EBM

Question 1

External Validity

Answer 1

The confidence with which the results can be accurately generalized to the population

Question 2

What do Inclusion and Exclusion Criteria do to validity?

Answer 2

Improves internal validity by controlling variability

Decreases external validity by limiting generalizability

Question 3

Probability Sampling

Answer 3

When each member of the population has a known chance to be included in the research

Question 4

Stratified random sampling

Answer 4

To ensure that critical variables are represented in the sample, subjects are stratified by traits and then randomly sampled

Question 5

Systematic sampling

Answer 5

A type of random sampling done when subjects are put in order. For example, the 3rd person from each letter of the alphabet can be chosen. Can incorporate stratification if there is a meaningful order (i.e. Weight or age)

Question 6

Purposive sampling

Answer 6

Hand-picked patients. Purpose might be to gather different perspectives

Question 7

Quota sampling

Answer 7

Convenience sampling, with specific quotas included. This is like stratification

Question 8

Healthy-User Bias

Answer 8

May occur with convenience samples because healthier people are more likely to volunteer, or be seeking healthcare

Question 9

Berkson’s Bias

Answer 9

Population selected from an impaired or diseased group (like hospitalized pts)

Question 10

Exclusion Bias

Answer 10

Excluding patients with certain characteristics. I.e comorbidities, racial groups, socioeconomic groups, people who have dropped out of a study

Question 11

Internal validity

Answer 11

Internal health of the study. How free it is from bias and chance.

Question 12

External validity

Answer 12

The degree to which you can generalize the results of the study back to the population of interest.

Question 13

How to prevent selection bias

Answer 13

Random or stratified random assignment

Equivalence can be double-checked for suspicious factors by obtaining relevant demographic or baseline data

Question 14

Extraneous factors

Answer 14

Other variables in the study that may affect the relationship between the independent and dependent variables

Example: Researchers examined whether relaxation therapy was better than drug therapy for reducing the number of tension headaches in medical students.
Extraneous Factors to control or account for
1.   Diet
2.  Other medications
3.  Severity of tension headaches

Question 15

Measurement bias

Answer 15

Occurs when measurements are made unequally between treatment groups

Question 16

Confounding bias

Answer 16

Occurs when 2 factors are associated and the effect of one is confused with or distorted by the effect of the other

Question 17

Investigator bias

Answer 17

When the investigator ‘knows’ the expected results, so the investigator treats groups differently

Question 18

Allocation concealment

Answer 18

Prevents investigator bias. The ppl randomizing individuals into groups are blinded as to which subjects go into which group. E.g. Subjects are given numbers (de-identified from researcher) or a 3rd party interacts with subjects during allocation

Question 19

Investigator blinding

Answer 19

Prevents investigator bias. E.g. Investigator who is providing treatment or making measurements is blinded as to the group.

Question 20

Hawthorne effect

Answer 20

Subject bias where people change behavior in a study. Effects both internal and external validity

Question 21

Subject blinding

Answer 21

Solution to hawthorne effect
Placebo group
Subjects don’t know what group they’re in
BUT blinding doesn’t work for long if there is an obvious physical change

Question 22

Absolute risk

Answer 22

Incidence
# of ppl with disease/total number of people at risk for getting disease

Question 23

Relative Risk/Risk Ratio

Answer 23

‘How many times more likely are exposed persons to get the disease relative to non-exposed persons?’

• Incidence in exposed/incidence in unexposed
• Common metric in studies with similar risk factors but with different baseline incidence rates.

Question 24

Cross-over trials

Answer 24

Advantages:

1. Subjects are their own controls, which reduces inter-subject variability
2. Randomization removes order effect
3. Statistical advantages

Disadvantages:

1. Inappropriate when time has an effect (e.g. Recovery from surgery)
2. Inappropriate when order effect is lasting

Question 25

Absolute Risk Difference/attributable risk

Answer 25

How much extra disease is actually caused by an exposure or risk factor Subtract absolute risk of unexposed from absolute risk of exposed

Question 26

Relative Risk

Answer 26

Ratio between absolute risk of exposed and absolute risk of non exposed I.e. Ratio between incidence of exposed and incidence of non exposed

Question 27

"Big Data" Studies

Answer 27

Subtype of retrospective cohort Very large N Data from various sources, though gathered usually without medical intent (billing) -BEST method for looking for rare side effects or outcomes

Question 28

Case Control Studies

Answer 28

- generally involves interviewing - Cases: newly-incident (optimally) cases of target disease - Controls: ppl without target disease who 'had the opportunity' to get exposed, and also in other ways similar to pts. - Controls are the hardest parts of case-control design - Case control outcomes are usually odds ratio - ratio bw odds of exposure in cases/odds of exposure in controls - very close to relative risk if rate in unexposed people is <1%

Question 29

Odds ratio

Answer 29

Ratio between the odds of exposure in cases and the odds of exposure in controls

Question 30

Case series

Answer 30

No controls NOT population-based Best for describing emergent diseases, rare outcomes, odd exposures Sometimes the best evidence available

Question 31

Misclassification bias

Answer 31

Example: Overworked medical assistants often forget to ask patients whether or not they use alternative medicines and simply check “No” in the electronic medical record. You are studying the effect of alternative medicines on the later development of liver failure. Pts that are actually taking these medications are classified as not taking them, so somebody could be taking these meds, be misclassified, then develop liver disease, so this bias is therefore increasing likelihood for type II error, where you say there isn't a difference, then there is one

Question 32

Compliance bias

Answer 32

People that are compliant with one thing tend to be compliant with other things that are thought to be good for them, causing confounding things

Question 33

Lead-time bias

Answer 33

Common problem in screening studies: if you LOOK for something, you'll tend to find it sooner, than if you wait for it to cause symptoms -pt will live longer with diagnosis even if intervention had no effect

Question 34

Prevalence

Answer 34

Number of people in a population who have a disease at a given time -If illness is chronic, over time prevalence will rise even if incidence is small -Effective treatment can delay mortality and thus increase prevalence -Diseases with high and rapid mortality (even if disease has high frequency) may have low prevalence because most die quickly -High prevalence could reflect better treatment and longer survival

Question 35

Absolute risk reduction

Answer 35

Difference in disease between 2 groups; but usually used in a treatment sense as opposed to an exposure sense. -How much disease can be prevented/reduced with a given treatment? NNT= 1/ARR

Question 36

Number Needed to Treat

Answer 36

1/Absolute Risk Reduction OR 100/ARR Ex: If a cancer treatment reduces mortality from 50% in untreated group to 40% in treated group, the Number needed to treat would be: 1/ (0.5 - 0.4) = 1/0.1 = 10. You need to treat 10 people with the drug to prevent 1 cancer death.

Question 37

If RR<1

Answer 37

Adverse outcome is decreased by treatment compared to control

Question 38

If RR>1

Answer 38

Adverse outcome is increased by the treatment compared to control

Question 39

If RR=0.5

Answer 39

The chance of a bad outcome is half as likely to occur with treatment as without it

Question 40

RR=1

Answer 40

Risk is same in both treatment and control groups

Question 41

Relative Risk Reduction

Answer 41

How much the treatment reduced the risk of bad outcomes relative to the control group who did not have the treatment [[[[[ Control event rate (#not exposed with disease/total not exposed) MINUS Experimental event rate (#exposed w. Disease/total exposed) ]]]]] OVER Control event rate

Question 42

Number needed to harm

Answer 42

100/Absolute risk %

Question 43

Sensitivity

Answer 43

How well can test detect disease | -True positive/Total with disease

Question 44

Specificity

Answer 44

How well can the test detect the absence of disease | -True negative/Total people without disease

Question 45

Pre-test probability

Answer 45

Prevalence | Varies with population/patient

Question 46

Positive Predictive Value

Answer 46

Of all ppl with positive test, which % actually have disease?

Question 47

Likelihood Ratio

Answer 47

Likelihood of certain test result in pt with disease OVER Likelihood of same test result in pt without disease

Question 48

Likelihood ratio for a + test

Answer 48

Likelihood of + result in diseased pop/likelihood of same in non-diseased pop = Sensitivity/1-specificity

Question 49

Likelihood ratio for a - test

Answer 49

Likelihood of - result in diseased pop/likelihood of same in non-diseased pop 1-sensitivity/specificity

Question 50

Hazard ratios

Answer 50

Evaluate one prognostic factor at a time (i.e. How big was the primary tumor?) - Similar to relative risk: Ppl with prognostic factor Y are X times more likely to die than ppl without this factor - Assumes that ratio between 2 prognostic curves is fairly stable over time

Question 51

Primary Prevention

Answer 51

- before exposure - sanitation - nutrition - immunization - education

Question 52

Secondary Prevention

Answer 52

- after exposure - early detection (Screening) - early intervention

Question 53

Tertiary Prevention

Answer 53

- after disease process begins - reverse course of disease - rehabilitation - treatment

Question 54

When is it okay to screen?

Answer 54

- If disease has significant morbidity/mortality - Prolonged asymptomatic phase - Effective treatment available - High prevalence in particular pt population - If pt accepts test - If pt can comply to treatment after result of test - If test has good sensitivity/specificity - If test is valid and reliable - If it's cost-effective

Question 55

Length-time bias

Answer 55

Slower growing tumors that are less likely to kill are more likely to be detected by one time/periodic/interval screening

Question 56

68-95-99. Rule

Answer 56

-shorthand used to remember the percentage of values that lie within a band around the mean in a normal distribution with a width of one, two and three standard deviations, respectively; more accurately, 68.27%, 95.45% and 99.73% of the values lie within one, two and three standard deviations of the mean, respectively.

Question 57

Variance and it's relationship to standard deviation

Answer 57

Variance is the square of SD S2= Sum of(X-M)2 / N-1 Where X=value and M=mean

Question 58

Standard Error

Answer 58

A measure of how far the sample mean is away from the population mean SEM= SD/sqrt(N) Used to show variability caused by experimental imprecision WHEREAS SD is used to show biological variability

Question 59

Relationship bw Alpha and Type 1 Error

Answer 59

As alpha decreases (say, from 0.05 to 0.01 ---> 95% confidence to 99% confidence), chance of type 1 error DECREASES

Question 60

Relationship between Alpha and Type II Error

Answer 60

As alpha decreases, the chance for Type II errors increases (I.e., as you make your confidence interval wider, you're more likely to say there isn't a difference when there is indeed a difference.)

Question 61

Random Error

Answer 61

Caused by inherently unpredictable fluctuations in the readings of a measurement apparatus or in the experimenters interpretation of the instrumental reading. This error can occur in either direction.

Question 62

Systematic Error

Answer 62

Is predictable Typically consistent or proportional to the true value. Causes by imperfect calibration of measurement instruments or imperfect methods of observation. Usually occurs only in 1 direction.

Question 63

Student T Test

Answer 63

``` Assumptions: N<30 Random sampling Equal sample size Most useful when comparing 2 sample means ``` T= M1-M2 / sqrt[(SE1)sq + (SE2)sq] Want the highest # T as possible, because T represents difference between the means. Large T indicates small variability and high signal. If T>critical T, then there is a clinically significant difference.

Question 64

1 Tailed T Test vs 2 Tailed T Test

Answer 64

1 Tailed: A one-tailed test will test either if the mean of exp group is significantly greater than control group (x) or if the mean is significantly less than x, but not both. The one-tailed test provides more power to detect an effect in one direction by not testing the effect in the other direction. 2 Tailed: A two-tailed test will test both if the mean is significantly greater than x and if the mean significantly less than x. The mean is considered significantly different from x if the test statistic is in the top 2.5% or bottom 2.5% of its probability distribution, resulting in a p-value less than 0.05. 2-tailed is more robust.

Question 65

Paired vs Unpaired T Test

Answer 65

Paired -The observed data are from the same subject or from a matched subject and are drawn from a population with a normal distribution. Example: Measuring glucose concentration in diabetic patients before and after insulin injection. Unpaired The observed data are from two independent, random samples from a population with a normal distribution. Example: Measuring glucose concentration of diabetic patients versus non- diabetics.

Question 66

ANOVA

Answer 66

Used to compare 3 or more means. Analyzes by using sum of squares. -tells us that the smallest and largest means likely differ from each other

Question 67

Mann Whitney U Test

Answer 67

- Nonparametric alternative to 2-sample T-test - Actual measurements not used- instead, ranks are used - USE THE LOWER OF THE 2 U STATISTICS

Question 68

Kruskal-Wallis Test

Answer 68

- Nonparametric equivalent of a 1-way ANOVA on ranks | - used for comparing 2 or more independent samples of equal or different sample sizes

Question 69

Calculating Chi Square

Answer 69

Expected value for box= (Total in row * Total in column) / N Participants Degrees of freedom= (rows-1)(columns-1) Calculated X2 should be > Critical value X2= sum of[(obs-exp)sq /expected]