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BiomarkersIntroduction
Enabling technologies
Study Design
Biomarker research overview
Study /experimental Design
In the research process, there are various steps when we start with the purpose of the
research. We need to set up the aim of the research. We define the purpose of the research,
and the research question we would like to answer.
But for this course we only focus on research methods (point 6)
The start of the research
We have an aim, research question, and hypothesis.
The first step is to specify what is our aim, and what we want to achieve in our project.
For example: find a biomarker to diagnose disease sub-type A
Next, we set up a research question, what needs to be investigated?
For example: Can biological inhibitor X characterize disease sub-type A?
- Questions should be well-defined to avoid failure in the biomarker discovery
The third thing is to specify a hypothesis, in other words what you expect to observe
For example: Serum levels of biological indicator X can distinguish disease sub-type A from
sub-type B
Research Methods: Study Design
Definition (Study Design): A study design is a specific plan or protocol for conducting the
study, which allows the researcher to translate the conceptual hypothesis into an
operational one.
There are different types of study designs. In terms of time, you have for example two types:
a retrospective, prospective, cross-sectional and longitudinal.
Retrospective: this research is conducted now, but we need to go back and select the
samples from the past.
- It is less expensive (+)
- But we have less control (-)
Prospective: we start now and we collect data from now on. For example we start a study
design now and we collect data until 2023.
- You have more control (+)
- But it is time-consuming (-)
,Cross-sectional: these are the ones that we start now and we collect data from a specific
time-point. It has a specific time-point in the past
Longitudinal: we collect data repeatedly over time, we can start from the past we can collect
data from the present and future.
Types of Epidemiological Study Designs
Epidemiological studies (quantitative): we have study designs from which we can do
analyses. We can extract results from them. These are the first split into non-interventional
and interventional.
Non-interventional (observation): the researcher doesn’t intervene to the people that are in
the study. (But in interfene studies it is possible that the reasearcher can intervene by giving
a specific administration or a drug, treatment or operation.)
- Descriptive studies: case reports and case series, only describe the population that
we have and the data that we collect from them.
- Analytical studies: cross-sectional, cohort (prospective) and case-control
(retrospective).
Interventional (Experimental):
- Randomized Controlled Trial (Clinical Trial)
- Quasi-Experimental (Non-randomized)
Hierarchy of Evidence
Hierarcy of the different types of study. If we go higher we get more quality of evidence.
,Observational & Experimental studies
Observational studies: we just observe the population/data, the researcher doesn’t
intervene to this population. So he/she doesn’t give the treatment, administration or drug.
- The researchers “allow nature to takes its course” by measuring but not intervening.
- They can be descriptive or analytical.
- Descriptive: observational study describes a disease or a phenomenon in a
population.
- Analytical: observational study goes a step further by analyzing the association
between health (outcome) and other biomarkers (exposure) to search for causes and
effects.
Outcome: health disease we want to study.
Exposure: biomarkers we want to assess if it has any association with the outcome of
interest.
Experimental studies: Also called interventional studies, where for example, in biomarker
discovery research the researcher can intervene with the administration of a drug or
treatment and after a biochemical analysis measure the drug effect using the biomarkers’
observation and compare it with the control group (placebo) .
Case report
- Most simple one, these are reports that are careful and detailed written of a single
patient by one or more clinical. they might have a specific/rare disease, that is very
important to investigate. (Dealing with cases that show an important variation of a
disease or condition.)
- This is a particular case, we can describe the disease by taking the characteristics of
that single patient but we cannot generalize it in a population
Advantages & Disadvantages of Case reports
Advantages:
- Case reports are considered the lowest level of evidence (the pyramid above), but
they are also the first line of evidence due to they are conducted when new issues
and ideas emerge; It can help with the identification of new trends or disease
- It can help with the identification of new trends or diseases.
- Can help detect new drug side effects and potential issues (adverse or beneficial)
- Useful in clinical education and research development
Disadvantages:
- Cases me not be generalizable, because they are referring to specific patients with
specific diseases.
- Not based on systematic studies.
- Causes or associations might have other explanations
Case series
- Description of clinical characteristics (biomarkers) of a small number of patients with
a given disease/condition having similar diagnosis (purely descriptive type of studies);
- Collection of their individual case reports (for the same type of disease)occurring
within a short time period
, - Analysis of cases together in order to learn about the disease
- Studying predictive symptoms, signs and tests
- Creating case definitions
- Clinical education, audit and research purpose
Advantages & Disadvantages of Case reports
Advantages:
- Can be valuable early evidence for associations between biomarkers and diseases
which can be studied in more detail
- Useful for describing a new disease with an unclear cause
- Useful for constructing of the natural history of a disease
Disadvantages:
- They don’t have a comparison group, We cannot compare the case series as for
example you have in other experiment the control group and the group treatment
group.
- Based on the experience of one person, thus it cannot be used to test for presence of
a valid statistically significant Association.
Cross-sectional
- The ones that collect data from a specific time-point.
- Disease (outcome)and biomarkers (exposure) are measured simultaneously among
individuals in a well-defined population at a certain point in time.
- Investigation of the association between the biomarker levels and the disease
prevalence
- It is like a picture of a population, “snapshot” of the health status of a specific
population at a particular point in time.
Example: Cross-sectional
These are used to see the probability of developing ovarium cancer. Odd ratio: How likely it
is to develop ovarium cancer. Odds-ration means the probability of developing a disease.
The highest ratio is BDNF, the chance to get cancer will be higher.
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