Summary pharmacoepidemiology
Lecture 1 intro
Diagnostic: What have the children?
Etiology: What is the cause of the disease?
Prognosis: What is the future of the children?
Intervention/therapy: How can these children be helped? What is the best treatment?
Intervention/prevent: How to prevent?
Efficiency/economics: Expensive to prevent?
Epidemiology: the science that studies the occurrence of diseases in large populations of people as a function
of determinants
Epidemiology is an essential science for the conduct of “Evidence Based Medicine: Approach to medical
practice that emphasizes the use of the best available scientific evidence to make informed decisions about
patient care. Epidemiology plays a crucial role in generating, interpreting, and applying this evidence.
Difference between etiology/intervention and diagnosis and prognosis.
Etiology/ intervention(understanding the causes of diseases and the effectiveness of interventions)
causal relationship (associations)
analytical studies
mostly one determinant: identify the specific factors responsible for the disease.
confounding bias: distortion of the true relationship between the determinant and the outcome due
to the presence of other factors
explanatory statistical model: how the determinant(s) influence the outcome
Diagnosis/prognosis(aim to describe and predict health outcomes)
no causal relationship
predictive associations
descriptive studies
more determinants
no confounding bias: these studies are not primarily concerned with causality, confounding bias is of
less concern.
predictive statistical model: to estimate the likelihood of a particular outcome occurring based on a
combination of determinants
Main reasons for dangerous side effect and of withdrawal alive:
1. Clinical trials are not large
2. Real world use of a drug differs
3. Time plays a role (clinical trials test not long time side-effects)
4. Off-label prescribing may lead to unexpected issues-> Off-label prescribing occurs when a healthcare
provider prescribes a medication for a use that has not been approved by regulatory agencies. This may include
using a drug to treat a different medical condition, using it in a different patient population, or at a different
dosage or duration.
Drug repurposing is that drugs are used for other diseases than where the drug is original is
made for. Other indication for the same drug.
Examples of drug withdrawal of market: Rofecoxib, valdecoxib
Examples of drugs with new identified effect (positive): Viagra (first for heart-related chest pain->now for
erectile dysfunction)
Two types of questions:
Type 1 What is the use of drug X in patient Y and what is the variation between age and sex?
This type of question typically involves observational studies, where researchers assess the real-world use of a
drug (cohort studies) in a specific patient population (patient Y). The variation between age and sex suggests
that the study might involve subgroup analysis, examining how drug X is utilized and its effects in different
demographic groups (age and sex). Age and gender are the determinants.
,Type 2 What is the effect of drug X in the treatment disease Z on outcome Y. E.g. to what extent prevents polio
vaccination the occurrence of polio in children?
This type of question often relates to efficacy studies (RCTs). Researchers administer drug X to a group of
patients with disease Z (e.g., polio vaccination in children with polio) and compare their outcomes (occurrence
of polio) to a control group that does not receive the treatment. These studies aim to assess the effectiveness
of the intervention in preventing or treating a specific disease.
Experimental studies:
field trials:(individual) conducted in real-world
settings, often with a focus on public health
interventions or preventive measures. (vaccination
campaigns)
clinical trials: research studies involving human
participants to evaluate the safety and efficacy of
medical interventions, such as new drugs,
conducted in controlled clinical environment.
community intervention trials:(whole group)
involve interventions targeting entire communities to assess their effects on public health outcomes
Observational studies:
cohort: investigate history of disease, relationship between exposures and outcomes(group with
common characteristics or exposure is followed over time)
case-control: used to investigate the causes of a disease/condition. (group with disease and group
without and look at exposure history of both groups to identify risk factors)
cross-sectional and descriptive studies: collect data from participants at a single point in time to
analyze the prevalence of an exposure/condition-> snapshot of population's characteristics at that
moment.
Descriptive Studies (Diagnosis/Prognosis): detailed information about a specific condition, disease, or
health outcome. They are often used to describe the distribution of a condition or to make predictions
about its future outcome (prognosis).
Randomized control trials (RCT): used to assess the effectiveness of medical interventions, treatment or
therapy. (intervention group with drug/treatment and control with placebo/standard treatment)
limited number of patients
limited time (short term therapy)
homogeneous populations
other variables excluded or controlled (control or minimize the influence of factors other than the
intervention. Researchers use randomization to ensure that confounding variables are evenly
distributed between the treatment and control groups)
Observational studies (PMS, post marketing surveillance):
large numbers
unlimited time
drug-users in practice (reflect to broader patient population that are all using the drug so not limited
to a controlled setting)
suspectable to other influences such as smoking, other drugs, nutrition
Characteristics of RCT:
Random assignment to allocate participants into either the treatment group or the control group. This
randomization minimizes selection bias
RCTs are often used to study specific clinical indications or questions
In a double-blind RCT, both the participants and the researchers are unaware of who is in the
treatment or control group. This minimizes the potential for bias.
Important clinical information that has to be obtained from PMS research that helps assess safety,
effectiveness, and real-world use of drugs and medical interventions:
Adverse effects
Effects in daily practice
Usage of drugs for other indications (off-label)
, New applications for existing drugs/interventions
Effect hard endpoints: PMS research can provide insights into the impact of treatments on "hard"
clinical endpoints, such as mortality, hospitalization rates or disease progression.
Other medication reactions (between drugs that are simultaneously taken)
Efficacy: Effect in clinical trials or laboratory studies
Effectiveness: Effect in daily practice
Efficiency: Costs in relation to effect
Post-marketing surveillance: Monitoring all (anticipated and unanticipated) desirable and undesirable
(adverse)-effects of drugs to human health, after these drugs are released on the market. The goal is to obtain
scientifically based data on rational and safe use of drugs.
PMS is obtained by:
More transparency in communication about adverse effects to the public
Black triangle on all newly approved drugs
“Direct-to-consumer advertising” prohibited in the first two years after registration
Better monitoring and reporting on drug safety (more funding needed to do this)
Who has interest in PMS:
Patient: wants an effective and safe drug with reliable information
Physician/pharmacist: wants reliable and complete information to make a good decision
Insurance company: importance of rational prescribing with regard to costs
Government: registration and safety
Industry: wants a good product
What are information sources PMS?
Spontaneous reporting system: reports of adverse events and side effects from healthcare professionals,
patients, and sometimes the pharmaceutical industry
routine database: consist of existing healthcare records, insurance claims, electronic health records, and other
routinely collected patient data
questionnaire/interviews: patients-reported outcomes
cohorts/physical testing/lab data: objective measures of patient outcomes and potential adverse effects
ATC/DDD system
ATC (=anatomical therapeutic chemical classification
system)are codes for medications, first
letter is the anatomy. N1= anatomical, N2 therapeutic
main group (2 digits), N3 therapeutic
subgroup(1 letter), N4 therapeutic/chemical
subgroup (1 letter), and N5 chemical substance (2
digits)
DDD(=defined daily dose) is the average daily maintenance dose for a drug used for it’s
main indication in adults. DDD of new drugs is revised after three years. DDD serves as a
rough estimate and does not account for individual patient characteristics or need.
Figure 1: anatomical main groups in the
DDD is primarily used to quantify the volume of drug usage at the population level->
ATC-system
compare consumption of specific drugs within and between different countries or
regions.
Larger intake than DDD-> toxic effects/more side effects.
Smaller intake than DDD-> no therapeutic effect.
Naronjo algorithm: Questions about drugs, to determine
adverse drug reaction(ADR) is actually caused by the drug.
Weber effect: increased reporting of adverse events and
complaints related to a newly marketed drug, particularly in the
initial period after its introduction to the market. This increase in
reports is often associated with heightened public and
healthcare professional awareness of the new drug.
, Channeling bias: When a new drug is introduced, it may be perceived as having a more favorable safety profile
compared to an existing drug. If patients who are already taking the older drug are directly switched to the new
drug based on this perception, it can result in channeling bias. Even if the new drug is believed to have fewer
adverse effects than the old drug, it does not necessarily mean that it is entirely free from adverse effects.
Channeling patients from the old drug to the new drug can result in underreporting or underestimation of the
new drug's potential adverse effects. This situation can create a significant problem. Patients may be exposed
to adverse effects they weren't previously experiencing, and the underestimation of these adverse effects can
affect patient safety.
Example of a cohort study is the Framingham Heart Study which is one of the most well-known cohort studies
focused on cardiovascular disease. It aims to identify risk factors for heart disease and stroke. British
physicians(Doll en Hill) (1951) is a study that studies the link between smoking and mortality
Advantages of cohort studies:
large group
fast
validation data (Cohort studies can provide valuable data for validating hypotheses and exploring cause-and-
effect relationships)
prevent recall bias because data on exposures are collected before the outcome occurs
o Recall bias is commonly associated with case-control studies. In these studies, researchers
compare individuals who have a specific health outcome (cases) with those who do not
(controls). Cases and controls are asked to recall past exposures, behaviors, or experiences. If
cases have a better memory or motivation to remember exposures, it can lead to
overestimation of the association between exposure and the outcome.
information about reference group or controls without disease
low cost
minimal effort researcher
Disadvantages:
indication bias, where patients in different exposure groups may have different baseline
characteristics or risk profiles, making it challenging to isolate the effect of the exposure.
insufficient number of patients
new drug (channeling->the use of a new drug may result in channeling bias if it's prescribed to
patients who are perceived to have a different risk profile)
no information about confounding variables or factors that can affect the outcome
validity and completeness(quality of) data depend on the data source (Inaccurate or incomplete data can
impact the validity of the study)
Lecture 2
Health economics: field of study that applies economic principles and methods to issues related to health and
healthcare
Pharmacoeconomics: evaluating and analyzing the economic aspects of medications and interventions
involving medications. It involves the systematic assessment of the costs and outcomes associated with various
treatment options to determine whether a particular healthcare intervention is worth the investment or
provides value for money.
Health technology assessment(HTA): process that evaluates new and existing health technologies. Including
thorough evaluation of all aspects of a new healthcare intervention, including its clinical and economic impact,
cost-effectiveness, and other factors to inform decisions on the adoption and utilization of healthcare
technologies. HTA has roots in different disciplines(economics, medicine, public health, and epidemiology).
The role of Health technology assessment(HTA) varies between countries. HTA is often used for making
decisions in medicines, vaccines and population screening program(screen for health conditions like cancer).
HTA is less used medical devices and procedures. EUnetHTA is a network established to promote collaboration
and facilitate the exchange of HTA information and expertise among European countries.
For low-and-middle-income countries(LMICs) a large part of health care spending is out of pocket->health
events may bankrupt families. Universal Health Coverage (UHC) is a global healthcare goal supported by WHO.