introduction to various aspects of risk, attributable and relative risk,odds ratio,confidence interval, experimental event rate and control event rate

1. CONCEPTS OF RISK

2. CONCEPTS OF RISK
• Risk is the likelihood or the probability of experiencing some
type of harm, or losing something that one values.
• Risk factors are variables or characteristics (biological -
genetic disorder/ageing, environmental-air/water pollution/
passive smokingor psychosocial- workload/deadlines)
associated with an individual that make it more likely that he
or she, as opposed to another person randomly selected from
the population, will develop a problem.

3. RISK FACTORS:
• Exists before a disorder or problem;
• Maybe time – limited or may continue over time;
• Can derive from the individual, the family, the community,
institutions or the general environment; and
• Can play a causal role or be a marker for a problem (BRAC)
CHARACTERISTICS OF RISKS:
1. Risk is not certain.
• Risk is based on probability. Therefore, not everyone who is
exposed to a risk condition or factor will have an adverse
outcome. Risk factors are “linked to” and “associated with”
negative outcomes.
• E.g. psychosocial outcomes v/s biological outcomes
• Teratogenic drug – thalidomide, environmental toxin – lead

4. 2.Risk is a relative concept.
• Risk factors range from those that are only markers to
minimally harmful situations to those that are markers to life –
threatening situations.
• (Social continuum of risk/personal risk continuum)
• Risk is not a neutral concept. It involves determining what are
acceptable or unacceptable consequences.
• Risk factors work together over time to influence the
likelihood of a negative outcome.
• The longer the exposure to risk factors, the greater the
likelihood the health problem will occur.
• Risk Identification – Exist as a social context. The
identification of risk will be partially based upon their values,
biases, experience and knowledge.

5. RISK PURSUED AS
OPPORTUNITY
RELUCTANTLY
ASSUMED RISK
RISK FOR WHICH
NO CHOICE
FREELY ACCEPTED
RISK
Personal risk continuum.

6. Flow of Risk in Epidemiology:
TRUE RISK
PHARMACOEPIDEMIOLOGICAL
CONSIDERATIONS
(Bias, confounding etc)
STATISTICAL CONSIDERATIONS
(Sampling, models, etc)
MEASURED
ESTIMATED RISK

7. Risk in Pharmacoepidemiology:
• Health research involves the estimation of risk.
• In the case of drug related research, it is important to
understand the concept of risk.
• It is the probability of developing an outcome when exposed to
a drug.
• A drug is approved for human use only after measuring the
risks and benefits associated with it.
• HCP/Pharmacists should know the magnitude and frequency
of the risk involved in the drug in use.
• Each drug outcome has its own risk.
• It is a probability and depends on a variety of factors like age,
sex, physical conditions, food habits, other diseases, other
medicines, kinetics of drugs etc.

8. MEASUREMENT OF RISK
 To accurately and precisely measure risk, one needs a tool that
is accurate and precise enough for the measurement being
made.
 Measuring risk in epidemiology , precision and accuracy
depend on factors :
 Degree to which the experimental data and analysis are
free of the errors associated with experimental design
flaws(confounding, bias, reliability, measurement error
and misclassification, potential alternate risk factors)

9. Statistical analysis errors (sampling error,
violations of model assumptions, model
shopping, multiple subgroup analyses, reliance on
significance levels or p-values.

10. ATTRIBUTABLE RISK
 Attributable risk is the difference in rate of a condition
between an exposed population and an unexposed population.
 Mostly calculated in Cohort Studies, where individuals are
assembled on exposure status and followed over a period of
time.
 Investigators count the occurrence of the diseases.
 The Cohort is then subdivided by the level of exposure and the
frequency of disease is compared between subgroups.

11.  One is considered exposed and another unexposed.
AR = Rexposed - Rnon-exposed
where R is the rate of the outcome of the interest or the
Incidence.
Attributable Risk = Incidence in exposed – Incidence in unexposed
%AR = 100 × Rexposed – Rnon-exposed
Rexposed

12.  The risk of a drug has to be assessed within the environment or
atmosphere where it is used.
 Example : we cannot attribute all incidence of GI discomfort in
people taking Ampicillin capsules to the drug since some may
have it for other reasons than the drug use.
 If the risk due to other reasons than the drug are reduced from the
overall risks, we get attributable risk.
AR = Rexposed - Rnon-exposed
 Attributable risk is also known as risk difference or rate
difference.

13.  In clinical outcomes the rate difference quantifies one rate in
comparison with another.
 If amoxicillin is 90% successful in treating a specific type of
infection and ampicillin is 65% successful in treating the same
infection, the rate difference 90% -65% = 25%.

14. RELATIVE RISK
 Relative risk or risk ratio (RR) is the ratio of the probability of
an event occurring ( eg:developing of an ADR to a drug) in an
exposed group to the probability of the event occurring in non-
exposed group.
 Includes 2 features:
i. A comparison of risk between two “exposure” puts
risks in context , and
ii. “exposure” is ensured by having proper denominators
for each group representing the exposure

15.  RR = Prevent when exposed
Prevent when non-exposed
 It is a ratio of two risks, the risk of the outcome/event in the
treated group compared with the outcome in those not
exposed(control group).
 RR = Proportion of events in experimental group/proportion of
events in control group.
 RR above 1 indicates treatment/exposure is associated with the
outcome and below 1 means that the treatment is negatively
associated with the outcome.

16.  When the rate in the exposed group is equal to the rate in the
comparison group RR will be equal to 1.
 An RR of 2 means that the rate in the exposed group is twice
that in the non-exposed group.
 An RR of 0.5 means that the rate in the exposed persons is half
that of non-exposed persons.
 Eg: The probability of developing allergy among users of
perfume was 20% and among those not using perfume 1%

17. Here , a=20, b=80, c=1, d=99
Then the relative risk of allergy associated with users of perfume would be
RR= a/(a+b)
c/(c+d)
= 20/100 = 20
1/100
RISK ALLERGY STATUS
Present Absent
Perfume users a b
Perfume Non- users c d

18. Different types of RR
 The RR is derived from study designs where the study
population is selected on the basis of exposure (eg: cohort
study),or disease (eg: case- control design) and may have
different names depending on the context :
• In a cohort mortality study the RR is called a standardized
mortality ratio (SMR).
• In a cohort incidence study the RR is called a standardized
incidence ratio (SIR).
• In a morbidity cohort or cross-sectional study the RR may be
called a prevalence ratio.
• In a case-control study the RR is called an odds ratio (OR).

19. ODDS RATIO:
• It is a measure of association between an exposure and an
outcome like Risk Ratio (RR).
• Odds Ratio in statistics and epidemiology is commonly
abbreviated as ‘OR’.
• Like Risk Ratio determines probabilities, in OR Odds are
used.
• In clinical studies and many other settings, the first parameter
of greatest interest is the RR and the next one is OR.

20. How to find odds ?
Eg:
There are two sample groups, one consisting of 100 men and
other 100 women were identified from city residential area. In a
dinner party, out of 100 men, 90 drank beer, while out of 100
women only 20 drank beer.
Ans: the odds of a man drinking wine are 90 to 10, or 9:1, while
the odds of a woman drinking wine are 20 to 80, or 1:4=0.25:1.

21. COMPUTATION OF OR:
• The OR represents the odds that an outcome will occur given a
particular exposure, compared to the odds of the outcome
occurring in the absence of that expoure.
Eg: OR helps to quantify how strongly the presence or absence of
property ‘X’ is associated with the presence or absence of
property ‘Y’ in a given population.
• If each individual in a population either does or does not have
a property “ X” (eg: increased blood sugar level),& also either
does or does not have a property “Y” (eg: use of statins) where
both properties are appropriately defined, then a ratio can be
formed.

22. • This ratio quantitatively describes the association between the
presence/ absence of “ X” and the presence / absence of “Y”
for individuals in the population. This ratio is the Odds Ratio.
• The OR can be computed by following these steps:
1. For a given individual that has “Y” compute the odds that the
same individual has”X”.
2. For a given individual that does not have “Y” compute the
odds that the same individual has “X”.
3. Divide the odds from step 1 by the odds from step 2 to obtain
the OR.

23. • The term “individual” in this usage does not have to refer to a
human being , as a statistical population can measure any set
of entities, whether living or inanimate.
• If the OR is greater than 1, then having “X” is considered to be
“associated” with having “Y” in the sense that the having of
“Y” raises ( relative to not having “Y”) the odds of having
“X”.
• Note that this is not enough to establish that ‘Y’ is a
contributing cause of “X”: it could be that the association is
due to a third property , “Z”, which is a contributing cause of
both “X” and “Y”.

24. • Illustration 1:
Take the same illustration given for finding odds above. Now
we can find the OR as shown below
The OR is 9/0.25, or 36. It shows that men are much more
likely to drink wine than women.
The detailed calculation is :
0.9/0.1 = 0.9 ×0.8 = 0.72 = 36
0.2/0.8 0.1 × 0.2 0.02
This eg also shows how odds ratios are sometimes sensitive in
stating relative positions. In this illustration men are 90/20 = 4.5
times as likely to have drunk beer than women, but have 36 times
the odds.

25. • Illustration 2: odds ratio contingency
OR = a/c = a×d
b/d b×c
Cases Control Total
Exposed a b a+b
Unexposed c d c+d
Total a+c b+d (a+b) + (c+d)

26. • Imagine a group of 20 students went out to the pub – the next
day a 7 were ill. They suspect that it may have been something
they ate, may be the fish casserole. Here are the numbers:
Cases (illness) Control (no
illness)
Total
Exposed (ate
fish)
5 3 8
Unexposed
(didn’t eat fish)
2 10 12
Total 7 13 20

27. • Odds of exposure in cases = a/c = 5/2 = 2.5
• Odds of exposure in controls = b/d = 3/10 = 0.3
• Odds Ratio = (a/c) / (b/d) = 2.5/0.3 = 8.33
INTERPRETATION: WHAT DOES THIS MEAN ?
• OR of 1 would suggest that there is no difference between the
groups; i.e., there would be no association between the
suggested exposure (fish) and the outcome being ill.
• OR of > 1 suggests that the odds of exposure are positively
associated with the adverse outcome compared to the odds of
not being exposed.
• OR of < 1 suggests that the odds of exposure are negatively
associated with the adverse outcomes compared to the odds of
not being exposed.

28. • In the eg above, we can conclude that those who ate the fish
casserole (exposure) were 8.3 times more likely (OR = 8.3) to
be ill (outcome), compared to those who did not eat the fish
casserole.
ADVANTAGES:
• Appropriate to analyse associations between groups from case-
control and prevalent (or cross-sectional) data.
• For rare diseases (or diseases with long latency periods) the
OR can be an approximate measure to the RR .

29. • Doesn’t require denominator (i.e. total number in population)
unlike measuring risk.
• Good method to estimate the strength of an association
between exposures and outcome.
DISADVANTAGES:
• Association does not infer causation.

30. TIME RISK RELATIONSHIP:
• The outcome of an exposure to a drug is related to
the time.
• It is also true with risks associated with medicines.
• There is always a time related association of risk in
pharmacoepidemiology.
• Certain events like anaphylactic reactions happen
immediately after taking an injection while certain
other risk events occur after days or months or even
years.
.

31. • Eg: prazosin , an alpha blocker has main effect in dilation of
veins and arteries which leads to reduction in BP. It is
sometimes also used for BPH. To minimize the impact of first
dose effect, prazosin is normally taken at bedtime. Other drugs
of same family, doxazosin and terazosin, can also cause this
phenomenon, though less frequently
• Delayed reactions to medications commonly begin more than
6 hrs after exposure but sometimes occur days after exposure.
Eg: delayed ADR to amoxicillin classically start between 7 to 10
days of exposure and may even begin 1 to 3 days after the
patients had stopped taking the medicine.

32. • Medications that cause delayed reactions include heparin, quinine,
sulphonamides, vancomycin, gold compounds, beta lactam antibiotics and
NSAIDs.
• Lomustine is an anticancer drug used in different types of cancer which has
an adverse effect of producing leucopenia that occurs 6 weeks after the
dose.
• The above mentioned aspects of medicine demonstrate that the exposure
time must always be considered and the risk should be expressed as a
function of time wherever possible in pharmacoepidemiology.
CONFIDENCE INTERVAL (CI):
• CI are a range of values within which the true population values probably
lies .
• When the risk estimators like RR or OR are calculated they are presented
with a CI.
• Generally a 95% CI (CI95) is calculated which means that we are 95%
confident that the true value lies between these limits.

33. ABSOLUTE RISK:
• The risk of having a disease at any point in time is known as
Absolute Risk.
• It is the incidence.
• If the incidence of epilepsy is 1 in 10,0000 then the absolute
risk is 0.001 %.
EXPERIMENTAL EVENT RATE (EER):
• It is the proportion of patients in the treated group in whom an
event is observed.
• If out of 100 treated patients (a+b), the event is observed in 27
(a), the EER = 0.27, that is
EER = [a/(a+b)]

34. CONTROL EVENT RATE (CER):
• It is the proportion of patients in the control group in whom
an event is observed.
CER = c/(c+d)

35. THANK YOU