Biologic methods and stats

Question 1

hormones for which measurement by standard assays are influenced by binding proteins

Answer 1

1) Free T4 and T3: thyroid binding globulin can alter measurement of total T4 and T3

2) Testosterone: binds to albumin and SHBG. Free testosterone can be measured or calculated

3) Estrogen: binds to albumin and SHBG

4) Cortisol: binds to corticosteroid binding globulin and albumin. 90% of cortisol is bound to CBG. Free cortisol can be measured with urine sample for 24 hours

5) Vitamin D (1,25 and 25): binds to vitamin D binding protein (DBP) and albumin.

6) Growth hormone: growth hormone binding protein

Question 2

what can interfere with assays

how to tell

Answer 2

• autoantibodies - will bind to the ligand and prevent it from binding to assay
• heterophiles antibodies - bind to capture Ab/assay and block the hormone receptor sites

both of these make it appear as if there are less substrate/hormone present in the sample

if you dilute the sample it will not dilute in a linear fashion

Question 3

hook effect

Answer 3

solid state assay
when large amounts of substrate are present
direct binding of the reporter Ab preventing the reported Ab from binding to the surface

ex: macroPRL

serial dilution

Question 4

what are normal ranges in parameters

Answer 4

central 95% of unaffected population
2SD above and below mean
2.5% above and below are normal

Question 5

what is the null hypothesis

Answer 5

“ there is no difference in the frequency of ‘x’ between 2 groups”

Question 6

what is type 1 error

Answer 6

alpha

Incorrectly rejecting null hypothesis
ie when you find there is a difference but it’s just by chance

Question 7

what is type 2 error

Answer 7

beta

Stating there is no difference when you just didn’t have enough subjects to detect the difference

Question 8

what is power

Answer 8

1-beta

Probability the study could have detected a difference

Directly related to sample size and magnitude of the difference

Question 9

what increases your chances of having a type 1 error

Answer 9

Making multiple individual comparisons (≥20) can generate a p value ≤ 0.05 by chance alone

Question 10

how do you correct for multiple comparisons

Answer 10

Divide the desired type I error rate by the number of comparisons to be made.

For example, with 3 comparisons:
.05/3 = .017
The new significant p value for comparisons is 0.017 and not 0.05.

Question 11

what does p = 0.05 mean

Answer 11

5% chance that the difference you found was due to chance alone
Therefore if you make 20 comparison, you should find statistical significance somewhere

Question 12

what do you typically set beta at

Answer 12

.20 (power = 1 – ß) or a 20% chance that you will fail to find a difference that actually does exist.

Question 13

if you have 2 independent samples with normal distribution, what kind of test should you use to analyze?

what if it is more than 2?

Answer 13

t-test

ANOVA

Question 14

if you have 2 independent samples with NOT normal distribution, what kind of test should you use to analyze?

what if it is more than 2?

Answer 14

Mann-Whitney U
Wilcoxon Rank Sum Test

Kruskal-Wallis

Question 15

what is odds ratio

Answer 15

Odds ALWAYS implies a ratio of two probabilities.
Probability of event happening over probability of event not happening
OR is a ratio of two ratios.

Question 16

if something has a probability of 80%, what’s the odds?

Answer 16

80:20 = 4

Question 17

relative risk

Answer 17

ratio of percent of those with a risk factor who have the disease compared to those without the risk factor who have the disease.

Question 18

when to use RR and when to use OR

Answer 18

RR
Useful in large prospective cohort studies

OR
case control
Retrospective studies

Question 19

Number Needed to Treat (NNT)

Answer 19

The NNT is the number of patients who need to be treated in order to prevent one additional “outcome”.

Question 20

how to calculate NNT

Answer 20

NNT = 1/ARR

Question 21

what is ARR
how to calculate

Answer 21

Attributable (Absolute) Risk Reduction

ARR = risk of outcome in non-intervention group – risk of outcome in intervention group

The difference between the control
group’s event rate and the experimental group’s event rate.

Question 22

RRR

Answer 22

Relative Risk Reduction = ARR/placebo or non-intervention group rate

Question 23

95% confidence interval

Answer 23

A 95% confidence interval (95% CI) is the range of values which we can be 95% confident includes the population statistic from which the study sample was drawn

Question 24

how to interpret confidence intervals:
what is the null value for a mean?
what is the null value for OR/RR/Hazard Ratio?

Answer 24

Null value is 0
If 95% CI includes 0, not statistically significant

Null value is 1
If 95% CI includes 1, not statistically significant

Question 25

What is a bias

Answer 25

“any systematic error in an epidemiologic study that results in an incorrect estimate of the association between exposure and risk of disease”

Question 26

what is selection bias

Answer 26

Patient selection is not uniformly performed. Patients selected are different than those not selected.

Question 27

Recall bias

Answer 27

- Differences in the accuracy of recalling past events/exposures between cases and controls

Question 28

Measurement bias

Answer 28

Systematic error in the measurement of data.

Question 29

Misclassification Bias

Answer 29

-Wrongly classifying a subject/mislabeling them

Question 30

what is a confounding variable

Answer 30

A confounding variable is associated with both the risk factor or ‘exposure’ and the disease being studied. Can either inflate or deflate the true magnitude of the association Should not be an intermediate link between exposure and disease.

Question 31

what is a correlation

Answer 31

Determine the strength of the linear relationship between two continuous variables. Its value can range from -1 to +1. closer to -1 to +1 indicate stronger 0 indicates no correlation

Question 32

what is regression what are the types

Answer 32

Any statistical technique which focuses on the relationship between a dependent variable and one of more independent variables. Linear regression – dependent variable is continuous or interval variable Logistic regression – dependent variable is dichotomous (yes/no, dead/alive)

Question 33

Prevalence

Answer 33

Proportion (or fraction) of a group possessing a clinical condition at a given point of time.

Question 34

Incidence

Answer 34

Proportion (or fraction) of a group initially free of the condition that develop it over a period of time.

Question 35

sensitivity

Answer 35

a/(a+c) or TP/(TP + FN) Proportion of people with the disease who have a positive test for the disease if high, Very few false negatives R/O disease

Question 36

Specificity

Answer 36

d/(b+d) or TN/(TN + FP) Proportion of people without the disease who have a negative test if high, Very few false positives R/I disease

Question 37

Positive Predictive Value

Answer 37

a/(a+b) or TP/(TP + FP) Probability of disease in a patient with a positive or abnormal test.

Question 38

Negative Predictive Value

Answer 38

d/(c+d) or TN/(FN + TN) Probability of not having the disease when the test result is normal or negative

Question 39

Positive Likelihood ratio

Answer 39

Probability of test result in the presence of disease OVER Probability of test result in people without disease Likelihood Ratio = Sensitivity OVER 1-Specificity Divides the probability that a patient with the disease will test positive by the probability that a patient without the disease will test positive

Question 40

what do LR mean

Answer 40

> 10 suggests large and conclusive change in pretest to posttest probability 5 - 10 suggests moderate change 2 - 5 suggests small, although occasionally important changes in probability 1 -2 suggests small, rarely important changes in probability < 1 decrease the probability of disease

Question 41

Receiver Operator Characteristic (ROC) Curves what are on the axes

Answer 41

Sensitivity on the y-axis 1- specificity on the x-axis Plotting the true positive rate against the false positive rate Describes accuracy of test over a range of cut-off points Overall accuracy of test described by the area under the curve (the larger the area the better the test)

Question 42

Case Reports

Answer 42

Presentations of single case or handful of cases Important way for unusual diseases or unusual presentations of disease are brought to attention

Question 43

Case series

Answer 43

Prevalence survey of a group of individuals with a particular disease at one point in time Describes clinical manifestations of disease including both purported causes and effects

Question 44

Cross-Sectional or Prevalence Studies

Answer 44

Prevalence: fraction or proportion of the group who are diseased All people examined, including cases and noncases Single point in time

Question 45

Cohort Studies

Answer 45

Group of people (cohort) is assembled none of whom has experienced the outcome of interest People are classified according to characteristics that might be related to outcome People are observed over time Relate initial characteristics to subsequent outcome events

Question 46

Advantages and Disadvantages Of Cohort Studies

Answer 46

Advantages: Establishes incidence Follows logic, if people are exposed, will they get the disease? Exposure elicited without bias since outcome is not known Can asses relationship between exposure and many diseases Disadvantages: Inefficient as many more subject must be enrolled than will experience the outcome of interest Expensive Results not available for a long time Can only assess relationship between disease and exposure to relatively few factors recorded at the outset of study

Question 47

Case control study

Answer 47

Patients with the disease and a group of otherwise similar people who do not have the disease are selected Researchers look backward to determine the frequency of exposure in the two groups Estimate the relative risk of disease related to exposure

Question 48

Advantages and disadvantages of Case Control

Answer 48

Advantages Cases can be identified unconstrained by the natural frequency of disease Good for rare disease Look at many exposure at the same time Do not need to wait a long time for the answer Able to address important questions rapidly and efficiently Disadvantages Can only estimate relative risk Incidence rates not measured Fraught with bias Selection of controls – controls and cases must have an equal chance of being exposed to risk factor Measuring exposure affected by presence of disease

Question 49

advantages of disadvantages of RCT

Answer 49

Advantages Minimize selection bias Equal distribution of known and unknown risk factors for disease (confounders). Often both provider and patient are blinded to study. Disadvantages Expensive Time consuming Often, patients and/or providers figure out which arm they are in (placebo pill tastes different)

Question 50

Systemic Review versus Meta-Analysis

Answer 50

Systemic review answers a defined research question by collecting and summarizing all empirical evidence that fits pre-specified eligibility criteria. Meta-analysis is the use of statistical methods to summarize the results of these studies.

Question 51

An article describing a test - what are criteria for it to be significant

Answer 51

i. P value ii. 95% CI iii. Sens & Spec iv. PPV & NPV v. Power: ability of test to detect a true difference

Question 52

what is What is the statistical term to describe the precision of the relative risk

Answer 52

confidence interval

Question 53

what is lead time bias

Answer 53

Lead time is the interval between the diagnosis of a disease at screening and when it would have been detected due to development of symptoms. = Represents the amount of time by which the diagnosis has been advanced asa result of screening. Lead time bias occurs when a screened population appears to have longer survival compared to an unscreened population because the diagnosis was simply made earlier because of screening (vs. actually prolonging disease survival).

Question 54

what is length time bias

Answer 54

Overestimation of survival duration due to the relative excess of cases detected that are slowly progressing ♣ Screening is more likely to detect cases of diseases in individuals with a longer preclinical phase, and therefore whose disease is progressing more slowly. These people are likely to have a better prognosis ♣ This means that individuals detected by screening are likely to have longer survival because their disease is likely to progress more slowly vs. those who go to MD with symptomatic disease ♣ Results in apparent increase in survival among people with disease detected by screening... overestimation of the benefit of screening.

Question 55

Negative likelihood ratio

Answer 55

= (1–sensitivity)/specificity i. Divides the probability that a patient with the disease will test negative by the probability that a patient without the disease will test negative