EPIDEMIOLOGICAL STATISTICS

An introduction to some commonly used terms of significance for all clinicians

MODERATOR: Prof Kakkar and Prof. R M Kaushik

PRESENTER- Dr.Garima Aggarwal

Epidemiology – It is the study of the rate/occurence of disease in a population

Incidence – The number of new cases occuring in a defined population during a specified period of time.

Prevalence – Refers to all current cases (OLD and NEW) of a disease/ condition at a given point /over a period of time in a given population

P = Incidence X Duration

Sensitivity – Ability of a test to identify correctly all those who have the disease , that is “TRUE POSITIVE”

ELISA for HIV is 99.5% sensitiveSpecificity – It is defined as the ability of

a test to identify correctly those who do not have the disease, that is “TRUE NEGATIVE”

ELISA for HIV is 98.5% specific

False negative-Patients who have the disease are told that they do not have the disease.

False positive- Patients who do not have the disease are told they have it.

Statistical AveragesMEAN – individual observations are

added together and then divided by the number of observations

MEDIAN – data is first arranged in an ascending or descending order of magnitude and then the value of the middle observation is located

MODE- most frequently occurring observation in a series of observations

STANDARD DEVIATION-

EPIDEMIOLOGICAL

STUDY

OBSERVATIONAL

DESCRIPTIVE ANALYTICAL

EXPERIMENTAL

RCTs FIELD TRIALS

COMMUNITY TRIALS

Observational studies-

CASE REPORT – clinical characteristic or outcome from a single clinical subject

CROSS SECTIONAL STUDY – study based on a single examination of a cross section of population at ONE POINT IN TIME , where cross section is such that the results can be projected on the entire study population

CASE CONTROL STUDY – study of a group of people with the disease and compares them with a suitable comparison group without the disease , i.e. CASES and CONTROLS. Retrospective study.

COHORT STUDY – population group of those who have been exposed to risk factor is identified and followed over time and compared with a group not exposed to the risk factor. Prospective study.

CASE CONTROL COHORT

CROSS SECTIONAL

Experimental studies -

RANDOMISED CONTROLLED TRIALS – subjects in the study are randomly allocated into “intervention” and “control” groups to receive or not to receive an experimental preventive or therapeutic procedure or intervention.Most scientifically rigorous studies. Select

population

Select suitable sample

RANDO-

MISE

Experimental V/S control group

Manipulation Blinding

ASSESSMENT

Statistical Analysis -

For observational studies Relative Risk – Ratio of the incidence of the disease (or death) among exposed group and the incidence among non exposed Relative Risk = 1 = no association, >1 = positive associationDirect measure of the ‘strength’ of association between suspected cause and effect

IMR in whites in the US is 8.9 per 1000 live births, and 18.0 in blacks. So the Relative risk of Black v/s White population is 18/8.9 = 2.02. Therefore Black infants are twice as likely to die in the first year of life.

Attributable Risk – It is the difference in incidence rates of disease (or death) between an exposed group and non exposed group.ATTRIBUTABLE RISK = (incidence of disease among exposed – incidence of disease among non exposed) / incidence of disease among exposed x 100

Using above example, AR= 18.0-8.9 = 9.1, hence Of every 1000 black infants there were 9.1 more deaths than were obsereved in 1000 white infants

ODDS RATIO – looks at the increased odds of getting a disease with exposure to a risk factor as opposed to getting the disease without exposure.

OODS RATIO = a x d / b x c

Exposure to Risk factor

CASES(Disease Present)

CONTROL(Disease Absent)

PRESENT a b

ABSENT c d

a + c b + d

SMOKING LUNG CANCER Without LUNG CA.

Smokers 33 55

Non Smokers 2 27

total ODDS RATIO = 33 X 27 / 2 X 55 = 8.1 Smokers showed a risk of having Lung Cancer 8.1 times that of Non smokers.

Inferential statistics

CONFIDENCE INTERVAL – Confidence intervals are a way of admitting that any measurement from a sample is only an estimate of the population

A confidence interval specifies how far above or below a sample based value , the population value lies within a given range , from a possible high to a possible low.

We have 95% confidence intervals and 99% confidence intervals.

If the confidence interval contains 1.0 it is not statistically significant

What is the ‘p value’??? With scientific methods – we put forward a

research question eg. Smokers more likely to get lung cancer!

Null hypothesis – says that all findings are a result of chance or random factors i.e. smoking has no real relation with lung cancer

Hypothesis testing – ‘p value’ – helps to interpret output from a statistical test. It is the standard against which we compare our results.

If p value < or = 0.05 - the results are statistically significant, i.e. REJECT NULL HYPOTHESIS

If p value > 0.05 – statistically insignificant, i.e. DO NOT REJECT NULL HYPOTHESIS

Statistical tests - META-ANALYSIS- A statistical way of

combining results of many studies to produce one overall conclusion.

Correlation coefficient – It indicates the degree to which two measures are related

It ranges from -1.o to +1.0 Medical school grades and various factors affecting

it.Positive value – two variables go together in the same

direction. IQ has a positive corelation with medical grades.

Negative value – presence of one variable is associated with absence of another. Time spent on outdoor activities negative correlation with grades.

t tests – used to compare MEANS of two groups. Can be used for testing two groups only.

Paired t test – when comparing ‘before’ and ‘after’ results in the same group.

Unpaired t test – when comparing means of two groups.

Chi square – can be used for any number of groups.

Used for nominal data.

Thank you for your patience.