Steven Katz MSIV

PART 1: BIOSTATISTICS Terms:

Independent variable: values that are controlled or selected by the person experimenting to determine its relationship to an observed phenomenon (the dependent variable).

Dependant variable: the observed phenomenon, usually cannot be changed.

In summary:○ Independent variables answer the question "What do

I change?" ○ Dependent variables answer the question "What do I

observe?"

Types of Studies (p.60) Case Control: Compares a group of people with

a disease to a group without. Asks “what happened?” Two types:

○ Observational and Retrospective Famous example is lung cancer link to smoking Issues:

Confounding: a variable that correlates to both dependant and independent variables.

Cannot prove cause and effect of risk factor to variable

Types of Studies (p.60) Cohort: Compares a group with a given risk

factor to a group without Assesses whether the risk factor increases the

likelihood of diseaseAsks “what will happen” Two types:

○ Observational and Prospective

Used to prove cause and effect of smoking to lung cancer.

Types of Studies (p.60)

Cross-Sectional: Collects data from a group of people to assess FREQUENCY of disease (and related risk factors) at a particular point in time. Asks “what is happening?”

Example: political polls

Types of Studies (p.60)

Twin Concordance: Compares the frequency with which both monozygotic twins or both dizygotic twins develop a diseaseMeasures heritability

Example: look at incidence of diabetes in twins

Types of Studies (p.60)

Adoption: Compares siblings raised by biologic v. adoptive parents Measures heritability and influence of

environmental factors

Famous examples are Swedish adoption studies

Clinical trials (p.60)

Experimental study involving humans. Compares therapeutic benefits of 2 or more treatments, or of treatment and placebo. Highest quality study is double-blind

randomized control trial.

Clinical trials (p.60)

Study Sample Purpose

Phase I Small number of pts, usually healthy volunteers

Assess safety, toxicity, and pharmacokinetics

Phase II Small number of pts with disease of interest

Assesses treatment efficacy, optimal dosing, and adverse effects

Phase III Large number of pts randomly assigned to either the treatment under investigation or to the best available treatment (or placebo)

Compares the new treatment to the current standard of care.

Is more convincing if double-blind

Meta-analysis (p.60)

Pools data from several studies to come to an overall conclusion. Achieves greater statistical power and

integrates results of similar studies

Highest echelon of clinical evidence May be limited by quality of individual

studies or bias in study selection

Evaluation of diagnostic tests (p.61) 2 x 2 table (TN = True neg, TP = True pos, FP

= false pos, FN = false neg)

DISEASE

TEST

+ -

+ TP FP

- FN TN

Evaluation of diagnostic tests (p.61) Sensitivity = TP/(TP+FN) = 1-FN rate

Proportion of all people with disease who test positive

Value approaching 1 is desirable for RULING OUT disease and indicates low false negative rate.

Used for SCREENING in diseases with low prevalence

SNOUT = SeNsitivity rules OUT If sensitivity = 100% then all negative tests

are TN (TP/(TP+FN) = 1) because FN = 0

Evaluation of diagnostic tests (p.61) Specificity = TN/(TN+FP) = 1-FP rate

Proportion of all people without disease who test negative

Value approaching 1 is desirable for RULING IN disease and indicates a low FP rate

Used as a CONFIRMATORY test after a positive screening test

SPIN = SPecificity rules IN If specificity = 100% then all positive tests

are TP (TN/(TN+FP) = 1) because FP = 0

Evaluation of diagnostic tests (p.61) Positive Predictive Value (PPV) =

TP/(TP+FP)Proportion of positive tests that are true

positivesProbability that a person actually has the

disease given a positive test result

Note: If the prevalence of a disease is low then even tests with high specificity or sensitivity will have LOW PPV

Evaluation of diagnostic tests (p.61) Negative Predictive Value (NPV) = TN

/(TN+FN) Proportion of negative tests that are true

negatives Probability that a person actually is disease

free given a negative test result

http://gim.unmc.edu/dxtests/bayes.htm

Evaluation of diagnostic tests (p.61) A = 100%

sensitivity B= most

accurate C = 100%

specificity

Prevalence v. Incidence (p.62) Prevalence = TOTAL cases in a population at a given time

total population at risk at a given time

Incidence = NEW cases in a population over a time period

total population at risk during that time

Prevalence = incidence X disease duration Prevalence > Incidence for chronic dz’s Prevalence = incidence for acute dz’s

Odds ratio (p.62)

For case control studies (a/b)/(c/d) = ad/bcOdds of having disease in exposed group

divided by odds of having disease in unexposed group

Approximates the relative risk if prevalence of disease is not too high

Relative risk (p.62)

For cohort studies Relative probability of getting a disease

in the exposed group compared to the unexposed group [a/(a+b)]/[c(c+d)]Calculated as a percent of exposed pts with

dz to unexposed pts with dz

Attributable risk (p.62) The difference in risk between exposed

and unexposed groupsOR

The proportion of disease occurrences that are attributable to the to the exposure

(e.g. smoking causes 1/3 of cases of pna)

[a/(a+b)] – [c/(c+d)]

Odds ratio, relative risk, attributable risk (p.62)

Disease

Risk Factor

+ -

+ a b

- c d

Attributable risk = [a/(a+b)] – [c/(c+d)]

Odds ratio: (a/b)/(c/d) = ad/bc

Relative Risk: [a/(a+b)]/[c(c+d)]

Precision v. accuracy (p.62) Precision:

The consistency and reproducibility of a test ○ RELIABILITY

The absence of random variation in a testRandom Error: reduced precision in a test

Accuracy:The trueness of test measures

○ VALIDITYSystematic error: reduced accuracy in a test

Precision v. accuracy (p.62)

Neither Precise Nor Accurate

                          

       

This is a randomlike pattern, neither precise nor accurate. The darts are not clustered together and are not near the bull's eye.

Precise, Not Accurate

                                                  

          

This is a precise pattern, but not accurate. The darts are clustered together but did not hit the intended mark.

Accurate, Not Precise

                                               

             

This is an accurate pattern, but not precise. The darts are not clustered, but their 'average' position is the center of the bull's eye.

Precise and Accurate

                           

      

This pattern is both precise and accurate. The darts are tightly clustered and their average position is the center of the bull's eye.

Bias (p.63) Occurs when 1 outcome is systematically favored

over another Systematic errors:

Selection bias: nonrandom assignment to study groupRecall bias: knowledge of presence of disorder alters

recall by subjectsSampling bias: subjects are not representative relative to

general pop; therefore, results are not generalizableLate-look bias: information gathered at an inappropriate

timeProcedure bias: subjects in different groups are not

treated the same○ E.g. more attention is paid to treatment group, stimulating greater

complianceLead time bias: early detection confused with increased

survival

Bias (p.63)Confounding bias: occurs with 2 closely associated

factors○ The effect of the 1 factor distorts or confuses the effect of the

otherPygmalion effect: occurs when a researcher’s belief in

the efficacy of the treatment changes the outcome of that treatment

Hawthorne effect: occurs when the group being studied changes its behavior to meet the expectations of the researcher

Ways to reduce bias: Blind studiesPlacebo responsesCrossover studies (each subject is its own control)Randomization

Statistical distribution (p.63)

Normal, Gaussian, bell-shaped curved Mean = mode = median

Bimodal = 2 humps Positive skew—mean

>median>mode Asymmetry with tail on right

Negative skew—mean<median<mode Asymmetry with tail on left

Mode is least affected by outliers

Statistical hypotheses (p.63) Null (H0): Hypothesis

of NO DIFFERENCEe.g. there is no

difference between the dz and the risk factor in the population

Alternative (H1): Hypothesis that the is some difference e.g. there is some

association between the dz and the risk factor in the population

Reality

Study R

esultsH1 H0

H1Power (1-)

H0

Error types (p.64)

Type I error (): Stating that there IS an effect or difference when none exists (to mistakenly accept the experimental hypothesis and reject the null hypothesis) p = probability of making a type I errorp is judged against , a preset level of

significance (usually <0.05) “False positive error”

Error types (p.64)

Type II error (): Stating that there is NOT an effect or difference when one exists (to fail to reject the null hypothesis when in fact H0 is false) is the probability of making a type II error“False negative error”

Error types (p.64)

If p < 0.05 then there is a less than 5% chance that the data will show something that is really not there.

= you “saw” a difference that did not exist

= you did NOT “see” a difference that does exist

Power (1-) (p.64) Definition:

1. Probability of rejecting a null hypothesis when it is in fact false

2. The likelihood of finding a difference if one in fact exists

Depends on: 1. Total number of endpoints experienced by the

population2. Difference in compliance between treatment groups

(diff in the mean values of the groups)3. Size of expected effect

If you increase sample size you increase power

Standard deviation v. standard error (p.64) n = sample size = standard deviation SEM = standard error

of the mean SEM = /square root

(n) Therefore, SEM < and

SEM decreases as n increases

t-test v. ANOVA v. 2

(p.65) t-test checks difference between the MEANS of 2

groupsMr. T is MEAN

ANOVA checks difference between the means of 3 or more groupsANOVA = ANalysis Of VAriance of 3 or more variables

2 checks difference between 2 or more percentages or proportions of categorical outcomes (NOT mean values)2 = compare percentages or proportions

Correlation coefficient (r) (p.65) r is always between -1 and +1. The closer the absolute value of r is to 1,

the stronger the correlation between the 2 variables

Coefficient of determination = r2 (value that is usually reported)]Provides a measure of how well future

outcomes are likely to be predicted by the model.

Disease prevention (p.65) 1o – prevent disease occurrence (e.g.

vaccination) 2o – early detection of disease (e.g. Pap

smear) 3o – reduce disability from disease (e.g.

exogenous insulin for diabetics) PDR:

Prevent Detect Reduce disability

Important prevention measures (p.65)

Risk Factor Services

DiabetesYearly eye exam, weekly self foot exams, urine tests for microalbuminemia

Drug Use Hepatitis immunizations, HIV, PPD for TB

AlcoholismInfluenza, pneumococcal immunization, PPD for TB

Overweight Fasting blood sugar test for diabetes

Homeless, recent immigrant, inmate

PPD for TB

High-risk sexual behaviorTest for HIV, hepatitis B, syphilis, Gonorrhea, Chlamydia

Reportable diseases (p.65) Only some infectious diseases are

reportable in ALL statesAIDS ChickenpoxGonorrhea Hepatitis A and BMeasles MumpsRubella SalmonellaShigella SyphilisTB

Other diseases (including HIV) vary by state

Reportable diseases (p.65) Hep Hep Hep, Hooray, the SSSMMART

Chick is Gone! Hep A Hep B Hep C HIV Salmonella Shigella Syphilis Measles Mumps AIDS Rubella TB Chickenpox Gonorrhea

Leading causes of death in US by age (p.66)

InfantsCongenital anomalies, short gestation/low birth weight, SIDS, maternal complications of pregnancy, respiratory distress syndrome

Age 1-14Injuries, cancer, congenital anomalies, homicide, heart disease

Age 15-24 Injuries, homicide, suicide, cancer, heart disease

Age 25-64 Cancer, heart disease, injuries, suicide, stroke

Age 65+Heart disease, cancer, stroke, COPD, pneumonia, influenza

Part 2: NUTRITION

Basal Metabolic Rate Metabolism of the body at rest Heat production of the body when in a

state of complete mental and physical rest and in the post-absorptive state.

BMR can be estimated at 20-25 Cal/kg/day

Varies between people and changes throughout life.High when you are young, slows as you

age.

Resting Energy Expenditure Energy expended in the post-absorptive

state and is approx 10% higher than BMR

Males: REE = 900 + 10W Females: REE = 700 + 7W

W is weight in kilograms REE is then adjusted for physical activity

by multiplying 1.2 for sedentary, 1.4 for moderately active, or 1.8 for very active individuals.

Caloric Requirement

Age and Caloric requirements: 3 mo: 28 Cal/kg9-12 mo: 6 Cal/kg 2-5 y/o: 2 Cal/kg9-17 y/o: 1 Cal/kg

10% reduction in energy allowance for adults > 50 y/o.

Caloric Requirement

Unstressed hospitalized pts require 1.2 times their REE

Stressed, febrile, catabolic pts require 1.5-2 times their REE

A 79-year-old African-American female is admitted to the hospital for progressive shortness of breath. She has no previous history of pulmonary insufficiency, and no history of emphysema, although she did smoke one pack per day until she was 60. The symptoms started three weeks prior to admission, and were gradual in onset. She has not had a cough, fever, or chest pain. She does have a history of hypertension, glaucoma, arthritis, kidney stones, and hysterectomy. Medications at the time of admission include amlodipine, ibuprofen, and eye drops. She is allergic to sulfur and penicillin, both of which caused a rash. Family history is significant for colon cancer, breast cancer, arthritis, diabetes, and hypertension. Social history reveals that the patient was married for forty years, but her husband died three months ago from heart failure. She lives alone. A chest x-ray at admission is suspicious for a mass in periphery of the left lower lung, and a follow up CAT scan is suspicious for malignancy. Consultation is obtained from a pulmonologist, who performs a video assisted thorascopic surgery (VATS) and biopsy. The pathology result reveals small cell carcinoma. An oncologist is called for an opinion, and recommends chemotherapy since the tissue type indicates a good chance of success. The problem is that the patient refuses treatment. She denies any depressive symptoms, appears to be awake, alert, and oriented. She answers questions appropriately and does not appear to be suffering from delirium or dementia. As the patient's primary care physician, you would like to respect the patient's autonomy, but are concerned about the consequences of her decision to forgo treatment. She has indicated to you that she understands the proposed treatment options and that she understands how they relate to her situation. You decide to:

(A) Assess her competence by administering a bedside mental status examination

(B) Enlist the help of family members who may be able to change the patient's mind

(C) Respect her decision if she can demonstrate and communicate ability to reason

(D) Consult adult protective services because she is no longer able to care for herself

(E) Declare her incompetent and ask the oncologist to administer the chemotherapy

Question 7 of 40

C   Respect her decision if she can demonstrate and communicate ability to reason

Competence is a legal term, capacity is a medical term. Physicians are often called on to make a determination of a patient's capacity to make medical decisions. The patient's primary care provider is an ideal person to make the assessment as they have background knowledge of the patient's educational level, values, and medical history.

A psychiatrist may be needed if overlying psychiatric problems make it difficult to determine capacity for judgment or ability to reason. Courts make the ultimate determination of competence, although there is usually concordance with the medical determination of capacity. Only lack of competence has legal ramifications, however.

A bedside mental status examination may help to determine capacity, but in and of itself does not determine competence. If the patient is deemed to have the capacity to make her own decisions, it may be detrimental to encourage family member involvement in the decision making process.

Adult protective services are usually called to investigate cases of abuse or neglect, not issues of capacity or competence. If still unclear, a psychiatrist or ethics board consultation could be utilized to help determine the patient's capacity to make her own decisions.

Four main criteria should be used to determine a patient's capacity to make medical decisions. 1) They can demonstrate understanding of the treatment options. 2) They can demonstrate understanding of how the different options affect their own individual situation. 3) They can demonstrate ability to reason with the above information, using either evidence based in fact, or

personal beliefs rooted in their value system.4) They are able to demonstrate 1-3 and can communicate a choice.

A 47-year-old male presents to his primary care physician complaining of markedly increased feelings of stress secondary to recent changes at his workplace. Which of the following statements about stress and its health effects is true?

(A) Stress does not include emotionally negative responses such as anger and hostility

(B) It is a factor in 10-20% of health problems

(C) Assertiveness training is unlikely to help an individual to avoid stress

(D) It is in the differential diagnosis for diarrhea

(E) It is the third leading cause of disability claims in California

Question 37 of 40

D   It is in the differential diagnosis for diarrhea

The definition of stress is an individual's negative emotional response to a perceived inability to meet demands place on him or her. It may express itself as anger, hostility, or feelings of helplessness, loss of control, or victimization. It is believed to be a factor in 60-80% of all health problems, and is the leading cause of disability claims in California. Major symptoms include fatigue, exhaustion, tight back and shoulders, insomnia, anxiety, anger, headaches, depression, sadness, hopelessness, colds, indigestion, diarrhea, and ulcer symptoms. Effective prevention and avoidance techniques include assertiveness training and the development of communication skills. Treatment methods include relaxation techniques, meditation, exercise, and participation in enjoyable activities.

Question 1 of 40

A 20-year-old man arrives at the emergency room asking for a strong pain killer because he is in serious pain. The attending physician notices that he is very anxious and is sweating. The man states that he has no appetite, he has a runny nose, nausea, stomach cramps and diarrhea. He said that he took his temperature at home at it was 100F. While he talks he is continuously yawning and restless. The attending physician recognizes that he is abusing a certain substance and is experiencing withdrawal. Which substance is it?

(A) Alcohol

(B) Cocaine

(C) Amphetamines

(D) Barbiturates

(E) Opioids

E   Opioids

The patient is experiencing the classic symptoms of withdrawal from opioids which are anxiety, insomnia, anorexia, sweating, piloerection, fever, rhinorrhea, nausea, stomach cramps, diarrhea, yawning. Symptoms usually appear within 8 to 10 hours after abstinence. The onset is longer if methadone has been withdrawn. These symptoms peak within 48 to 72 hours and then disappear in 7 to 10 days. Methadone lessens the effects of withdrawal. It should be given no more than 20-50mg/day. Alcohol withdrawal appears within a few hours of stopping or decreasing alcohol consumption. It lasts for three to four days and sometimes as long as a week. The patient experiences tachycardia, tremulousness, diaphoresis, nausea, orthostatic hypotension, malaise, anxiety, and irritability. Benzodiazepine should be administered in a tapering dose over three days. Cocaine withdrawal is classified by psychological symptoms such as increased sleep, REM rebound causing nightmares, lassitude, increased appetite, depression, and suicide attempts. Treatment would consist of an antidepressant such as bupropion. Amphetamine withdrawal would include a post use crash, including anxiety, lethargy, headache, stomach cramps, hunger, severe depression, dysphoria mood, fatigue, and insomnia or hypersomnia. Barbiturate withdrawal is characterized by anxiety, seizures, delirium, and life threatening cardiovascular collapse.

Question 4 of 40

The city of Cancerville had a population of 10,000,000 (50% women) in 1995. In 1995, there were 80,000 women with previously diagnosed ovarian cancer in Cancerville. Twenty thousand new cases of ovarian cancer were diagnosed in 1995. What was the incidence rate of ovarian cancer in Cancerville in 1995?

(A) 2000 per One hundred thousand population

(B) 4000 per One hundred thousand population

(C) 200 per One hundred thousand population

(D) 400 per One hundred thousand population

(E) 1,000 per One hundred thousand population

D   400 per One hundred thousand population

The incidence rate is the number of new cases of a disease during a specific period per population at risk. Twenty thousand divided by 5 million women gives a rate of 1 case per 250 women, or 400 cases per One hundred thousand populations.

Question 8 of 40

A laboratory has developed a new test for rapid ascertainment of serum parathyroid hormone levels. The test is repeated twenty times on the same sample with a resulting coefficient of variation of one percent. This is a measure of

(A) Accuracy

(B) Reliability

(C) Precision

(D) Validity

(E) Mode

B   Reliability

-The mode is the most commonly occurring value in a series of data. -Reliability is a measure of the reproducibility of a test over different conditions. The four most common types are inter-observer reliability, intra-observer reliability, split-sample reliability, and repeat testing reliability. -Accuracy is a measure of the extent to which a test approximates the real value of that which is measured. New tests are measured against the gold standard, if one exists. -Validity is the assessment of the degree to which a test measures that for which it was designed. In other words, you need to determine whether it reflect the outcome of interest or other outcomes. -Precision is the degree to which a measurement is not subject to random variation.

Question 10 of 40

At a large university, a study of pulse rates at rest was conducted on 5000 students. The mean pulse rate was 70, with a standard deviation of 10. Which of the following statements is true?

(A) Approximately 95% of the students had pulses between 60 and 80

(B) Approximately 68% of the students had pulses between 60 and 80

(C) Approximately 99.7% of the students had pulses between 50 and 90

(D) Approximately 95% of the students had pulses between 40 and 100

(E) Approximately 68% of the students had pulses between 50 and 90

B   Approximately 68% of the students had pulses between 60 and 80

When a test is conducted on a normally distributed population, 68% of the population will have values within one standard deviation of the mean, 95% of the population will have values within two standard deviations of the mean, and 99.7% of the population will have values within three standard deviations of the mean. Therefore, in this population, 68% of the pulses will be between 60 and 80, 95% between 50 and 90, and 99.7% between 40 and 100.

Question 13 of 40

A statistician analyzes data for several academic departments. She is free to choose the appropriate methodology to her perform her analyses. Which of the following data would best be analyzed by non-parametric statistical methods?

(A) Results of a study on the effect of a new lipid-lowering drug on LDL cholesterol

(B) Results of a study on the effect of asbestos exposure on forced vital capacity

(C) Results of a study on the relationship between gender and lung cancer

(D) Results of a study on the differences in weight distributions between children in different countries

(E) Results of a study on the relationship between hemoglobin and reticulocyte count

C   Results of a study on the relationship between gender and lung cancer

Parametric techniques can be used to analyze data where at least one of the variables is quantitative (interval or ratio) and where the data is distributed normally. If the data is not distributed normally or both variables are qualitative (nominal or ordinal), non-parametric techniques must be used. Gender and lung cancer are both qualitative variables, so non-parametric techniques, such as chi-square, are used to determine the relationship between them. LDL cholesterol, forced vital capacity, hemoglobin, and reticulocyte count are quantitative ratio variables, so studies involving them can be analyzed using parametric techniques, assuming they are normally distributed. The use of a new lipid-lowering drug and the presence or absence of asbestos exposure is qualitative nominal variables. Weight is a quantitative ratio variable, and various parametric techniques can be used to compare the means, ranges, and variances of distributions between populations.

Question 15 of 40

You are doing a research project on comparing the effectiveness of cognitive-behavioral versus psychoanalytic therapy in depressed patients. Your subjects consist of 60 outpatient females being seen at the local college clinic. They are randomly assigned to three groups: those who will receive cognitive-behavioral therapy, those receiving psychoanalytic therapy, and a third group that receives no therapy to serve as a control group. In your study what is the independent variable?

(A) the subjects participating in the different therapy groups

(B) the therapies being compared in the study

(C) the subjects receiving no therapy

(D) the level of depression in the participants at the end of the study

(E) the assignment of the participants into the separate groups

B   the therapies being compared in the study

The independent variable is defined as the variable that is to be manipulated or controlled, or that has been selected by the researcher. In the study, as the researcher you are controlling the type of therapy to be utilized in the study. You are also controlling whether or not the participants are receiving any therapy at all. The subjects that are participating in the different therapy groups and that have been assigned to serve as the control group are the sample being used in this study. The sample simply means the participants chosen to represent the larger population. The level of depression in the participants at the end of the study is considered to be the dependent variable. The dependent variable is defined as the response to the independent variable (or therapy), the observed or measured behavior, or the outcome of the study.

Question 21 of 40

You are doing a study on the distribution of IQ scores in 15-year-old adolescent males in a standard high school classroom. You have chosen one school from Los Angeles, Seattle, Dallas, Miami, Chicago and New York. The WISC-III is administered to all 15-year-olds in the schools selected. After all tests have been administered, the scores are collected and the distribution of the scores is analyzed. The IQ scores represent what type of statistical measurement scale?

(A) Nominal

(B) Ordinal

(C) Interval

(D) Ratio

(E) Correlational

C   interval

In statistical measurements, IQ is considered an interval scale because the difference between an IQ of 90 and 100 is indistinguishable from the difference in an IQ of 100 and 110. In interval scales, the difference between intervals is relative. The difference between 1 and 2 is relative to the difference between 3 and 4. Nominal measurements are used for variables in which there are no numerical values that can be compared, such as gender or ethnic background. Ordinal scales are used for rank ordering. Ordinal scales can be used for such variables as attractiveness, or grades in school. In each case one can state that s/he is more attractive then, or an A or B is better than a C or D. Ratio scales are based in measurements where there is an absolute 0. In IQ's there are no absolute zeros, and one cannot state that an IQ of 50 is half as good as an IQ of 100. Ratio scales can be used for variables such as the number of hours a student spends studying, 2 hours of studying would be half as many hours as 4 hours of study. Correlations are not used as a method of statistical measurements, but are used in research and statistics to define a relationship between two variables.

Question 24 of 40

A researcher studied the levels of serum calcium in the U.S. and Panama. The null hypothesis was proven. What does the null hypothesis state?

(A) There is a significant difference between populations tested

(B) Difference between populations is not attributable to chance

(C) Difference between populations is due to a particular factor

(D) There is no significant difference between populations tested

(E) Power of a study to detect a significant difference between populations is nil

D   There is no significant difference between populations tested

The null hypothesis states that there is no significant difference between the populations being tested, and that any difference that is found is attributable to chance. It is tested against the alternative hypothesis, which is that there is a significant difference between the populations tested.

Question 29 of 40

The public health officials of a particular city wish to evaluate the lead levels of its constituents. In order to develop a sample population, they choose every 10th family in the city for the study. This is an example of what kind of population sample?

(A) Stratified selected sample

(B) Cluster selected sample

(C) Simple random sample

(D) Systematically selected sample

(E) Nonrandom selected sample

B   Cluster selected sample

In cluster selected samples, the population of interested is divided into subunits, such as families, and a random sample of these units is used. In simple random samples, each individual member of a population has an equal probability of being chosen. In stratified selected samples, individuals are chosen randomly from within stratified groups, such as age groups. In systematically selected samples, the population is ordered by some characteristic, such as age, a starting point for selection is randomly selected, and then the remainder of the sample is collected by a predetermined scheme, such as choosing every x number of people. In nonrandom selected samples, some predetermined scheme is used, such as the first x number of people presenting for a certain disease to a clinic.

A physician wants to learn more about prevalence rates for diabetes mellitus in his local community. He has raw data from his town public health department, but he is not sure how to determine the prevalence rates. Which of the following comments is true of prevalence rates?

(A) Reflect a portion of specific illnesses in a population

(B) Include new and existing cases during a specific time period in the numerator

(C) Denominator is the entire population, both those at risk and those not at risk

(D) Include only cases prevalent at the start of the time period in the numerator

(E) Are not influenced by the duration of disease

Question 31 of 40

B   Include new and existing cases during a specific time period in the numerator

Prevalence rates are determined as the number of new and existing cases of disease during a specific time period in the numerator divided by the population at risk in the denominator. They are influenced by both the duration of disease and the incidence of new cases. By measuring both existent and new cases of illness, they reflect the total amount of specific illnesses in a specific population.

Question 36 of 40

You are conducting an experiment on the effectiveness of behavioral therapy in treating social anxiety. Your research hypothesis is that behavioral therapy is effective in reducing social anxiety. The participant's in your study are 30 individuals who have been diagnosed with social anxiety. Each individual is independently evaluated for social anxiety to confirm the diagnosis. After the evaluation, 6 participants are found to not meet the set criteria for social anxiety and are dropped from the study. The remaining 24 participant's are broken up into two separate groups. Group A receives behavioral therapy and group B is put on a wait-list to receive therapy after the experiment is over. At the end of the experiment, you find that behavioral therapy was effective in treating social anxiety. In your study what is the independent variable?

(A) The subjects participating in the treatment group

(B) The treatment administered to group A

(C) The subjects in the no treatment group

(D) The level of social anxiety in the participants at the end of the study

(E) The assignment of the participants into the separate groups

B   The treatment administered to group A

The independent variable is defined as the variable that is to be manipulated or controlled, or that has been selected by the researcher. In this study, as the researcher, you are controlling whether or not participants receive therapy. The subjects that are participating in therapy and those that have been assigned to serve as the control group are the sample being used in this study. The sample simply means the participants chosen to represent the larger population. The level of social anxiety in the participants at the end of the study is considered to be the dependent variable. The dependent variable is defined as the response to the independent variable (or therapy), the observed or measured behavior, or the outcome of the study.

Question 40 of 40

A researcher studied the relationship between childhood exposure to lead and stature. The heights of the children measured at age 12 range from 4'8" to 5'9", with a standard deviation of 5", a mean of 5'3", a mode of 5'2", and a coefficient of variation of 7.9%. Which of the following statements is true?

(A) Variance is the square root of the standard deviation

(B) Range of a series of data provides information about the distribution of the data

(C) Coefficient of variation is a measure of the spread of the data in regard to the mean

(D) Standard deviation is an estimate of the standard error of a population

(E) Mode is a measure of central tendency of a data series

C   Coefficient of variation is a measure of the spread of the data in regard to the mean

The coefficient of variation is defined as the standard deviation divided by the mean, expressed as a percentage. It is a measure of the spread of the data with regard to the mean. The standard deviation is the positive square root of the variance. The standard error is an estimate of the standard deviation of a population. The range of a series of a data is calculated as the highest value in the series minus the lowest value, and it provides no information about the distribution of data within the series. The mode is the most commonly occurring value in a data series and does not provide any information about the central tendency of a data series.

A researcher is preparing a paper for publication on characteristics of hepatitis C infection in her local population. It includes exposure and treatment information. She reports that female sexual partners of men with hepatitis C virus are twice as likely than other women in the same population to contract the hepatitis C virus. This is a measure of

(A) Type I (alpha) error

(B) Odds ratio

(C) Prevalence

(D) Attributable risk

(E) Bias

Question 2 of 40

D   Attributable risk

Attributable risk, which can be determined from cohort studies, is a measure of the difference in occurrence of disease between exposed and unexposed populations. The likelihood that a positive result is due to chance is a measure of type I (alpha) error.

Prevalence is the amount of disease existing in a population at a certain point in time.

The odd ratio is a measure of the estimated relative risk occurring due to certain factors. Confounding variables may cause bias in studies.

In reporting the results from a clinical study of a new anti-inflammatory drug for the treatment of post-operative pain, the study's authors present data comparing the total days of hospitalization for comparable groups of patients who have received either the investigative anti-inflammatory drug or a placebo. The attached table appears in their report. Which of the following would be a valid interpretation of the data presented in this table?

(A) The p-value is greater than 0.05, indicating that there is no true treatment effect upon total days of post-operative hospitalization

(B) The treatment group and placebo groups have unequal numbers of participants, and therefore the statistical test results are not interpretable

(C) The results are suggestive of a true treatment effect, but the study has limited power to detect the effect due to the relatively small number of study subjects

(D) Statistical testing of two group means yields a t-value, not a p-value

Question 6 of 40

C   The results are suggestive of a true treatment effect, but the study has limited power to detect the effect due to the relatively small number of study subjects

While the p-value for the differences between the mean days of post-operative hospitalization is not below the conventional level of 0.05, it is relatively close to that value. The values of the treatment group and placebo group means (3.0 and 4.5 days, respectively) do suggest that there is an effect of treatment. It is likely that the statistical power of the study is rather limited, given the modest number of people enrolled in each group. Ideally, this study would be repeated with larger numbers of study subjects in each of the two groups. While it would be a mistake to conclude that there was definitively a treatment effect, it would also be a mistake to conclude that there was no evidence for a treatment effect, as well. In clinical trials, it is not necessary that the comparison groups have identical numbers of subjects, although there should be a sufficient number of participants in each study group to effectively evaluate the treatment being considered. While statistical testing of two group means may use the t-test, it is possible to derive a p-value from the use of this test.

Suppose that a researcher is using hypothesis testing to determine whether two treatments are equally effective. The hypotheses being tested are given below.

H0: Treatment A and Treatment B are equally effectiveHa: Treatment B is more effective than Treatment A

The study used an -level of = 0.05. The power of the test was 0.80. What is the probability that H0 will be rejected if in fact the two treatments are equally effective?

(A) 0.05

(B) 0.20

(C) 0.80

(D) 0.95

(E) It is impossible to tell from the information given

Question 9 of 40

A   0.05

When a researcher uses hypothesis testing, the researcher can never be certain that the conclusion he/she draws is correct. The decisions a researcher makes versus the truth can be portrayed by the following table.

  TRUTH

  Ho True Ha True

RESEARCHERACCEPTS Ho

Correct DecisionType II Error

(Probability )

RESEARCHERACCEPTS Ha

Type II Error(Probability )

Correct Decision

If H0 is true, but by chance the data suggested strong enough evidence against H0 to reject H0, then a type I Error has been committed. The probability of a Type I Error is the -level of the test. Therefore, if = 0.01, then only 1% of the time will data be strong enough to reject H0 when H0 is true, resulting in a Type I Error.

If Ha is true, but the evidence against H0 was not strong enough to reject H0, then a Type II Error has been committed. The power of a test is defined as the probability of rejecting H0 when Ha is in fact true (the ability of the test to correctly identify a significant difference). The power of a test is directly related to the probability of committing a Type II Error. The probability of a Type II Error is and the power of a test is given by (1 - ). One of the most common reasons for a Type II Error is due to sample size being too small. In general, the larger the sample size, the greater the power of the test.

A trial is carried out to determine the impact of a new diet combined with exercise in addition to conventional therapy to further reduce the risk of dying in patients recovering from heart surgery. Patients are assigned to one of the two study arms:

1- Conventional therapy only2- Conventional therapy plus new diet plus new exercise program.

Patients are followed up every two months for the first year and then every six months for the next four years. Among other factors, the following information is collected:1) Sex2) Age at time of surgery3) Weight (at entry into trial and at each visit)4) Percentage of body fat (at entry and at each visit)5) Survival status and date of death where applicable6) Need for further surgery and date where applicable7) A grading for actual activity level (1 to 5 with 1=Sedentary & 5=Very Active) Refer to the attached trial description. What study design is this?

(A) Case-Control study

(B) Cohort Study

(C) Randomized Clinical Trial

(D) Cross Over Study

(E) Cross Sectional

Question 11 of 40

C   Randomized Clinical Trial

Two study arms are present. In the first one, only the conventional therapy is present. In the second, diet and exercise are added to conventional therapy. This is, therefore, an experimental study. The patients are assigned to only one of the two study arms. Due to the nature of the intervention (diet plus exercise), patients are unblinded to their study group. This is a Randomized Clinical Trial. In a cross-over study, patients are assigned to one of the study arms for a period of time and then assigned to the other study arm for the same length of time. The other study designs mentioned are all observational studies. In case-control studies, people with and without a specific outcome are chosen. Then, looking backward in time, one tries to detect possible causes or risk factors. In cross sectional studies, data is collected at one time. Large governments surveys are good examples of cross sectional studies. In a cohort study, people are selected and followed over a period of time. At the beginning of the study, people are defined as being exposed or not exposed to certain risk factors. They are observed over time for the development of outcome. The outcome is then compared to exposure to risk factors.

A researcher wishes to compare the efficacy of a COX-2 inhibitor to that of ibuprofen for treatment of pain in patients with osteoarthritis. Using a visual analogue scale of 1-100, a difference of 15 points between the mean values of the treatment arms is considered to be clinically significant. Given that a true clinically relevant difference exists between the two therapies, which of the following is most true about the probability that the statistical test used in the study will fail to detect the difference?

(A) The probability decreases as decreases

(B) The probability is determined by the type-II error of the study

(C) The probability decreases as the increases

(D) The probability is impossible to determine without knowing the true mean

(E) The probability decreases as the power decreases

Question 14 of 40

B   The probability is determined by the type-II error of the study

Before a study is conducted, the researcher must select the significance level (a), which is the value used to interpret the result of the statistical test. The a level represents the probability that the statistical test used will detect a clinically significant difference due to chance alone. This is the chance of a type-I error. The a level does not predict the response of an individual patient, or the proportion of a sample that will have a particular therapeutic outcome.

The probability of a statistical test failing to detect a difference between means of two samples when such a difference truly exists, is the b or type-II error. As the level of significance increases, there is a greater chance of a type-I error, but less chance of a type II error, therefore, b decreases as a increases.

The ability of a statistical test to detect a difference between two means is the power of the test. Power is the probability that a statistical test will detect a difference when such a difference truly exists and is not due to chance. Power is the complement of b, and is equal to 1-b. Therefore, b decreases as power increases. As the level of significance, and the chance of a type-I error decreases, b increases. Power differs from a and b in that it is not a measure of error.

In a study of the effects of a new treatment for ovarian cancer on mortality, the level is 0.05 and the level is 0.20. What is the power of the study to detect a change in mortality from this new treatment?

(A) 5%

(B) 20%

(C) 25%

(D) 80%

(E) 95%

Question 17 of 40

D   80%

The power of a study is the ability of the study to detect a significant change when one exists. It is calculated as 1 - b, where b is the Type II error. In this case, 1 - b = 0.80, or 80%. Therefore, there is an 80% surety that this study has detected a change in mortality with this new treatment when one exists. Or, in other words, 20% of the time it will have missed a significant difference when one exists.

You and your colleagues are conducting a small clinical trial concerning the management of pediatric asthma. The clinical trial involves three different treatment arms and one placebo arm. The outcome of interest is hospitalization for respiratory distress. In one treatment arm (n=31), there are no patients that require hospitalization during the follow-up period (i.e., 0 events). What is the upper 95% confidence bound for the rate of hospitalization for the 31 subjects in this treatment arm?

(A) The upper 95% confidence bound cannot be calculated from the data provided

(B) 0

(C) 0.10

(D) 0.15

(E) 0.22

Question 20 of 40

C   0.10

The answer to this question is derived using the "rule of three" (as explained by Hanley and Hand, JAMA, 1983). When there are no events of interest observed in a particular group, the upper 95% confidence bound can be calculated by dividing 3 by the number of subjects in the group (i.e., n). In the question, 3/n is equivalent to 3/31 or 0.097. Rounding up produces the answer 0.10, and thus the largest rate that we would expect (with 95% confidence) would be 0.10 or approximately 3.0 events in this group of 31 study subjects. The 99% confidence bound can be obtained by using the "rule of 4.6" (i.e., 4.6/n), and the 99.9% confidence bound can be obtained using the "rule of 6.9" (i.e., 6.9/n). While this explanation will not go into the derivation of this rule, the calculations underpinning the convenient statistical device are sound and well-tested.

During a research rotation as a medical student, you spend several months gathering data on the use of a new oral vaccine to prevent a serious gastrointestinal disease in primates. Your research generates the attached table of data, and you are interested in using the 2 test to statistically test the association between vaccination status and the subsequent development of this particular gastrointestinal disease. After calculating the 2 value, you are interested in looking at a table of 2 values to determine the p-value that is associated with the 2 value that you obtained with the numbers shown in the table above. What would be the correct "degrees of freedom" associated with this table

(A) 1 degree of freedom

(B) 2 degrees of freedom

(C) 3 degrees of freedom

(D) 4 degrees of freedom

(E) 5 degrees of freedom

Question 32 of 40

A   1 degree of freedom

The shape of the c2 distribution changes according to the number of degrees of freedom (df) involved in a particular testing situation. Thus, in order to determine the correct p-value associated with a particular c2 value, it is necessary to know the correct degrees of freedom. For contingency tables, the correct degrees of freedom is obtained with the following formula: df = (r-1)(c-1), where r is the number of rows, and c is the number of columns. In a table with 2 rows and 2 columns, the c2 test will have 1 degree of freedom.

While doing morning rounds on the pediatric bone marrow transplantation unit at a large university-affiliated medical center, the attending hematologist-oncologist asks you about the allocation of patients to treatment groups in pediatric marrow transplantation clinical trials. How should you answer her question most correctly?

(A) Patients are allocated based on prognosis

(B) Patients are allocated based on parental preference

(C) Patients are allocated by random assignment

(D) Patients are allocated based on the attending physician's clinical judgment

     

(E) Clinical trials cannot be done with pediatric subjects

Question 36 of 40

C   Patients are allocated by random assignment

To effectively evaluate experimental agents or procedures, randomized clinical trials must be performed. Randomized clinical trials should be double-blinded in all but the most exceptional circumstances, and patient allocation should be achieved by a random process in which each patient has the same probability of being allocated to a specific treatment or control arm. Allocation based on prognosis, parental preference, or clinical judgment can lead to seriously biased results and flawed conclusions about the efficacy of the experimental treatment.