Intro, Biostats

3 elements of EBM (evidence based medicine)

1. clinical expertise

2. patient values + pref

3. best research evidence

EBM PYRAMID

1. BG info/expert opinion

2. observational-descriptive designs

3. observational-analytic designs

4. quasi-experimental designs

5. experimental designs

6. systemic reviews + meta-analyses

1. DOE (pathophys/pharmacology/etiology)

2. vs POEM (clinical endpoints/quality of life)

3. Which is MORE relevant?

4. Which uses surrogate markers?

1. disease-oriented evidence

2. patient-oriented evidence that matters

3. POEM

4. DOE

Label the following as DOE, surrogate marker, or POEM

1. HCTZ controls HTN

2. alendronate improves BMD

3. atorvastatin reduces heart attack, stroke, mortality

4. alendronate treats osteoporosis

5. HCTZ decreases mortality in patients with HTN

6. HCTZ decreases BP

1. DOE

2. surrogate

3. POEM

4. DOE

5. POEM

6. surrogate

What has become the “gold standard” for judging whether a treatment does more good than harm?

Randomized controlled trials

T or F?

Since RCTs are the "gold standard" in EBM, they will always answer the question being asked.

F

_________: a characteristic that is BEING MEASURED

example: math, reading, science

variable

_______: measured VALUES of the variable for each individual member of a study

example: a … of the math proficiency rate is 48% (Mankato)

data

Scales of Measurement of a Variable (1)

1. ______ scales → values are _________

2. Actual values have _________

1. nominal → CATEGORIES

2. no rank/order

Scales of Measurement of a Variable (2)

1. ______ scales → values represent some associated _______

2. BUT …

3. Exs

1. ordinal → order/rank

2. increments MAY NOT be equal

3. pain scale, ECOG performance

Scales of Measurement of a Variable (3)

1. _____ scales → ______ data

2. Distance …

3. Has _________

4. Can add, subtract, and but …

1. interval → numerical

2. increments ARE EQUAL

3. NO TRUE ZERO POINT

4. ratio is meaningless

Scales of Measurement of a Variable (4)

1. _____ scales → ______ data

2. Difference between this and interval scale? (3)

1. ratio → numerical

2. increments EQUAL, has TRUE zero point, ratio is meaningful

Continuous vs Categorical Variable

1. continuous = interval/ratio, if ordinal is large

2. categorical = nominal/ordinal

1. CATEGORICAL variables may also be referred to as _____

2. If only has 2 CATEGORIES = _______ or ______

1. discrete

2. binary, dichotomous

What is the scale of measurement of Age at Hysterectomy in the table?

ordinal

(category + age group ranking)

Describe CONTINUOUS Data

1. Measures of central location → 3

2. Measures of spread or variation → 3

1. mean, median, mode

2. variance and standard dev, range, inter-quartile range (IQR)

ARITHMETIC MEAN

1. Most common, the _____

2. Affected by …

3. *Most appropriate when data is approximately _____ and _________

1. avg

2. extreme values

3. symmetric, not very skewed

MEDIAN

1. To calculate, _________ first

2. If total number (n) is ODD, median is …

3. If total number (n) is EVEN, median is …

4. *Is a better measure of central location when data is ________

1. order the data

2. middle

3. avg of middle 2

4. skewed or ordinal

MODE

1. Most _______ occurring value

2. **Most appropriate for _______ data

3. 2 modes =

4. 3 modes =

1. freq

2. categorical

3. bimodal

4. trimodal

VARIANCE AND STANDARD DEVIATION (SD)

1. Measures of data __________

2. VARIANCE:

3. STANDARD DEVIATION:

1. variability AROUND the mean

2. V = SD²

3. SD = sq root of V

Example: Variance and SD

Age at 2nd MMR dose: 4, 4, 5, 5, 6, 9

1. n =

2. mean =

3. sample V =

4. SD =

5. What is the benefit of taking a sq root of variance (SD)?

1. 6

2. 5.5

3. 3.5

4. 1.9

5. clearer interpretation

STANDARD ERROR of Mean vs SD

1. Measures the _____ in an estimated sample mean

2. Formula (SEM or SE)

3. Previous Example: 4, 4, 5, 5, 6, 9

   SD = 1.9

4. SE is related to ________

1. precision

2. SE = SD/sq root n

3. 0.8

4. confidence interval

T or F:

Standard Error of the Mean or Standard Error can be used to describe the variability in the data.

F (SD describes variability, SEM/SE describes precision)

RANGE =

max-min

Inter-quartile range (IQR)

1st quartile: 25th percentile

2nd quartile: 50th percentile

3rd quartile: 75th percentile

1. Median =

2. IQR =

1. 50th percentile

2. 75th-25th percentile

Box-and-Whisker Plot (also called “Boxplot”)

1. IQR

2. median

Boxplot of body weight with outliers. Circles represent values 1.5 to 3.0 IQRs from either ends of box, asterisks represent values >3.0 IQRs

1. What is the maximum BW?

2. What is the minimum BW?

   a. 149

   b. 118

   c. 98

   d. 90

3. What is the mean BW?

   a. 190

   b. 185

   c. 175

   d. can’t be determined

4. What is the IQR of BW?

   a. 130

   b. 110

   c. 80

   d. 20

1. ~225

2. c

3. d

4. d

A. Right-skewed (positively skewed)

B. Symmetric

C. left-skewed (negatively skewed)

A (mean>median)

A. Right-skewed (positively skewed)

B. Symmetric

C. left-skewed (negatively skewed)

C (mean<median)

A. Right-skewed (positively skewed)

B. Symmetric

C. left-skewed (negatively skewed)

B (mean=median)

A. Right-skewed (positively skewed)

B. Symmetric

C. left-skewed (negatively skewed)

A

The distribution of the Age is …

A. Right-skewed (positively skewed)

B. Symmetric

C. left-skewed (negatively skewed)

C

CHOICE OF DESCRIPTIVE STATISTICS

1. If approximately symmetric =

2. If skewed =

1. report mean and SD

2. report median, range/IQR

CHOICE OF STATISTICAL TESTS

1. If approximately symmetric =

2. If skewed =

1. parametric test

2. nonparametric test

PARAMETRIC TESTS:

1. Based on _______ that observed data are distributed

2. _________ is most commonly used parametric distribution

3. Determined by 2 parameters →

4. _______ affects the spread of data (flattness)

5. Which color is the standard normal distribution?

1. assumption

2. normal distribution

3. mean, SD

4. variance

5. red → mean = 0, SD = 1

Describe CATEGORICAL Data:

nominal scale → categories, no order

Reported as …

n (%)

Which variable is measured as categorical variable?

All except age

5 STEPS IN STATISTICAL HYPOTHESIS TESTING:

1. Step 1: Develop ______ and _________

2. Step 2: Determine the appropriate _________

3. Step 3: Determine the ______

4. Step 4: Calculate the test statistic from the sample data and make decisions →

5. Step 5: State the ______ in the context of the study

1. null + alternative hypotheses → null assumed to be true

2. test statistic

3. decision rule

4. reject/fail to reject the null

5. conclusion

___________ (H0): presumed to be TRUE unless sample data produce overwhelming evidence to prove the contrary

null hypothesis

__________ (Ha): the opposite, or complement of H0

alternative hypothesis

Which type of test is more common?

two-sided

1. H0 (null)

2. Ha (alternative)

1. %CW in T = %CW in S

2. %CW in T does not equal %CW in S

________: the probability of observing the outcome from the study or more extreme values by chance, if the null hypothesis is true.

^ the probability of observing a difference of 6.5% or even larger difference, if in fact there is no difference

P-value

Comparing P-VALUE to ALPHA to determine statistical significance →

1. alpha = ____ is most common

2. If …

1. 0.05

2. P < alpha = statistically significant

1. Is the result statistically significant?

2. Reject or fail to reject the null?

1. yes (P<0.001 is < alpha 0.05)

2. REJECT

   (remember that the null was %CW in T = %CW in S)

Statistical Significance uses 95% Confidence Intervals (CI)

1. ______ is most common and is equivalent to a _________ test of ________

2. FOR TESTING MEANS → 95% CI contains … indicates …

3. FOR TESTING RATIOS → 95% CI contains … indicates …

1. 95% CI, two-sided, no diff at alpha = 0.05

2. contain 0 = NO diff

3. contain 1 = NO diff

Step 1: statistical significance

1. For tirzepatide, is there a statistically significant change in weight at 72 weeks from baseline?

2. For semaglutide, is there a statistically significant change in weight at 72 weeks from baseline?

Step 2: if statistically signficant, interpret the direction

3. In both groups, there are statistically significant ________ in weight change from baseline to 72 weeks

1. yes (does NOT contain 0 → 95% CI -21.4 to -19.1)

2. yes (does NOT contain 0 → 95% CI -14.9 to -12.6)

3. reduction

Hazard Ratio (HR), 0.71; 95% CI: 0.54-0.95.

1. Does Ribociclib plus Endocrine Therapy improve survival in breast cancer patients (compared to Endocrine Therapy alone)? (Yes/No)

2. Direction? (if statistically significant)

3. Magnitude of effect

1. Yes (does NOT contain 1, also P<0.05)

2. -risk of death (0.71<1), +survival

3. 29% ((1-0.71)x100=29)

1. What is the variance?

2. What is the range?

3. What is IQR?

4. What is the median?

1. 1521

2. 115

3. 55

4. 125

1. What is the maximum age at admission among males? (Circle in the Box is the mean.)

   a. 98

   b. 90

   c. 87

   d. 72

2. Based on information in the figure, which description about this study sample patients is correct? (Circle in the Box is the mean.)

   a. Distribution of age at admission among males is right-skewed

   b. The median age at admission is higher among females than males

   c. At least 75% of males were 50 or under at admission

   d. The IQR of age at admission is about 70 in females

1. A

2. B

Match with ordinal, nominal, or interval/ratio

1. Sum of largest-lesion diameters - mm:

2. Smoking status:

3. ECOG performance status:

4. Previous radiotherapy:

1. interval/ratio

2. nominal

3. ordinal

4. nominal

A randomized, placebo-controlled trial enrolled infants 1 to 24 months of age who were hospitalized with respiratory syncytial virus (RSV) infection. Infants were randomized to receive Ziresovir or placebo. At Day 3, the mean (95% CI) difference in the respiratory rate between Ziresovir vs. placebo was - 0.18 (- 0.32, - 0.04). Which is a correct conclusion from this finding?

A. Ziresovir reduces respiratory rate in hospitalized infants 1 to 24 months of age with RSV

B. Ziresovir increases respiratory rate in hospitalized infants 1 to 24 months of age with RSV

C. Ziresovir has no statistically significant effect on respiratory rate in hospitalized infants 1 to 24 months of age with RSV

A

Which is a correct conclusion from this finding?

A. Ziresovir reduces system remission at Day 3 in hospitalized infants 1 to 24 months of age with RSV

B. Ziresovir increases system remission at Day 3 in hospitalized infants 1 to 24 months of age with RSV

C. Ziresovir has no statistically significant effect on system remission in hospitalized infants 1 to 24 months of age with RSV

C

Which is a correct conclusion from this finding?

A. Ziresovir had a larger reduction in RSV viral load at Day 5 than placebo in hospitalized infants 1 to 24 months of age with RSV

B. Ziresovir had a smaller reduction in RSV viral load at Day 5 than placebo in hospitalized infants 1 to 24 months of age with RSV

C. Ziresovir had no statistically significant effect on RSV viral load in hospitalized infants 1 to 24 months of age with RSV

A

Why do we need sample size calculation or power analysis?

1. Mainly to ensure the study will have sufficient sample size to detect a ____________ if exists

2. Most often, power is set at _______

1. true effect

2. 80% or higher

1. Reject H0 =

2. Fail to reject H0 =

3. Type I (α)

4. vs Type II (β) ERROR

1. diff

2. NO diff

3. Type I → H0 is wrongly rejected (false positive) → there is no diff, but you say there is

4. Type II → false H0 is wrongly FAIL to reject (false negative) → there is a diff, but you say there is no diff

The MAXIMUM allowable probability of making a Type I error is denoted as α (alpha) and is referred to as the level of the test, or __________.

Often set at α = ____

significance level, 0.05

The maximum allowable probability of making a Type II error is denoted as β (beta)

_______ is the _______ of the test

1-B, power (0.8 or higher)

ERRORS IN HYPOTHESIS TESTING

1. Type I error and Type II error are ________ related

2. The relationship is …

3. Type I error is ______ related to power

4. Type II error is ______ related to power

1. inversely

2. NOT 1:1

3. positively

4. negatively

Factors Affecting POWER → 5

1. effect size

2. population variations in outcome

3. type I error (significance level)

4. sample size

5. study design

The effect size tells us how large is the difference in study outcome between 2 treatments under comparison

Effect size and power are __________ associated

positively

a between-group difference in the percent change in body weight of 3 percentage points

1. What is the anticipated effect size?

2. What is the actual effect size?

1. 3%

2. 6.5%

Variation of the outcome and power are _________ associated

negatively

What is the anticipated variation?

12%

Sample size (n) and power are ________ associated

positively

Factors affecting power: summary

1. Effect size

2. Population variations in the outcome (σ, standard deviation)

3. Type I error (α) or significance level

4. Sample size (n)

5. Study design

1. +

2. -

3. +

4. +

5. depends

C

(A. smaller n = smaller power

B. larger variation = smaller power

C. larger n = LARGER power

D. lower effect size = smaller power)

A study of 20 patients at UAMS found no difference in glucose control between 2 diabetic drugs. What could be a potential error? (Choose all that apply.)

A. Type 1 error

B. False negative error

C. False positive error

D. Type 2 error

E. No potential error

B, D

(reject H0 = diff, fail to reject = no diff

type I = H0 is wrongly rejected = u say there is a diff but there is not

type II = H0 is wrongly failed to reject = u say there is no diff but there is)

Which statement is INCORRECT? (Choose all that apply.)

A. Type 1 and Type 2 errors are inversely related.

B. Type 1 and power are inversely related.

C. Type 2 error is when there is no difference, but you conclude there is a difference.

D. Population variation in the outcome is inversely related to power.

B, C