Biostatistics Flashcards

1
Q

LR > 1

A

Disease you’re worried about is more likely after test result

(Likelihood ratio > 1)

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2
Q

LR < 1

A

Disease of concern is less likely after test result

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3
Q

LR = 1

A

Pt likelihood of having disease hasn’t moved

(e.g. still β€œ30%” before and after test result)

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4
Q

LR = 10 is a very good _____

A

Rule-in test

(e.g. b-hCG, CT PE, β€œGold Standard” tests)

Higher LR = better for rule-ins

Closer to 0 = better for rule-outs

Closer to 1 = less useful

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5
Q

LR = 0.1 is a very good _____

A

Rule-out test (e.g. D-Dimer)

Higher LR = better for rule-ins

Closer to 0 = better for rule-outs

Closer to 1 = less useful

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6
Q

How often a test is right when people have the disease

A

Sensitivity

(True positive rate)

  • High sensitivity = low false negatives
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7
Q

How often the test is negative when people don’t have it

A

Specificity

(True negative rate)

  • High specificity = low false positives
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8
Q

Probability of the outcome of interest occuring in the exposed group compared to the probability of it occuring in the non-exposed group

A

Relative Risk (RR)

  • RR of 1.0 = null value (outcome occurs w/ equal frequency in both groups; no association btw exposure and outcome)
  • RR > 1.0 = positive association (outcome occurs more frequently in exposed group)
  • RR says nothing about the significnace of the study
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9
Q

95% confidence interval p value

A

p < 0.05 (Statistically significant)

  • Note: if p > 0.05, then the 95% confidence interval contains the null value (1.0)
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10
Q

99% confidence interval p value

A

p < 0.01

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11
Q

Proportion of pts with a negative test result who truly do not have the disease

A

NPV

Chance that a positive test is truly negative (# true negatives / total negative tests)

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12
Q

Proportion of pts with a positive test result who actually have the disease

A

PPV

Chance that a positive test is truly positive (# true positives / total positive tests)

true positives / # true positives + # false positives

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13
Q

The positive and negative predictive values of a diagnostic test are highly dependent on the ____

A

Prevalence of disease in the population

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14
Q

Sensitive tests rule in/out

A

Out

(SnOUT / SpIN)

  • High sensitivity = low false negatives = Negative test is reliable
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15
Q

Specific tests rule in/out

A

In

(SnOUT / SpIN)

High specificity = low false positives = Positive test is reliable

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16
Q

LR(+) values of 2, 5, and 10 correspond to an increase in disease probability by __, __, and __ respectively

A

15%, 30%, 45% increase in probability

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17
Q

LR(+) values of 0.5, 0.2, and 0.1 correspond to a decrease in disease probability by __, __, and __ respectively

A

15%, 30%, 45% decrease in disease probability

18
Q

The difference in risk attributable to the intervention when comparing placebo and intervention groups

(Placebo rate - intervention rate)

A

Absolute Risk Reduction (ARR)

Absolute Risk of A - Absolute Risk of B

  • NNT = 1/ARR
19
Q

NNT

A

1/ARR = 1/(Absolute Risk of A - Absolute Risk of B)

20
Q

The absence of a control group would affect a study’s ____

21
Q

The post-test probability is dependent on these 4 things

A
  1. Sensitivity
  2. Specificity
  3. Pre-test probability
  4. PPV
22
Q

Cases are selected from the entire disease population instead of just those who are newly diagnosed

A

Selective survival bias

(because study not limited to newly diagnosed pts will contain a higher proportion of relatively benign disease as these pts generally live longer)

23
Q

People in a study who have suffered an adverse event are more likely to recall risk factors than those without such experiences

A

Recall Bias

24
Q

Randomization is used to control for ____

A

Confounding

25
Methods to control confounding
* Randomization * Matching (levels of a confounder between groups) * Restriction (e.g. only men) * Stratified analysis * Statistical modeling (e.g. multivariate analysis)
26
Tight confidence interval
**Precision** | (low random error)
27
False Positive Rate
**1 - Specificity** * High specificity = Low false positive rate
28
False Negative Rate
**1 - Sensitivity** * High sensitivity = low false negative rate
29
Indicates how well a test can screen for disease
**Sensitivity**
30
Indicates how well a test can confirm the diagnosis
**Specificity**
31
The proportion of true results (true positives and negatives) out of all the results of a given diagnostic test
**Accuracy**
32
Increasing a diagnostic test's cutoff value will ___ the sensitivity and ___ the specificity
* Decrease the sensitivity (more false negatives) * Increase the specificity (less false positives)
33
A study's ability to detect a difference between groups, if one exists
**Power**
34
The number of people that need to receive a treatment to prevent 1 additional adverse event
Number Needed to Treat (NNT) ## Footnote **1/ARR**
35
Comparing two means: T test vs. Z test
Two-sample **T test** - compares means using **sample variances** Two-sample **Z test** - compares means using **population variances**
36
The alteration of behavior by the subjects of a study due to their awareness of being observed
**Hawthorne Effect**
37
Unlike sensitivity & specificity, PPV and NPV depend on \_\_\_\_
The **prevalence** of disease in the population being tested However, _changing cutoff point_ of a diagnostic test affects all four
38
Atrributable Risk Percent (ARP) is easily derived from
**Relative Risk** ARP = (RR-1)/RR
39
Generalizability
**External validity** Applicability of study results to other populations
40
"A new screening test" - Think of this type of bias
**Lead-time bias** Prolongation of apparent survival in patients to whom a test is applied, without changing the prognosis of the disease
41
Statistical test used to compare **3 or more** groups using discrete or nominal (**categorical**) variables
**Chi-Squared Test**
42
Statistical test used to compare **3 or more** groups using **continuous** (numerical) variables
**ANOVA**