Epidemiology And Biostatics

Front 1

Case series

Back 1

Several patients with the same diagnosis, treatment and outcome

Front 2

Cross sectional study

Back 2

1- Frequency of a disease and the frequency of the risk related factors are assessed in the present

2- Disease prevalence

Front 3

Case controls study

Back 3

1- Compares a group of patients with the disease to a group of patients without the disease

2- Odds ratio

Front 4

Cohort study

Back 4

1- Compare a group of patients with a given exposure or risk factor

2- Looks if the exposure or risk factor is associated with later development of the disease

3- Relative risk

4- Retrospective or prospective

Front 5

Cross over study

Back 5

1- Compare the effects of a series of 2 or more treatments on a participant

2- Randomized

Front 6

Twin concordance study

Back 6

1- Compare the frequency in which both a monozygotic and a dizygotic twin develop the same disease

2- Measure heritability and influence environmental factors

Front 7

Adaption study

Back 7

Compare siblings of biological parents vs adaptive parents

Front 8

Ecological study

Back 8

Compare frequent of a disease vs frequency of relative factor in the population

Front 9

Clinical trial

Back 9

1- Experimental studies on humans

2- Compare the therapeutic benefits of 2 of more treatments

3- Improved study when it is randomized , double blind or triple blind

Front 10

Clinical trial

Back 10

1- Experimental studies on humans

2- Compare the therapeutic benefits of 2 of more treatments

3- Improved study when it is randomized , double blind or triple blind

Front 11

Single vs double vs triple blind study

Back 11

Single blind- only the patient is blind

Double blind- Neither the patient nor the doctor knows who is in the treatment group from the control group

Triple blind- Blind the researcher analyzing the data

Front 12

Phase 1 of the clinical trial

Back 12

1- Small number of healthy volunteers or patients with the disease of interest

2- Is it safe

3- Determine safety, Toxicity, pharmacokinetics and pharmodynamics

Front 13

Phase 2 of clinical trial

Back 13

1- Moderate number of patients with the disease of interest

2- Does it work

3- Determine treatment efficiency, optimal dosing and adverse effect

Front 14

Phase 3 of clinical trial

Back 14

1- Large number of patients are randomly assigned to the treatment under investigation or the stander of care

2- Improvement

3- Compare the new treatment to the current standard of care

Front 15

Phase 4 of clinical trial

Back 15

1- Post-marketing surveillance of patients after the treatment is approved

2- Marketing

3- Detect rare long term effects

Front 16

What is the purpose of phase 0 in a clinical trial

Back 16

Initial assessment of a drug pharmacodynamics and pharmacokinetics

Front 17

Bradford hill 9 criteria’s

Back 17

Cause and effect relationship

1- Analogy- compare

2- Biological gradient - dose response relation

3- Consistency

4- Coherence - supported by literature

5- Experimental

6- Plausibility - cause lead to and effect

7- Temporality - Exposure proceed onset of the drug

8- Strength - associate increase evidence of causation

9- Specificity

Front 18

Main Bradford Hill criteria

Back 18

Temporality

Front 19

Sensitivity

Back 19

1- Proportion of people with the disease who test positive are truly positive

2- Value approching 100% rule out

3- Indicate a low false negative rate

4- Use in screening

Front 20

Specificity

Back 20

1- Proportion of people without the disease who test negative are truly negative

2- Value approaching 100% rule in

3- Indicate low false positive rate

Front 21

Positive predictive value

Back 21

1- Probability that a person with a positive test results actually has the disease

Front 22

Negative predictive value

Back 22

Probability that a person with a negative test result does not have the disease

Decrease with prevalence

Front 23

Positive Likelihood ratio

Back 23

Probability of positive result in a patient with the disorder / Probability of a positive result in a patient without the disorder

Front 24

Positive Likelihood ratio

Back 24

Probability of positive result in a patient with the disorder / Probability of a positive result in a patient without the disorder

Front 25

Negative likelihood ratio

Back 25

Probability of negative result in a patient with the disorder / Probability of a negative result in a patient without the

Front 26

Likelihood ration >10 <0.1

Back 26

> 10 specific test increase chance by 45%

<0.1 sensitive test decrease change by 45%

Front 27

Odds ratio

Back 27

1- Case control study

2- Odds of exposure among the cases vs odds of exposure among control

3- ad/cb

Front 28

Relative risk

Back 28

1- Cohort study

2- Risk of developing a disease among the exposed vs unexposed groups

3- a/(a+b)/ c/(c+d)

Front 29

Relative risk

Back 29

1- Cohort study

2- Risk of developing a disease among the exposed vs unexposed groups

3- a/(a+b)/ c/(c+d)

Front 30

Relative risk =1 <1 >1

Back 30

=1 No association between exposure and disease

>1 Exposure associated with a increase risk of disease occurrence

<1 Exposure associated with a decrease risk of disease occurrence

Front 31

Relative risk reduction

Back 31

1- Proportion of risk reduction attributed to the intervention as compared to a control

2- 1-RR

Front 32

Attributable risk

Back 32

1- The difference in risk between the exposed vs unexposed group

2- a/(a+b) - c/(c+d)

RR-1/ RR x 100

Front 33

Absolute risk reduction

Back 33

1- The difference in risk reduction attributed to the intervention as compared to the control

2- c/(c+d) - a/(a+b)

Front 34

Number needed to treat

Back 34

1- Number of patients who need to be treated for 1 patient to benefit

2- NNT= 1/ARR

Front 35

Number needed to treat

Back 35

1- Number of patients who need to be treated for 1 patient to benefit

2- NNT= 1/ARR

3- Low number - better treatment

Front 36

Number needed to harm

Back 36

1- Number of patients who need to be exposed to the risk factor for 1 patient to be harm

2- NNH = 1/AR

3- High number- safe exposure

Front 37

Case fatality rate

Back 37

1- Percentage of death occurring among those with the disease

2- death/case x 100

Front 38

What measurement can you use in place of the relative risk (RR) of a disease if it is exceedingly rare

Back 38

Odds ratio

Front 39

Mortality rate

Back 39

Number of deaths within a population over a period

x 1000

Front 40

Attack rate of a disease

Back 40

Proportion of people exposed to a particular disease who become ill

Front 41

Incidence

Back 41

1- Number of new cases / number of people at risk

Front 42

Incidence

Back 42

1- Number of new cases / number of people at risk

Front 43

Prevalence

Back 43

1- Number of current cases/ Total population at risk

2- Increase prevalence increase PPV

Front 44

Common cold with incidence and prevalence

Back 44

Equal for disease with short duration

Front 45

Precision (reliability)

Back 45

1- The consistency and reproducibility of a test

2- Absence of random variation

3- Random error decrease precision

4- Increase precision with decrease standard deviation and increase statical power

Front 46

Precision (reliability)

Back 46

1- The consistency and reproducibility of a test

2- Absence of random variation

3- Random error decrease precision

4- Increase precision with decrease standard deviation and increase statical power

Front 47

Accuracy (validity)

Back 47

1- The closeness of a test result to its true value

2- Absence of bias or error

3- Systemic error decrease accuracy

Front 48

What does the aces represent

Back 48

Y - sensitivity (true positive)

X- 1- Specificity (false positive rate )

Front 49

Measure of central tendency

Back 49

Mean

Median

Mode

Front 50

Measure of dispersion

Back 50

Standard deviation

Standard error

Front 51

Mean vs median vs mode

Back 51

Mean- Average

Median - Middle value of a list of data sorted from least to greatest

Mode- Most common value

Front 52

Standard deviation vs standard error

Back 52

Standard deviation- How much variability exist in a set of data around the mean value

Standard error- How much variability exist in a set of data around the total population mean

2- SD/square root of sample size

Front 53

Outliers affecting central tendency

Back 53

Mean- mostly affected

Mode- least affected

Front 54

Non-normal distribution

Back 54

Bimodal - suggest two different population

Positive skew - Tail to the right

Mean>median>mode

Negative skew tail to the left

Mean

Front 55

What is the relationship between standard variance and standard deviation

Back 55

Standard variance = SD2

Front 56

What is the best measure of central tendency for normal distribution

Back 56

Mean

Front 57

Null hypothesis

Back 57

No difference or relationship

Front 58

Alternative hypotheses

Back 58

Some difference or relationship

Front 59

Meta analysis

Back 59

Statistical analysis that pools summary data from multiply studies for a more precise estimate of the size of effect

Front 60

What 2 factors can limit the findings of a meta analysis

Back 60

Quality of the study

Selection bias

Front 61

By conducting a meta analysis what happen to the power of the study

Back 61

Improves power

Front 62

In a meta- analysis how is generalizability of the study affected

Back 62

Increase generalizability

Front 63

How does the level of evidence of individual studies change after meta analysis

Back 63

Strengthens the level of evidence

Front 64

What is the numeric range of r (Pearson coefficient)

Back 64

-1 and +1

Front 65

Recruiting bias

Back 65

Selection bias

Front 66

Performing bias

Back 66

1- Recall bias

2- Measurement bias

3- Procedure bias

4- Observer bias

Front 67

Interpreting bias

Back 67

1- Confounding bias

2- Lead time bias

3- Length time bias

Front 68

Selection bias

Back 68

1- Sample from the study population is not representative of the target population

2- Sampling bias

3- Berkson bias - case/control from the hospital are less healthy and have different exposures

Attrition bias- Subjects lost to follow up or have different prognosis

4- Reduce with randomization

Front 69

Recall bias

Back 69

1- Awareness of the disorder alters recall by the subject

2- Reduce- Decrease time from exposure to follow up

Front 70

Recall bias

Back 70

1- Awareness of the disorder alters recall by the subject

2- Reduce- Decrease time from exposure to follow up

Front 71

Measurement bias

Back 71

1- Information is gathered in a systematically distorted manner

2- Hawthorne effect - Participants chances behavior upon awareness of being observed

3- Reduced- using objective, standardized and previously tested methods

2- use placebo group

Front 72

Procedure bias

Back 72

1- Subjects in different groups are not treated the same

Front 73

Procedure bias

Back 73

1- Subjects in different groups are not treated the same

Front 74

Observer bias

Back 74

1- Pygmolion effect - Researcher beliefs the efficacy of the treatment changes the outcome of the treatment

2- Reduced - Double blinding

Front 75

Procedure bias

Back 75

1- Subjects in different groups are not treated the same

2- Reduced 1- Blinding

2- Using placebo groups

Front 76

Observer bias

Back 76

1- Pygmolion effect - Researcher beliefs the efficacy of the treatment changes the outcome of the treatment

2- Reduced - Double blinding

Front 77

Confounding bias

Back 77

1- Factors related to the exposure and outcome affects the exposure and outcome

2- Reduced 1- Multiple repeated study

2- Cross over studies

3- Matching

2-

Front 78

Lead time bias

Back 78

1- Early detection of a disease is confused with increase survival

Front 79

Lead time bias

Back 79

1- Early detection of a disease is confused with increase survival

2- Reduce- Measure back end survival

Front 80

Length time bias

Back 80

1- Screening test detect diseases with longer latency periods while those with shorter latency period become symptomatic earlier

2- Reduce - Randomized trials

Front 81

Name one type of study design which can help to eliminate confounding bias

Back 81

Cross over studies

Front 82

What type of studies are most likely to introduce recall bias

Back 82

Retrospective studies

Front 83

Matching in confounding bias

Back 83

Patients with similar characteristics are selected in both treatment and control groups

Front 84

Correct results

Back 84

Null hypothesis is not rejected

Front 85

Correct results

Back 85

Null hypothesis is not rejected

Front 86

Incorrect results

Back 86

Type 1 - alpha

Type 2- beta

Front 87

Type 1 error alpha

Back 87

1- There is an effect or difference when the non exist (failure to reject the null in favor of the alternative hypothesis)

2- Can not prove the alternative hypothesis

3- False positive error

4- Detecting a difference when non exist

Front 88

Type 2 error beta

Back 88

1- There is no effect or difference when non exist

2- false negative error

3- Power in number

4- Failure to reject the null hypothesis failure to accept alternative hypothesis

5- No difference when there is one

Front 89

Power in type 2 error (beta)

Back 89

1- How valise a study is

2- 1- beta decrease beta increase power

3- Power in numbers (increase sample size increase power)

Front 90

Power in type 2 error (beta)

Back 90

1- How valise a study is

2- 1- beta decrease beta increase power

3- Power in numbers (increase sample size increase power)

Front 91

P value

Back 91

= 0.05

Significant of a study

Front 92

What is the generally value of alpha in hypothesis testing

Back 92

0.05

Front 93

What are 3 ways the power of a study can be increased

Back 93

1- Increase sample size

2- Increase expected effect size

3- Increase precision of measurement

Front 94

What should be the relation of p and alpha for rejecting the null hypothesis

Back 94

If p

Null hypothesis is rejected as false

Front 95

Confidence interval

Back 95

1- Range of value in which the true mean of a population is expected to fall

Front 96

3 resins 95% CI not significant

Back 96

1- 95% CI of 2 variables include 0 - there is no significant difference (null hypothesis not rejected)

2- 95% CI of odds ratio and relative risk include 1- there is no significant difference

3- 95% CI of 2 group overlap - there is no significant difference

Front 97

3 resins 95% CI not significant

Back 97

1- 95% CI of 2 variables include 0 - there is no significant difference (null hypothesis not rejected)

2- 95% CI of odds ratio and relative risk include 1- there is no significant difference

3- 95% CI of 2 group overlap - there is no significant difference

Front 98

Increase sample size in CI

Back 98

Increase power

Decrease CI

Increase precision

Front 99

Calculating confidence interval

Back 99

+/- Z(SD/ square root of n)

Z- 1.96

N- size of population

Front 100

What is the value of Z if it reports a 99% confidence interval

Back 100

2.58

Front 101

T test

Back 101

1- Difference between mean of 2 group

2- Sample T test- 2 different groups

3- Paired T test- same individual

Front 102

T test

Back 102

1- Difference between mean of 2 group

2- Sample T test- 2 different groups

3- Paired T test- same individual

Front 103

ANOVA test

Back 103

Difference between mean of 3 or more groups

Front 104

Chi square x2

Back 104

1- Difference between 2 or more percentage or proportion of catigorical outcome ( no mean value)

2- Large population

Front 105

Fishers exact test

Back 105

1- Difference between 2 or more percentage or proportion of categorical nominal outcome

2- Small population