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NAPLEX > Chapter 14: Biostatistics > Flashcards

Chapter 14: Biostatistics Flashcards

1
Q

Continuous Data

A

Can be ratio data or interval data

Continuous data has a logical order with values that continuously increase or decrease by the same amount

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2
Q

Ratio Data

A

Equal distance between values with a true, meaningful 0
(0=none)

E.G. age, height, weight, time, blood pressure

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3
Q

Interval Data

A

Equal difference between values but without a meaningful 0
(0=/ none)

E.G. Celsius and Fahrenheit temperature scales

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4
Q

Discrete or Categorical Data

A

Can be nominal data or ordinal data

Discrete data fits into a limited number of categories

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5
Q

Nominal Data

A

Categories are in an arbitrary order. Order of categories does not matter

E.G. gender, ethnicity, marital status

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6
Q

Ordinal Data

A

Categories are ranked in a logical order, but the difference between categories is not equal. Order of the categories matters.

E.G. NYHA functional class I-IV, 0-10 pain scale

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7
Q

Independent Variables

A

Are variables changed by the researcher

Include: drugs, drug doses, placebos, patients included (gender, age, comorbid conditions)

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8
Q

Dependent Variables

A

Can be affected by the independent variables

Include: HF progression, A1C, blood pressure, cholesterol values, mortality

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9
Q

Null Hypothesis

A

States that there is no statistical difference between groups

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10
Q

Alternative Hypothesis

A

States that there is a statistical difference between the groups. This is what the researcher is trying prove or accept.

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11
Q

Alpha

A

Is the maximum permissible error margin.

Alpha is the threshold for rejecting the null hypothesis and is commonly set at 5% or 0.05

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12
Q

P-values

A

P-value is compared to alpha. If alpha is set to 0.05 and the p-value is less than 0.05 then the null hypothesis is rejected and the result is termed statistically significant

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13
Q

Confidence Interval (CI)

A

CI provides the same information about significance as the p-value, plus the precision of the result. Alpha and CI will correlate with each other.

For example if alpha is 0.05 the study reports a 95% CI; and alpha of 0.01 corresponds to a CI of 99%

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14
Q

Confidence Interval (CI) Significance

A

The result is statistically significant if the CI range does not include 0 when comparing difference data (means)

The result is statistically significant if the CI range does not include 1 when comparing ratio data (relative risk, odds ratio, hazard ratio)

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15
Q

Type I Errors

A

Null hypothesis is rejected in error

“False Positive”

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16
Q

Type II Errors

A

Null hypothesis is accepted when it should have been rejected.
“False Negative”

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17
Q

Study Power

A

Power is the probability that a test will reject the null hypothesis correctly (i.e. the power to avoid a type II error)

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18
Q

Risk Formula

A

Risk refers to the probability of an event, when an intervention, such as a drug, is given

Risk= # of subjects is a group with an unfavorable event/ total # of subjects in group

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19
Q

Relative Risk

A

Is the ratio of risk in the exposed group (tx group) divided by risk in the control group

RR= risk in tx group/risk in control group

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20
Q

RR Interpretation

A

RR = 1 implies no difference in risk of the outcome between groups
RR > 1 implies greater risk of the outcome in tx group
RR < 1 implies lower risk (reduced risk) of the outcome in tx group

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21
Q

Relative Risk Reduction

A

Indicates how much risk is reduced in the tx group compared to the control group

RRR = 1 - RR
or
RRR = % risk in control - % risk in tx / % risk on control

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22
Q

RR vs RRR

A 
RR = AS likely (vs. the control)
RRR = Less likely (vs. control)
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23
Q

Absolute Risk Reduction

A

Is more useful because it includes the reduction in risk and the incidence rate of the outcome

ARR = % risk on control - % risk in tx

24
Q

ARR interpretation

A

For example is ARR is 12%; 12 out of every 100 patients will benefit from tx. Said another way, for every 100 patients treated, 12 patient will benefit.

25
Q

Number Needed to Treat (NNT)

A

NNT is the number of patients who need to be treated for a certain period of time in order for one patient to benefit.

NNT = 1/ARR

26
Q

NNT Interpretation

A

If NNT is 9 then for every 9 patients treated for 1 year, 1 patient will benefit

27
Q

Number Needed to Harm (NNH)

A

NNH is the number of patients who need to be treated for a certain period of time in order for one patient to experience harm.

NNH = 1/ARR

28
Q

NNH Interpretation

A

If NNH is 90 then one additional patient will be harmed for every 90 patients taking tx

29
Q

Hazard Ratio (HR)

A

A hazard rate is the rate at which an unfavorable even occurs within a short period of time

HR = hazard rate in tx/hazard rate in control

30
Q

Odds Ratio (OR)

A

Odds ratio is used to calculate the odds of an outcome occurring with an exposure compared to the odds of the outcome occurring without exposure

31
Q

OR and HR interpretation

A

OR or HR = 1 the event rate is the same
OR or HR > 1 the event rate in the tx group is higher than the even rate in the control group
OR or HR < 1 the event rate in the tx group is lower than the event rate in the control group

32
Q

Type of Statistical Tests for Continuous Data: T-Test

A

T-Test is used when the endpoint has continuous data and the data is normally distributed.

33
Q

Type of Statistical Tests for Continuous Data: One-sample t-test

A

-When data from a single sample group is compared to data from general population a one-sample t-test is used

34
Q

Type of Statistical Tests for Continuous Data: Paired T-test

A

When a single sample group is used for pre/post measurements a paired t-test is used

35
Q

Type of Statistical Tests for Continuous Data: Analysis of Variance (ANOVA)

A

ANOVA is used to test for statistical significance for continuous data with 3 or more sample groups

36
Q

Type of Statistical Tests for Categorical or Discrete Data: Chi-Square test

A

Used to determine statistical significance between treatment groups
One group uses chi-square
Two groups use chi-square or fisher’s exact

37
Q

Sensitivity

A

The true positive

38
Q

Specificity

A

The true negative

39
Q

Intention to Treat Protocol

A

Analysis includes data for all patients originally allocated to each treatment group even if the patient did not complete the trial according to trial protocol

40
Q

Types of Studies from Most Reliable to Least Reliable

A
  • Systematic Review and Meta-Analysis
  • Randomized Controlled Trials
  • Cohort Studies
  • Case-controlled Studies
  • Case Series and Case Reports
  • Expert Opinion
41
Q

Case-Control Study

A

Compares patients with a disease (cases) to those without the disease (control).
Outcomes are already known and researcher looks back retrospectively

42
Q

Cohort Study

A

Compares outcomes of a group of patients exposed and not exposed to a treatment.
The researcher follows both groups prospectively

43
Q

Case-Report and Case-Series

A

Describes an adverse reaction or a unique condition that appears in a single patient (case report) or a few patients (case series)

44
Q

Randomized Controlled Trial

A

Patients are randomized (have an equal chance) of being assigned to treatment or control group.
Studies can be blinded or double-blinded

45
Q

Meta-Analysis

A

Combines results from multiple studies in order to develop a conclusion that has greater statistical power than is possible from the individual studies

46
Q

Systematic Review

A

Summary of the clinical literature that focuses on a specific topic or question

47
Q

Direct Medical Costs

A

Drug preparation and administration, office visits, hospital bed etc

48
Q

Direct Non-Medical Costs

A

Travel and lodging, elder or childcare costs, home health aides

49
Q

Indirect Costs

A

Lost work time, low work productivity, morbidity and mortality

50
Q

Intangible Costs

A

Pain, suffering, anxiety and fatigue

51
Q

Incremental Cost-Effectiveness Ratios

A

= (C2-C1)/(E2-E1)

52
Q

Cost Minimization Analysis

A

Is used when 2 or more interventions have demonstrated equivalence in outcomes and the costs of each intervention are being compared.
Limited to compare only alternative with demonstrated equivalent outcomes

53
Q

Cost Benefit Analysis

A

Is a systematic process for calculating and comparing benefits and costs of an intervention in terms on monetary units ($)

54
Q

Cost Effectiveness Analysis

A

Is used to compare the clinical effects of two or more interventions to the respective costs.
Main advantage is that the outcomes are easier to quantify .
Disadvantage is the inability to directly compare different types of outcomes

55
Q

Cost Utility Analysis

A

includes a quality of life component. Uses quality-adjusted life years (QALYs) and disability-adjusted life years (DALYs)

NAPLEX (45 decks)

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