.
The research question is a key step in the design of any research and it should reveal the
purpose of the research. When formulating a research question and making the decision on
research, we need to think well about the feasibility and possibility of research implementation.
Besides that, the research question must be interesting enough, it must make new discoveries,
it must comply with the ethical principles of research, and it must be important.
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The background of the research is related to the knowledge known from the previous
research of the same problem, to the knowledge that we will gain in the specific research and
to the questions that will remain unanswered after we conduct the planned research. Thus, the
background of the research is about the possible overcoming of existing doubts about the
research topic.
After setting up a research question and a thorough description of the background of the
research, follows the decision on the study design i.e. the decision on the epidemiological
research method. This decision will depend on the purpose of the research, human and financial
resources and the time we have at our disposal. For studying illness and health, epidemiology
use special methods that are common to majority of scientific researches within the area of
biomedicine and health. These methods can be classified into the observational epidemiological
methods (non-experimental) and experimental epidemiological methods (intervention) given
the main approach. In observational epidemiology, the subjects are only observed and recorded,
for example, a disease or death according to the characteristics of the population, without
affecting the course of the disease and the usual treatment. On the other hand, in an experimental
epidemiology, the researcher actively participates in the process being investigated, i.e.
exposing the subjects to certain factors whose protective activity is being investigated, whereby
according to ethical principles in epidemiological research these factors can be exclusively
protective. All epidemiological research methods are shown in Figure 1.
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Figure 1. Epidemiological research methods.
The observational epidemiology can be divided into the descriptive epidemiology and
analytical epidemiology. The descriptive epidemiology deals with the description of an event
in the population as to who, where and when it is ill. Thus, descriptive epidemiology describes
the event of an illness, accident, or other health problem to the person-place-time variables, and
this is also the first step in the research of any event in the population. The results of descriptive
logyEpidemio
vationalObser
miologyEpide
Descriptive
Epidemiology
Analytical
Epidemiology
udyCohort St
Case- rolcont
Study
Cross-sectional
Study
Ecologic al
Study
Experimental
Epidemiology
Randomized
Controlled Trial
Controlled
Field Trial
Community
Trial
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epidemiology serve to set hypotheses on possible causes of the disease, which is confirmed or
disputed by the methods of analytical epidemiology.
The analytical epidemiology deals with the investigation of the cause or risk of an illness, i.e.
examines the relationship between exposure to risk factors and illnesses, and responds to the
question of why someone is ill. Methods of analytical epidemiology are commonly used after
descriptive epidemiology has described the occurrence of disease in the population and when
we want to know the reasons why some populations suffer from certain diseases. We use special
study methods such as cohort study, case-control study and crosssectional study. Each of these
study methods has its own specifics as well as advantages and disadvantages. Given the moment
in the time of the health outcome and the exposure we investigate, we differentiate longitudinal
and cross-sectional analytical research. In the longitudinal type of research, there is a certain
period of time between these two events and we use this approach in cohort study and case-
control study. On the other hand, in a cross-sectional study, exposure data and health outcomes
are collected at the same time. In addition, there is still a division of research into data collection
for individual subjects (cohort study, case-control study and cross-sectional study) and so-called
aggregated data i.e. data for groups of subjects. In the last case, we are talking about ecological
study. The problem with this type of study is the so-called ecological fallacy, which is one form
of deviation that leads to a systemic error in the research. Ecological fallacy appears when one
concludes about causal connection between individual subjects from the results of ecological
study.
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Methods of experimental epidemiology can be applied once we have responded to basic
epidemiological questions with descriptive and analytical epidemiology (who, where, when and
why they are ill). In the experimental epidemiology, we include a randomized clinical trial, a
controlled field trial, and a community experiment. The decision on observational or
experimental approaches to research will primarily depend on the factor we are investigating.
The advantage of observational research is the ability to apply it for evaluation of any exposure,
protective or harmful, after the subjects are exposed, irrespective of the researcher's
interventions.
Once we have decided for one of the research methods, the decision on the study subjects’ is
following. It is therefore important to determine how the study subjects will be selected
(inclusion and exclusion criteria) as well as how we will collect the sample i.e. what sampling
method we will choose.
The decision on research variables i.e. the decision on the data we collect and the way
we do it will depend on the research question and the research method. When deciding on the
variables, which we are going to use, we need to distinguish outcome variables, predictor
variables, and confounding variables. Outcome variables in epidemiological studies include
disease (its existence or absence), but also recovery, improvement of clinical symptoms, injury,
death and others. Predictor variables are most often exposure (or inexposure) to the investigated
risk factor, and confounding variables are related to confounding factors, most commonly age,
sex, socioeconomic status, etc.
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Finally, after we have designed the previously described parts of research one needs to
answer statistical issues such as sample size, and the selection of appropriate statistical methods
for data analysis.
References
Bailey S, Handu D. Introduction to Epidemiologic Research Methods in Public Health Practice,
1st edition. Burlington: Jones & Bartlett Learning, 2012.
Haynes B. Forming research questions. In: Haynes RB, Sackett DL, Guyatt GH, Tugwell P.
(eds.) Clinical Epidemiology – How to Do Clinical Practice Research, 3rd edition. Philadelphia:
Lippincott Williams & Wilkins, 2006; pp 3 – 14.
Rothman KJ. Epidemiology: An Introduction, 2nd edition. Oxford: Oxford University Press,
2012.
Detels R. Epidemiology: the foundation of public health. In: Detels R, Gullford M, Karim QA,
7. 7
Tan CC. (eds.) Oxford Textbook of Global Public Health, 6th edition. Oxford: Oxford
University Press, 2015; pp 403 – 410.
Pearce N. Classification of epidemiologic study designs. Int J Epidemiol. 2012; 41: 393 – 397.
2. Experimental epidemiologicalmethods
The experimental setup of research is not a novelty in medicine. There are many examples of
experiments throughout medical history that were done by famous physicians of those times.
One of them was James Lind. Lind was not the first physician who suggested that citrus fruit
can be a cure for scurvy, but he was the first to study their effect by an experiment in 1747. His
experiment was one of the first noted, controlled clinical experiment in the history of medicine.
Lind’s research included twelve subjects, all of whom slept in the same place and had the same
nutrition (during his research he taught about confounding factors). The subjects were divided
into six groups, and each group with a regular diet was given daily a nutrition supplement, such
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as cider, elixir, Indian nuts, two tablespoons of vinegar, seawater and two oranges and one
lemon. Of course, those who got orange and lemon quickly recovered from scurvy.
Experimental studies are quite different from cohort studies because the researcher who
performs such study is the one who makes the decision about subjects that will be exposed to
the investigated factor based on the specific design rules that are employed such as
randomization, matching, etc. Because of that, confounding factors such as choice that may
have led to the subjects being exposed in the cohort studies are usually not a problem in
experimental studies. Due to the fact that epidemiologists usually study human populations,
there are few possibilities for a researcher to intentionally expose subjects to a suspected factor.
However, experimental studies are largely used in basic medical sciences such as physiology,
pathophysiology, medical biology and pharmacology where investigators design researches on
animal models.
In contrast to observational epidemiological studies, in experimental studies, the investigator
has "control" over the protective factor that is being investigated, i.e. the investigator determines
which of the subjects will get a drug that is being investigated, and who does not (the control
group gets either placebo or the best existing drug on the market – so called gold standard). The
best way to classify subjects in the investigated groups (exposed to investigated drug and
unexposed) is randomization, which indicates the random distribution of the subjects in the
groups. Randomization is primarily used to eliminate the effects of confounding factors.
Following such possibility, experimental studies achieve higher probability of accuracy of the
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results compared to observational studies, because it is less likely to occur deviation and/or
misunderstand. However, randomization is not required in
experimental studies, although it is desirable to carry it out.
When we use experimental studies in epidemiology, we can get very strong evidence.
Namely, intervention studies of randomly assigned subjects or group of subjects to participate
or not to participate in an intervention program that demonstrates a subsequent decrease in a
specific health outcome in the intervention group do provide powerful evidence, almost a proof,
of a causality. Because of serious consequences due to application of an intervention that may
change the biological status of a subject or the sociopolitical behavior of a group of subjects,
intervention studies should not be implemented until the probability of a causal or risk
relationship has been well determined using the other types of study designs.
There are several types of experimental studies, considering who the study subjects are.
These are randomized controlled trial (RCT), controlled field trial (CFT) and community trial
(CT). The main goal of randomized controlled trial is to evaluate the therapeutic approach to
the patients who are included in the study individually. This is the most common approach
although the study subjects can also be healthy individuals when it comes to researching a
measure of primary prevention of the disease. In randomized controlled trial, we can investigate
the effect of drugs, surgical procedures, certain physical therapeutic methods and other
therapeutic approaches. In controlled field trial we want to estimate the effect of preventive
intervention most commonly on healthy subjects, which are included in the study individually.
This type of study was mostly used to prove the efficacy of the vaccine. Unlike the
10. 10
abovementioned experimental studies, community trial serves as tool for evaluation of
preventive intervention on a group of subjects. Within this chapter, controlled field trial and
community trial will be described in detail, while randomized controlled trial will be described
in separate chapter due to its relevance to basic medical sciences.
Controlled field trial was most frequently applied when investigating the efficacy of a
vaccine. However, controlled field trial can also be used for investigating other preventive
measures, such as exploring access to the prevention of sexually transmitted diseases, suicide
prevention, smoking cessation interventions, etc. Unlike randomized controlled trial, controlled
field trial most commonly includes healthy subjects, and sampling is carried out from the
population. In the case of investigation on the efficacy of the vaccine, it is related to inclusion
of subjects who, most probably, did not come into contact with the cause of the contagious
disease against which the vaccine is being explored, which means that subjects are most
commonly children. After defining the inclusion and exclusion criteria of the study subjects,
one should carry out the sampling process. Vaccine efficacy study requires a fairly large sample
and often includes several thousands of study subjects. In addition to the efficacy of the vaccine,
it is also important to investigate all side effects associated with the use of active substance,
which may be live attenuated vaccine, inactivated vaccine, subunit vaccine and toxoid vaccine.
When investigating the efficacy and safety of the vaccine, we need to divide the healthy subjects
into two groups, one that will get the active substance (exposed group) and the other who will
be given placebo (unexposed group). The randomization is the best way to achieve such
division. After the division of the subjects into the groups, the application of the active substance
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and the placebo follows, so that the placebo should be applied in exactly the same way, at the
same dose and at the same time, and must have the same color, as well as the same smell and
the taste. In this type of experimental study, we can show results in several ways, such as relative
risk, survival curves and effectiveness of the investigated vaccine or other preventive procedure.
In addition, based on the results of the controlled field trial, we can, as well, calculate population
preventable fraction (PPF), which tells us about the proportion of newly diagnosed cases of the
disease that can be prevented at the population level if we apply a preventative measure in that
population. The formula for population preventable fraction (PPF) calculation is as follows:
p – the proportion of the population that is exposed to the protective factor;
RR – relative risk.
The community trial is a type of experimental study that involves at least two whole
communities, one exposed and the other unexposed. Namely, some of the protective factors
cannot be investigated on individuals because all inhabitants of a particular geographic area are
exposed to such factors. These factors can be a better air quality, better water quality or better
health care. In this case, all inhabitants of a geographic area that is exposed to a protective factor
are included in the study, and as a control group all inhabitants of another geographic area,
where such a factor is lacking. One of the best known community trials began in 1944 in the
United States, and that was a study of the effect of water fluorination on health of the teeth in
children.
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In addition to the above mentioned types of experimental studies, one should also
mention the natural experiment. Namely, although the name of this type of study contains the
term experiment, the natural experiment is not a type of experiment studies; this is, in fact, only
observation. The term natural experiment refers to the implementation of observational
epidemiological studies in case of unfortunate events, such as natural disasters (e.g. flood, fire
or earthquake), or accidents caused by human error and neglect (for example, Chernobyl
catastrophe and methyl-mercury poisoning in the Gulf Minamata in Japan). Besides that, there
are deliberately provoked exposures of people to harmful factors, such as nuclear bombs in
Hiroshima and bioterrorism. Therefore, in a natural experiment, the investigator does not expose
people to any of the factors, and these are the most common factors that are harmful to human
health, but in the previously mentioned circumstances, after a certain event has already
occurred, they simply conduct descriptive and analytical epidemiological studies trying to
quantify the effects of these factors on human health.
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References
Gordis L. Epidemiology, 4th edition. Philadelphia: Elsevier Sounder Inc., 2009.
Rothman KJ, Greenland S, Lash TL. Modern epidemiology, 3rd edition. Philadelphia:
Lippincott Williams & Wilkins, 2008.
Donner A. Methodological issues in the design and analysis of community intervention trials.
In: Detels R, Gullford M, Karim QA, Tan CC. (eds.) Oxford Textbook of Global Public Health,
6th edition. Oxford: Oxford University Press, 2015; pp 500 – 515.
Atienza AA, King AC. Community-based health intervention trials: An overview of
methodological issues. Epidemiol Rev. 2002; 24: 72 – 79.
Gerstman BB. Epidemiology kept simple: An introduction to classic and modern epidemiology,
2nd edition. New York: Wiley – Liss, 2003.
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3. Randomized controlled trials
The International Conference on Harmonization defines a clinical trial as: Any research in
humans expected to reveal or confirm the clinical, pharmacological, and/or other
pharmacodynamic effects of a research product(s), and/or to determine any adverse reactions
to a research product(s), and/or to study absorption, distribution, metabolism, and excretion of
a research product(s) with the aim to discover its safety and/or efficacy.
Clinical trials are needed because only rarely is the exact pattern or outcome of a disease
or condition known. Today it is not still possible to reveal all of the genetic and environmental
factors that lead to disease progression, recovery, and relapse. Furthermore, it is very rare to
have the therapy that is so effective that even with an indefinite understanding of the course of
the disease, it is possible to say, without a control group, that the therapy is clearly beneficial
and has few major adverse effects. Usually, the applied therapy, while useful, is not perfect.
Because of that, in order to determine the true balance of potential benefit and harm from a new
therapy or intervention, it is necessary to compare people who have received the therapy with
those who have not. Ideally, this comparison will be made in an unbiased manner so that, at the
end, any observed difference between those treated and those not treated is most likely due to
the therapy. It has been said that except for systematic reviews, randomized controlled trials
provide the highest level of evidence and an evidence pyramid has been developed (Figure 2.).
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Figure 2. Hierarchy of scientific evidence.
At the beginning of a controlled clinical trial, after we formulate a specific research question
to be answered in the research, we need to decide on the method of selecting the subjects. When
we investigate a substance that we think can prevent the disease, the sample will consist of
healthy subjects. Then, when deciding on inclusion and exclusion criteria for study subjects, we
need to take into account the frequency of the health outcome we are interested in. Namely, if
the investigated health outcome is a rare event in the population, then it is better to involve
Strongest
evidence
Weakest
evidence
Meta-analyses
& systematic
reviews
Randomized
controlled trials
Cohort studies
Case-control studies
Cross-sectional studies
Animal trials & in vitro studies
Case reports, opinion papers and letters
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subjects who have an increased risk of this outcome, so that we can include sufficient number
of subjects and thus prevent the increase in the research cost above the acceptable level.
Furthermore, one should consider the simplest approach in sampling, as well as the likelihood
that the subjects will adhere to the research protocol and take the substance that is assigned to
them (compliance). In addition, it is important to ensure the maximum possible number of the
subjects during the study period, in order to avoid the loss of the subjects during the follow-up
period, i.e. lost to follow-up. Cautious approach should be taken in narrowing the subjects
inclusion criteria (for example, those at high risk), as this can result in an unrepresentative
sample of subjects, which is why we will not be able to apply the results of the study to the
population, especially those at low risk for the selected health outcome. However, it is not
crucial to provide a representative sample of subjects in the implementation of the randomized
control trial, as it is assumed that the biological mechanism of the effect of the drug does not
differ with regard to whether the subjects are selected from the general population (very
demanding and expensive) or from the population of patients in hospital treatment (less
demanding and expensive). When we investigate a substance that we think can lead to cure or
improving a clinical status or improving quality of life of the patients, the sample will consist
of people who already have a diagnosed disease.
After selecting the target population (source for sampling) and sampling, randomization is
required in order to divide the subjects into at least two investigated groups, one that will be
exposed, i.e. will receive a new drug whose activity we are investigating, and the other,
unexposed or control group. An unexposed group will receive either a placebo if it is a healthy
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subject, or a gold standard, if it is a subject with illness. Namely, it is not ethically acceptable
to deny a proven effective drug or procedure to patients who need treatment and assign a
substance that has no pharmacological effect (placebo) and, in that case, we must administer
the best available drug on the market.
Randomization is a very important step in conducting controlled clinical trial. This is a process
that allows unpredictability of the distribution of subjects in the exposed group and the group
of unexposed ones, and we primarily do it because it allows us to eliminate the effect of
confounding factors. This applies even to those confounding factors that we still do not know
are confounders or factors that cannot be measured, either because of their complexity or
because of financial constraints. Thus, the goal of randomization is to achieve comparability of
a group of subjects with respect to certain significant characteristics of the subjects, i.e. we
achieve an equal distribution of all characteristics, except of the exposure to the tested drug.
Randomization can be accomplished in many ways, e.g. by using random number tables, using
sealed envelopes, drawing red or green balls, and today it is easiest to do it with the computer,
using statistical programs. Randomization can be carried out in an independent center to avoid
the possibility that researchers will "circumvent" the proper conduct of randomization. In most
large randomized controlled clinical trials, conducted in many clinical centers (multicentric
research), this is in fact the rule. Such center is responsible for conducting randomization,
coordinating the research, collecting and analyzing data.
In addition to simple randomization, there is also a stratified randomization approach, which
ensures complete comparability of subjects in groups according to very important confounding
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factors, such as age and sex. In this case, we may divide the subjects by age, for example over
the age of 50 and under 50, and then divide the two subgroups according to sex. Thus, we will
get four subgroups of subjects, and from each of them we will randomly select the same number
of subjects in the group to be exposed (the drug being investigated) and in the unexposed group
(gold standard or placebo), using the randomization procedure. After the performed stratified
randomization, regardless of the fact that we initially had a sample with an unequal distribution
of sexes and age, we would get a completely equal distribution of these characteristics in the
group of subjects exposed to the investigated drug and in the group of subjects who were not
exposed. Namely, if we perform a simple randomization, it would be possible, by chance, not
to get the same proportion of subjects according to age and sex in the group of exposed and
unexposed subjects. Thus, when the equal distribution of the subject characteristics is crucial in
the research (the confounding factors that may distort the results of the research), then stratified
randomization is better.
After we randomized the subjects to the investigated groups and the subjects started taking the
investigated drug (exposed group) or placebo / gold standard drug (unexposed group), the
monitoring of the subjects and collection of the data on the health outcome is following. Data
collection must follow a predefined protocol and must be performed equally well in both groups
of subjects in order to avoid the occurrence of a discontinuation of the diagnostic procedure.
This is ensured by using blinding, masking, which can be single, double or triple. When single
blinding occurs, only the subjects do not know in which group they had been signed into, i.e.
whether they get the investigated drug or placebo / gold standard drug is obtained. This is not
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ideal because in this case, researchers may be biased and apply different criteria when collecting
data from subjects in the control group. In a double-blind, randomized, controlled clinical trial,
neither the subjects nor the researchers who collect the data during the follow-up period of the
subjects do not know who from the subjects is in which group. When we carry out a triple blind
experiment, then with the previously mentioned participants in the study, neither the person
analyzing the data do not know which subjects are in which groups, in order to avoid
manipulating with the data during statistical processing. Obviously, the blinding can only be
done if placebo, or gold standard drug, are of the same appearance (color and shape), weight,
taste and odor as the drug being investigated. However, despite the blinding, it is possible to
have a placebo effect when the ineffective substance also improves health status as well as the
appearance of Hawthorne's effect, which is marked by the "positive" reaction of subjects
because researchers care about them. In both cases, we can get a result that underestimates the
actual effect of the drug being investigated.
Although the use of placebo has been investigated quite well, there is no single answer to
whether there is indeed a placebo effect or the way of its action. According to some findings,
there is no placebo effect, and other studies point out a particularly strong placebo effect.
Namely, it is thought that placebo-effect is only possible if the subjects do not know that they
are getting inactive substance. One research has denied that. This was a placebo-effect study in
which subjects with irritable bowel syndrome knew that they were receiving placebo and not
active substance. In this controlled randomized clinical trial, the exposed group consisted of
women who knew that they were given placebo (defined as placebo-containing capsules
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containing inactive substances, but it has also been noted that it has been proven that these
capsules lead to significant rebound symptoms through autosugestive processes), while the
control group of women did not receive any therapy. The monitoring of a group of subjects was
carried out in the same way. The results of this study have shown that placebo, even when there
is no blinding, has a positive effect, because the women who received it reported lowering the
severity of the disease symptoms and improving the quality of life (the result was marginally
statistically insignificant).
In addition to the decision on how to classify subjects in groups (most preferably
randomization) and how to conduct blinding, and how to monitor subjects (equally good for all
subjects), it is necessary to decide which health outcomes to determine or measure. This, of
course, depends on the research question and the disease we are investigating, and the outcomes
we can measure are divided into primary and secondary. The primary health outcome in
research is usually one and that is the answer to the most important part of the research question.
For example, the primary health outcome can be complete lack of illness, improving the clinical
status of the subject, improving the quality of life, five-year survival rate. The secondary
outcome may be drug side effects, but also a recurrence of the disease, functional impairment,
disability, etc.
One of the possible approaches in research in experimental epidemiology is the use of socalled
cross-over design. The basic principle of this type of design is to put the subjects in the groups
by randomization, application of the investigated drug in the exposed group and placebo / gold
standard drug in the unexposed group, and follow-up of the health outcomes over time, just as
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described in the previous sections. However, what is specific to this approach is the change in
exposure in the investigated groups and the exposed group in the second part of the research
becomes unexposed and vice versa. This change in the exposure and non-exposure status of
each subject can be accomplished after a certain amount of time has passed required for the
previously applied substance to be completely excreted from the body. This is a very valuable
approach to the research, because every subject is in the exposed and in the unexposed group,
i.e. every subject is control to itself! In this way, we completely exclude the possibility of
deviating from the inadequate selection of the subjects. However, there are some problems that
have been raised with this mode of research, and this is primarily the ability to carryover, which
is the permanent effect of the initial exposure (or non-exposure) that is misleadingly interpreted
by the effect of non-exposure (or exposure). For example, if the subjects in the first part of the
research (before the cross-over) received the investigated drug (exposed group) and he
permanently improved their health status, then in the second part of the research we can get a
false impression of the positive effect of the gold standard drug and the final result may be an
underestimate effect of the investigated drug compared to the effect of the gold standard drug.
An additional problem is order of exposure and unexposure because the placebo effect is more
pronounced at the beginning of the study, as well as the fact that this approach cannot always
be applied, e.g. when it is a surgical procedure. The cross-over design can be used to investigate
the efficacy of drugs for chronic diseases, which require continuous treatment such as
hypertension or diabetes mellitus.
22. 22
As the implementation of randomized controlled clinical trials is very expensive, there is also
the possibility of applying factorial design. By using this approach, we simultaneously
investigate the effect of multiple drugs. These drugs must inevitably have different
pharmacokinetics and their activity must be completely independent. A very important
advantage of the factorial design is the use of one sample of subjects to investigate the effect of
multiple drugs, which can save considerable amount of money and other resources. The
advantage is that during the monitoring of the subjects we can stop the exposure for one drug,
if there is a need for that, and that the second part of the research continue without interruption.
The results of a randomized controlled clinical trial can be presented in several ways. We can
calculate the relative risk for health outcomes using the incidence in the exposed and
nonexposed group of subjects. If the investigated drug was really better compared to a placebo
or a gold standard drug, then we expect a relative risk score of less than 1. Furthermore, as a
result of the randomized controlled clinical trial, we can show survival of the subjects in the
groups, for which we can use Kaplan-Meier survival curve, which shows the proportion of
survivors during the follow-up time. These curves can also be used to display other health
outcomes in time, and not just survival, e.g. the proportions of the persons who remain non-
smokers after the measure of interventions among smokers. Similar to the survival curves, for
the analysis of survival, we can use the multivariate analysis of survival - Cox regression model
(proportionalhazards model), and as a result, we get the hazard ratio. Unlike Kaplan-Meier's
method, Cox's regression takes into account the effect of the confounding factors. Of course,
23. 23
the use of Cox regression, as well as the Kaplan-Meier method, is not reserved exclusively to
demonstrate the results of experimental studies, but can also be used in observational studies.
Clinicians may be most interested in the effectiveness of the investigated drug (efficacy), which
speaks of the effectiveness of the investigated drug compared to placebo, or to the gold standard
drug.
The efficacy of the investigated drug is calculated in the following way:
,
whereby the exposed group was the group that received the investigated drug, while the
unexposed group was the one who received a placebo or a gold standard drug.
The difference in incidence in unexposed group and incidence in the exposed group is called
absolute risk reduction. It is necessary to note the difference of this measure in relation to the
attributable risk, which is calculated so that the incidence of unexposed subjects is taken from
the incidence of the exposed subjects. Thus, the absolute risk reduction and attributable risk are
equal in significance, but differ in that the attributable risk is used to estimate the effect of the
harmful factor, while the absolute risk reduction is used to assess the effect of the protective
health factor for the human health.
Another fairly frequent and popular way to display results is to calculate the number of people
you need to treat in a certain way in order to prevent one undesirable outcome (number needed
to treat - NNT). This outcome depends on the research question and the investigated drug, and
may be, for example, death, myocardial infarction, hip fracture, etc.
NNT is calculated in the following way:
24. 24
whereby the exposed group was the group that received the investigated drug, while the
unexposed group was the one who received a placebo or a gold standard drug.
When analyzing data in a randomized controlled clinical trial, we must think of the possibility
of losing subject during the follow-up period (lost to follow-up), as well as the possibility of an
unplanned transition of subjects from exposed to unexposed group, and vice versa (unplanned
crossover) during the follow-up of the subjects. If the proportion of these events is not large,
we analyze the data so that subjects are put into groups that we initially formed with
randomization process (intention to treat analysis). This means that even if we did not follow
subject for a whole set of time, or the subject had to receive a different treatment from an
initially defined, we still put him in the analysis in the group in which he was at the beginning
of the research.
As the results of a randomized controlled clinical trial can have a significant impact on human
health and on the way that health care is provided, it is very important to understand the overall
course of each individual research. In order to show the overall course and the results of this
type of research clearly, the guidelines for writing a scientific article have been developed, so
that the readers could critically evaluate the quality of the implementation of the research, the
data analysis, and the interpretation of the obtained results. Among the most frequently, used
guidelines are the CONSORT (Consolidated Standards of Reporting Trials), which consist of a
25. 25
list of the constituent parts of the research that must be described in the scientific article and the
diagram of the course of the survey.
References
Friedman LM, Schron EB. Methodology of intervention trials in individuals. In: Detels R,
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