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Step 2 > Biostats HY > Flashcards

Biostats HY Flashcards

1
Q

Give an intervention to one group and give placebo to other group then compare /record outcomes

A

Random Controlled Clinical Trial
(RCT)

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2
Q

Compare group of ppl with an uncommon dz (or characteristic) and a group of ppl w/o the dz and look back in time for exposures

A

Case-Control
(calculate odds Ratio)

Cohort is opposite it looks at exposure first then future dz.
Case control looks dz first then back in time for exposure!

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3
Q

prominent issue with Case Control Studies?

A

Recall Bias

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4
Q

To do a study on a rare phenomena (or disease)
_____ studies are typically the best option on NBME exams.

A

case-control study

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5
Q

Which study looks at 2 groups; one with a risk factor/exposure and one w/o risk factor and then follow into future to see if they develop a particular outcome (disease/adverse effect)

A

Cohort studies

(calculate relative risk)

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6
Q

Lower P value (<0.05) = higher (2)

A

confidence & power
(that results are not by chance)

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7
Q

which P-value is better?

P<0.05 or <0.01?

A

P<0.01

means 1% chance that results were due to chance

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8
Q

__% of population with normal distribution should fall within 2 Standard deviations below & above of the mean (average)

A

95%
Example: SD is 100 and mean is 1000.
2SD below mean = 800
2SD above mean = 1200
95% of population falls within 800-1200
5% must fall outside this range
2.5% less than 800
2.5% higher than 1200

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9
Q

95% of population with normal distribution should fall within __ Standard deviations below & above of the mean (average)

A

2
Example: SD is 100 and mean is 1000.
2SD below mean = 800
2SD above mean = 1200
95% of population falls within 800-1200
5% must fall outside this range
2.5% less than 800
2.5% higher than 1200

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10
Q

__% of population falls outside 2 Standard deviations below & above of the mean (average)
___% falls above 2 SD of average
___% falls below 2 SD of average

A

5%
2.5% above 2SD of mean
2,5% below 2SD of mean

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11
Q

Whenever you have 2 confidence intervals overlap in value (or cross each other) that means results are

A

not significant

(no difference in effectivity between those two things)

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12
Q

In Ratio derived confidence intervals (Relative risk, Odds ratio) if the confidence interval includes (crosses) the number ___ = not significant

A

1

(can get ONE, if you divide two of the SAME number)

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13
Q

In Difference derived confidence intervals (Average/ percents/proportions, RRR, Attributable Risk, ARR) if the confidence interval includes (crosses) the number ___ = not significant

A

0

(can get zero, if you subtract two numbers that are the SAME)

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14
Q

3 Rules for figuring out what a value’s Confidence interval is.
Example: Confidence interval of a Relative Risk of 3.5

A
  1. Is it a ratio or a difference?
    Relative risk is a ratio so CI can’t include #1 (eliminate those ans)
    ARR is a difference so CI can’t include #0
  2. Value cannot start or end the CI
    (ex: confidence interval can’t start or end with 3.5)
  3. Value must fall within the CI range of numbers & be nearest the center of the range.
    (eliminate all ans that do not include 3.5 within the range)

CI must include the value (ex: 3.5) at the center within the range of numbers, but the value must not start or end the interval and the interval can’t include the number 1 or 0

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15
Q

Calculate Number Needed to Treat & ARR

A

ARR = (% of pts who died getting DRUG) minus (% of pts who died getting PLACEBO)
──

NNT= 1 ÷ ARR

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16
Q

Calculate Number Needed to Harm

A

1 ÷ (% of pts harmed by Placebo) minus (% of pts harmed by Drug)

NNH= 1 ÷ AR

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17
Q

Calculate Relative Risk

& Relative Risk Reduction (Decreased Relative Risk)

A

Relative Risk
(% exposed/intervention + dz) ÷ (% unexposed/control + dz)

(ex: 20% of smokers got Lung cancer/ 10% nonsmoker got lung cancer = 2 → aka smoking increases risk of lung cancer 2-fold)
─
RR = rate of outcome in exposed/ rate of outcome of control
RRR= (1– RR)

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18
Q

What is the Positive & Negative Likelihood ratio formula?

A

Positive= (Sensitivity/1– Specificity)
Negative= (1– Sensitivity/Specificity)

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19
Q

When to use the positive or negative likelihood ratio on exam to calculate correct answer?

A

+ve LRs tell you how much more likely a phenomenon is when you have a +ve test result.

-ve LRs tell you how much less likely a phenomenon is when you have a -ve test result.

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20
Q

Quick way to calculate Odds ratio

A

Odds ratio
(Expected Outcomes )÷ (Odd Outcomes)
─

Expected: (exposed got disease) x (unexposed no disease)
÷
Odd: (exposed no disease) x (unexposed got disease)

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21
Q

How to Calculate Confidence Interval

A

90% Z-Score = 1.5
95% Z-Score = 2
99% Z-score = 2.5

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22
Q

ROC curves (how well a test can distinguish b/w 2 groups)
The best test (highest sensitivity & specificity) lies at the _____ of the graph.

A

top left corner

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23
Q

Cohort study, 2 groups of individuals are initially identified as “exposed” or “nonexposed” according to their exposure status to a specific risk factor and then followed into future to assess development of the outcome (incidence of disease).

A

Case-Control = 1 Uncommon diseases are followed back in time to assess exposure(s)

Cohort = Exposures are followed into future for development of common diseases

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24
Q

68%, 95%, and 99.7% of a normal population lie b/w __, __, & __ SDs of the mean respectively.

A

1 (68% → 16%)
2 (95% → 2.5%)
3 (99.7%)

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25
Q

Both test require measuring a quantitative (numerical) outcome
Between 2+ qualitative (Intervention/Risk Factor) groups

compares means of 2 groups, ___ test.
compares means of 3+ groups, ___ test.

A

T test
ANOVA (or F) test

Chi test has qualitative terms for both intervention and outcome

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26
Q

When you incorrectly reject the null
(state there is an effect when there is not an effect)
= a Type __ error.

A

Type 1 error (alpha error)

(aka false positive error)

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27
Q

When you incorrectly accept the null
(state there is no effect when there is an effect)
= a Type ___ error.

A

Type 2 error (beta error)

(aka false negative error)

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28
Q

Power = ___

A

1– beta

Statistical power is the probability of stating that there is an association & it’s actually true.

(aka rejecting a false null hypothesis)

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29
Q

Narrower CIs tell you study is more ___.

A

precise

However, you should feel a lot less confident in the results of the study bc the CIs are too narrow (less room for error).

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30
Q

Ways to Increase the power of a study (HY!)

A

Studies with larger sample sizes have greater statistical power, consequently a lower probability of a type II error

  1. Recruit more people for a study (larger sample size).
  2. Have a large difference b/w 2 quantities you’re trying to measure (larger effect size).
  3. Increase measurement precision (how consistent values are)
  4. lower P values = more power (P<0.01)
  5. Increase data for a measured qty cluster around 1 value.
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31
Q

FYI

A

The fact that something is statistically significant does not mean that it is clinically significant

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32
Q

study compares 2+ treatment on one pt and allows them to serve as own controls

A

Crossover study

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33
Q

This test has
2 groups divided by
≥2 categorical/qualitative factors
(exposure or intervention)
and measure the categorical/qualitative outcome
observed in each group

A

Chi squared test

Qualitative = characteristic
Quantitative = numerical values (Temp, BGL, Percentages)

34
Q

Mean is the average.

Median represents:
1. the ___ #
2. the ___#s

Mode represents the # that ____ in the data set

TIP Arrange data in ascending/descending order before making these determinations.

A

Middle # (odd # data set)
Avg of the 2 middle #s (even # data set)

Mode = # that is repeated most

35
Q

For a normal distribution, _____

A

mean = median = mode

36
Q

HY
bimodal distributions found in (3 illnesses)

A

Hodgkin’s lymphoma
Suicide
slow/fast acetylators in metabolism

37
Q

erroneously thinking that survival has been improved when in fact the “apparent survival improval” arose bc you found disease earlier.

A

Lead time bias

38
Q

80% sensitivity = 20% ____ test result

A

False negative test result

(tested negative but have dz)

39
Q

Screening test: High _____ test if Negative rules out dz
Confirmatory test: High ____ test if Positive rules in dz

A

High Sensitivity test if Negative rules out dz (SN-N-OUT)
High Specificity test if Positive rules in dz (SP-P-IN)

40
Q

Of all the population with the disease what % will have a (+) test result = ___

A

Sensitivity

High seNsitivity = Low False Negative rate

Missed ones are False Negative
(pt has disease, but result was negative)

41
Q

Of all the population without the disease, what % have (–) test results = ___

A

Specificity

A highly sPecific test has a low false Positive rate.

42
Q

90% specificity = 10% ____ test result

A

False positive test result

(tested + but have no disease)

43
Q

Which of the following points best represents the spot with the highest positive predictive value (PPV)

(aka % of people with +ve tests who have disease)

A

C
The highest PPV region on a graph, corresponds to the region with the highest sPecificity (C)

44
Q

Sensitivity of a test represents the (% of pts with disease) & have _____

PPV of a test represents the (% of pts with +ve test) & have _____

A

(+ve test result)
→ SN = % of ppl w/dz the test marks positive

(disease)
→ PPV= % of True Positives the test reports

45
Q

Equation for calculating Sensitivity

A

Sensitivity = (True Positive Test)/ (TP test + FN test)

aka (# of diseased & [+] test ) over (# of diseased regardless of test result)

46
Q

Equation for calculating Specificity

A

Specificity = (True Negative test)/ (TN test + FP test)

aka (# of healthy & Neg test) over (# of healthy regardless of test result)

47
Q

Equation for calculating PPV%

A

PPV= (TP test)/ (TP test + FP test)

aka [# of pts w/ (dz & + test)] over [total # of positive test regardless if true or not]

NPV= TN/(TN+FN)

48
Q

Which of the following points best represents the region of the graph with the highest negative predictive value (NPV)

(aka % of healthy pts w/ NEG test results)

A

B
The highest NPV region on a graph, corresponds to the region with the highest seNsitivity (B), which corresponds to the region that DOES NOT miss anyone with disease.

49
Q

Specificity of a test represents the % of people ____

NPV of a test represents the % of people ____

A

SPECIFICITY: % people (w/o disease) who have (–ve test results)

NPV: % people with (-ve test results) who are (w/o disease).

50
Q

Lowering cutoff value dose what (6)

A

Lowering cutoff (B → A)
↑ SN & NPV & FP
↓ SP & PPV & FN

51
Q

Increasing the cutoff value dose what (6)

A

Increasing cutoff (B → C)
↑ SP & PPV & FN
↓ SN & NPV & FP

52
Q

As Prevalence goes up, ____ should increase too

A

PPV

53
Q

As Prevalence goes up, ____ should decrease

A

NPV

(Inversely related PPV/NPV)

54
Q

Can Prevalance change Sensitivity or Specificity of a test?

A

No

(but changing cut off values can)

55
Q

Prevalence vs Incidence

A

Prevalence counts at all current cases of dz in total population (live longer stay in population longer incr prevalence)

Incidence counts all new cases in the total population

56
Q

Prevalence decreases with (4)

A

increased mortality
faster recovery
more vaccine/prevention
Lowering risk factors

57
Q

incidence decreases with (2)

A

more vaccine/prevention
lowering risk factors

58
Q

TIP place Mean, Median, Mode in alphabetical order.
This should help you remember that:

in a Negatively skewed curve (flat portion on the ___): ____
in a Positively skewed curve (flat portion on the ___): _____

A

Flat left → mean < median < mode.

Flat Right → mean > median > mode.
───
notice how arrow head’s (<) flat part points in direction of the skew’s flat part

59
Q

Case-control studies can consider only ____ per study but can evaluate exposure to several risk factors.

A

1 outcome (ie, disease)

60
Q

3 actions used to control for confounding variables during the design stage of a study.

A

Randomization
Matching (same # of pts w & wo risk factor)
Restriction (participation criteria)

61
Q

Nonrandom treatment assignment may lead to ___ bias

A

selection bias

62
Q

Stratified analysis of the extraneous variable can help distinguish whether that variable is a confounding bias or an effect modifier.

It is a confounding bias if ______.

A

Stratified analysis of both groups yields similar RR (relative risk) no significant difference

If RR between 2 groups are significantly different → Effect Modifier

63
Q

Because cohort studies measure incidence of disease, they provide a measure of

A

relative risk of disease

64
Q

A case-control study compares the exposure status of people with & w/o a disease (ie, cases), they provide a measure of

A

odds ratio

65
Q

Types of studies:
A) 2 groups: Disease & no disease
B) 2 groups: Exposed & not Exposed
C) 2 groups: All subjects have disease or don’t have dz (risk factor and outcome are measured simultaneously)

A

A) Case control
B) Cohort
C) Cross Sectional

66
Q

By raising the cutoff value, it is harder to get a ___ test result and easier to get a ___ test result.

A

Harder: positive test result ( ↓ False Positives)

Easier: negative test result ( ↑ False Negatives)

67
Q

Equation for Accuracy
(probability that an individual will be correctly classified by a test)

A

(True positives + True negatives) / Total number of individuals tested

68
Q

probability of *having** the disease if pt gets negative test results.

vs not having the disease if pt gets positive test results

A

100 – NPV

100- PPV

69
Q

Increasing the CI from 95% to 99% does what to the range of numbers?

A

Makes the range larger/wider

Mean 7 → 95% CI= 4–10
Mean 7 → 99% CI= 2– 12

70
Q

P value of <0.05 in words mean

A

If there is no real difference between 2 groups, there is a 5% chance of finding a difference

71
Q

The probability/likelihood that a patient with a negative test result truly does not have the disease.

A

Negative predictive value (NPV)

72
Q

ANOVA test
If p-value is greater than alpha (α) the results are ____.

A

Not significant (no difference/are similar)

if p-value less than α → significant (difference exists)

73
Q

correlation coefficient (r)
r < 0 =
r > 0 =

A

(NEG correlation #) as one variable increases, the other variable decreases

(POS correlation #) both variables increase (or decrease) together.

74
Q

Increasing power
(guess before flipping card)

A
75
Q

In a NORMAL DISTRIBUTION
Pt’s above/below the mean by
1SD → is within the __% of the distribution.
2 SD → is within the __% of the distribution.
3 SD → is within the __% of the distribution.

A

68%
95%
99.5%

76
Q

The narrower the confidence interval range is, the more ____ the test/results are.

A

precise

(FYI: Increasing the sample size increases the precision of the study, but does not affect accuracy.)

77
Q

The best diagnostic accuracy represents the

A

best compromise between highest sensitivity & specificity

(aka top left corner of ROC curve)

78
Q

Odds Ratio cannot establish

A

risk (increase nor decrease)

79
Q

Calculate Absolute risk reduction (ARR) & Attributable Risk (AR)

A

ARR = (Intervention % outcome) – (Control % outcome)

AR = (Control % outcome) – (Intervention % outcome)

80
Q

A ___ study design is best for determining the incidence of a disease.

What about prevalance?

A

cohort

Prevalence = Cross-Sectional

81
Q

A ___ study is best for determining odds of developing a disease.

A

Case-control

82
Q

The typical example of lead-time bias is prolongation of apparent survival in patients to whom a test is applied, without changing the prognosis of the disease.

A

FYI

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