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Behavioral Sciences > Biostatistics and Preventive Medicine > Flashcards

Biostatistics and Preventive Medicine Flashcards

1
Q

Bias (Recruiting participants)

A

Selection bias

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2
Q

Colon Cancer Screening

A

Screening is by colonoscopy after the age of 50 every 10 years

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3
Q

What happens to incidence and prevalence if additional Federal research dollars are targeted to a specific condition

A
  • I = no change

- P = no change

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4
Q

Diagnostic Odds Ratio [DOR]

A

= LR+ / LR-

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5
Q

Late-look bias

Definition, association(s), solution(s)

A
  • Severely diseased individuals are not uncovered
  • Early mortality
  • Stratify by severity
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6
Q

Dependent Probability

A

P = P(A) * P(B I A)

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7
Q

Number needed to treat (NNT)

A

= 1 / ARR

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8
Q

Sensitivity (Recall, True Positive Rate [TPR])

A

= TP / (TP + FN)
= 1 - False Negative Rate [FNR]
- SNOUT

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9
Q

Incorrect results of statistical hypothesis

A
  • Type I error (alpha): stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis). (H0,H1)
  • Type II error (beta): stating that there is not an effect or difference when one exists (null hypothesis is not rejected when in fact it is false). (H1,H0)
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10
Q

Proportionate Mortality Rate (PMR)

A

Deaths from cause / All deaths

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11
Q

Selection bias

Definition, association(s), solution(s)

A
  • Sample is not representative
  • Berkson bias (population selected from hospital), healthy worker effect (study population is healthier than general population), Non-response bias (people included in a study are different from those who are not)
  • Randomization and independent sample
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12
Q

Crude Rate

A

Actual measured rate for the whole population

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13
Q

Correct results of statistical hypothesis

A
  • Stating that there is an effect or difference when one exists (null hypothesis [H0] is rejected in favor of alternative hypothesis [H1]). (H1,H1) which equals power (1-beta)
  • Stating that there is not an effect or difference when none exists (null hypothesis not rejected). (H0,H0) which equals a correct result
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14
Q

Binomials

A
  • Every term expanded is nCr x^n-r * y^r

- We can find a term that contains the factor x^r in an expansion of (x+y)^n by using nCn-r * x^r * y^n-r

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15
Q

What happens to incidence and prevalence if behavioral risk factors are reduced in the population at large

A
  • I = decrease

- P = decrease

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16
Q

t-test

A
  • 1 interval and 1 nominal

- 2 groups only

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17
Q

Randomized Controlled Trials (RCTs)

Definition, Advantages, Disadvantages

A
  • Experimental, prospective study in which subjects are randomly assigned to a treatment or control group. Could be single or double blinded study
  • Ad:
  • Minimize bias
  • Potential to demonstrate relationships because exposure is assigned randomly, which minimize confounding
  • Dis:
  • Costly and time consuming
  • Some interventions (like surgery) are not amenable to masking
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18
Q

Absolute Risk Reduction (ARR)

A

= [c/(c+d)] - [a/(a+b)]

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19
Q

What happens to incidence and prevalence if number of persons dying from the condition increases

A
  • I = no change

- P = decrease

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20
Q

Odds Ratio (OR)

A

= (ad) / (bc)

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21
Q

What happens to incidence and prevalence if new effective vaccine gains wide spread use

A
  • I = decrease

- P = decrease

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22
Q

Outcomes (definitions)

A

Results of each trial

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23
Q

Positive Predictive Value [PPV] (Precision)

A

= TP / (TP + FP)

- Varies directly with prevalence

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24
Q

False Discovery Rate [FDR]

A

= FP / (FP + TP)

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25
Q

Type II error (beta)

A
  • Also known as false-negative error
  • It is related to statistical power (1-beta), which is the probability of rejecting the null hypothesis when it is false.
  • To increase power and reduce beta error:
  • Increase sample size
  • Increase expected effect size
  • Increase precision of measurement
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26
Q

Randomized Clinical Trials (RCTs) phases

A
  • Phase I: small # of healthy volunteers to assess safety, toxicity, pharmacokinetics and pharmacodynamics
  • Phase II: small # of patients with disease of interest to assess treatment efficacy, optimal dosing, adverse effects
  • Phase III: large # of patients randomly assigned either to treatment under investigation or the best available treatment (or placebo) to compare the new treatment to the current standard of care
  • Phase IV: post-marketing surveillance of patients after treatment is approved to detect rare or long term adverse effects. can result in treatment being withdrawn from market
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27
Q

Probability of mutually non-exclusive events

A

P(A union B)= P(A) + P(B) - P(A intersection B)

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28
Q

Repeated measures ANOVA

A
  • 1 interval and 1 nominal

- More than 2 groups, linked data

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29
Q

Cross-Sectional Study

Definition, Advantages, Disadvantages

A
  • People in the population are examined the presence of a disease of interest at a given point in time (prevalence study)
  • Ad:
  • Provide an efficient means of examining a population
  • Can be used as a basis for diagnostic testing
  • Can be used to plan which health services to offer and where
  • Dis:
  • Cannot determine causal relationships
  • Risk or Incidence cannot be directly measured
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30
Q

Confidence Interval (CI)

A
  • Range of values within which the true mean of the population is expected to fall, with a specified probability
  • CI = mean +/- Z * (SEM)
  • For the 95% CI, Z= 1.96 (95% CI corresponds to p=0.05)
  • For the 99% CI, Z= 2.58
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31
Q

Osteoporosis Screening

A
  • Every women should be screened with bone densitometry at the age of 65 by DEXA scan
  • Prophylaxis with bisphosphonates to increase bone density
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32
Q

One-way ANOVA

A
  • 1 interval and 1 nominal

- 2 or more groups

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33
Q

Diabetes Mellitus Screening

A
  • Screening with fasting blood glucose (2 measurements over 125) or HbA1c < 6.5% for patients that have hypertension and/or hyperlipidemia
  • No clear recommendation for age to start screening in general population
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34
Q

Disease Rate

A

of actual cases / # of potential cases

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35
Q

Number needed to harm (NNH)

A

= 1 / AR

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36
Q

Tertiary Disease Prevention

A

Aims to reduce the disability or morbidity resulting from disease like some treatments and surgeries

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37
Q

Prevalence types

A
  • Point prevalence

- Period prevalence

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38
Q

Probability of an event

A

P(A) = n(A) / n(S)

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39
Q

Permutations

A
  • Order is important
  • When all objects are taken n!
  • When number of objects taken at a time from n nPr = n! / (n-r)!
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40
Q

F-Score

A
  • Harmonic mean of precision (PPV) and recall (Sensitivity)

- = 2 * [(precision * recall) / (precision + recall)]

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41
Q

Indications of Pneumococcal vaccination

A
  • Everyone above age of 65
  • Cochlear implant
  • CSF leak
  • Alcoholics
  • One vaccine above 65 only
  • Single revaccination after 5 years if the patient is immunocompromised or the first injection was prior to age 65
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42
Q

Sample points (definition)

A

Elements of the sample space

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43
Q

Relative Risk (RR)

A

= a/(a+b) / c/(c+d)

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44
Q

Trial (definition)

A

A repetition of experiment

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45
Q

Relative Risk Reduction (RRR)

A

= 1 - RR

46
Q

Specific Rate

A

Actual measured rate for subgroup of population

47
Q

Cohort Study

Assess what, Method(s) for data analysis

A
  • Single risk factor affecting many diseases

- Relative risk to estimate risk

48
Q

Independent Probability

A

P = P(A) * P(B)

49
Q

Abdominal Aortic Aneurysm Screening

A
  • All men above age of 65 with a history of smoking should be screened with an ultrasound
  • Aneurysm should be repaired if it is wider than 5 cm
  • Also screen 65-75 with a +ve family history
50
Q

What happens to incidence and prevalence if long-term survival rates for the disease are increasing

A
  • I = no change

- P = increase

51
Q

Probability of mutually exclusive events

A

P(A union B)= P(A) + P(B)

52
Q

Combinations

A
  • Order is not important
  • nCr = n! / r! (n-r)!
  • nC0= 1
  • nCn= 1
53
Q

Observer-expectancy bias

Definition, association(s), solution(s)

A
  • Researcher’s beliefs affect outcome
  • Pygamlion effect (experimenter expectations inadvertently communicated to subjects, who then produce the desired effects
  • Double blinded design
54
Q

False Positive Rate [FPR] (Fall out)

A

= FP / (FP + TN)

- Type I error

55
Q

Primary Disease Prevention

A

A method used to stop the disease before it starts like immunization and behavioral counseling

56
Q

Experiment (definition)

A

An activity with an observable result

57
Q

Normal Distribution

A
  • Mean = Median = Mode
  • 1 SD = 34% (68% on both sides)
  • 2 SD = 47.5% (95% on both sides)
  • 3 SD = 49.9% (99.7% on both sides)
58
Q

Case-fatality rate

A

Deaths from cause / # of persons with the disease or cause

59
Q

Positive Likelihood Ratio [LR+]

A

= TPR / FPR

60
Q

Standardized Rate (Adjusted Rate)

A

Adjusted rate to make groups equal on some factor

61
Q

Positive Skew Distribution

A
  • Mean > Median > Mode

- Asymmetry with longer tail on right

62
Q

What happens to incidence and prevalence if recovery from the disease is more rapid than it was 1 year ago

A
  • I = no change

- P = decrease

63
Q

Breast Cancer Screening

A
  • Mammography between (40-50). Age of maximum benefit is > 50 is clear in decreasing mortality
  • Screening is done every 2 years and can be stopped at age of 75
  • Selective estrogen receptor modulators (SERMs) like tamoxifen and raloxifene used as a prophylaxis in patients who are free of disease but with multiple first degree relatives with breast cancer (at least 2) results in a 50% to 60 % reduction in breast cancer
  • BRCA comes +ve, management remains undetermined
64
Q

Hypertension Screening

A

For all above age of 18 every 2 years

65
Q

Procedure (design) bias

Definition, association(s), solution(s)

A
  • Parts of study do not fit together
  • Non-comparable control group
  • Random assignment
66
Q

Case-Control Study

Definition, Advantages, Disadvantages

A
  • A series of cases are identified and a set of controls are sampled from the underlying population to estimate the frequency of exposure in the population at risk of the outcome
  • Ad:
  • Use smaller groups than cohort, thereby reducing cost
  • Can be used to study rare diseases and easily examine multiple risk factors
  • Dis:
  • Cannot calculate incidence or prevalence, but an odds ratio can be used to estimate a measure of relative risk
  • Retrospective data may be inaccurate owing to recall or survivorship biases
67
Q

Bias (Performing study)

A
  • Recall bias
  • Measurement bias
  • Procedure bias
  • Observer-expectancy bias
68
Q

Precision and Errors

A
  • Increased precision leads to increased statistical power (1-beta) and decreased standard deviation
  • Random error decreases precision
69
Q

Confidence Interval (CI) interpretation

A
  • If the 95% CI for a mean difference between 2 variables includes 0, then there is no significant difference and H0 is not rejected
  • If the 95% CI for odds ratio or relative risk includes 1, H0 is not rejected
  • If the CIs between 2 groups do not overlap, that means statistically significant difference exists
  • If the CIs between 2 groups overlap, that means no significant difference exists
70
Q

Probability of complement of an event

A

P(A’)= 1 - P(A)

71
Q

Negative Predictive Value [NPV]

A

= TN / (TN + FN)

- Varies inversely with prevalence

72
Q

Prevalence

A
  • # of existing cases / Total # of people in a population

- = Incidence * Duration of disease

73
Q

Conditional Probability

A

P(B I A) = P(A intersection B) / P(A)

74
Q

Variance

A

= (SD)^2

75
Q

Incidence

A

of new cases / # of people at risk

76
Q

Sample space (definition)

A

Set of all possible outcomes

77
Q

False Omission Rate [FOR]

A

= FN / (FN +TN)

78
Q

Cohort-Study

Definition, Advantages, Disadvantages

A
  • A group of people is assembled, none of whom has the outcome of interest, but all of whom could potentially experience the outcome. Incidence of outcome events is compared in the 2 exposure groups
  • Ad:
  • The only way to directly determine incidence
  • Can be used to assess the relationship of a given exposure to many diseases
  • In prospective studies, exposure is elicited without bias from a known outcome
  • Dis:
  • Time consuming and expensive
  • Assess only the relationship of disease to a few exposure factors
  • Require many subjects, which makes it difficult to study rare diseases
79
Q

Measurement bias

Definition, association(s), solution(s)

A
  • Gathering info distorts it
  • Hawthorne effect (subject’s behavior is altered because they are being studied)
  • Control group/placebo group and using objective, standardized, and previously tested methods of data collection that are planned ahead of time
80
Q

Negative Likelihood Ratio [LR-]

A

= FNR / TNR

81
Q

What happens to incidence and prevalence if contacts between infected persons and non-infected persons are reduced for airborne infectious disease

A
  • I = decrease

- P = decrease

82
Q

Accuracy and Errors

A

Systematic error decreases accuracy

83
Q

Receiver Operating Characteristic (ROC) Curve

A
  • Plotting sensitivity (y axis) against 1 - specificity (x axis)
  • The more the area under curve is the more better the test
  • More sharp plot on the y axis more better the test isC
84
Q

Attack Rate

A

Same as incidence but during an epidemic

85
Q

Chi-square

A
  • 2 nominal

- Any # of groups

86
Q

Recall bias

Definition, association(s), solution(s)

A
  • Subjects cannot remember accurately
  • Retrospective studies
  • Multiple sources to confirm info and decrease time from exposure to follow-up
87
Q

Specificity (True Negative Rate [TNR])

A

= TN / (TN + FP)
= 1 - False Positive Rate [FPR]
- SPIN

88
Q

Trade off between sensitivity and specificity

A
  • Possible cutoff values are ( A: 100% sensitivity, B: practical compromise between sensitivity and specificity, C: 100% specificity)
  • Lowering the cutoff value (from B to A) will increase FP and decrease FN thereby increases sensitivity and NPV while decreases specificity and PPV
  • Raising the cutoff value (from B to C) will increase the FN and decrease the FP thereby increases specificity and PPV while deceases sensitivity and NPV
89
Q

Negative Skew Distribution

A
  • Mean < Median < Mode

- Asymmetry with longer tail on left

90
Q

Case-Control Study

Assess what, Method(s) for data analysis

A
  • Many risk factors for a single disease

- Odds ratio to estimate risk

91
Q

What happens to incidence and prevalence if contacts between infected persons and non-infected persons are reduced for non-infectious disease

A
  • I = no change

- P = no change

92
Q

Events (definition)

A

Subset of the sample space

93
Q

Matched pairs t-test

A
  • 1 interval and 1 nominal

- 2 groups, linked data pairs, before and after

94
Q

Cross-Sectional Study

Assess what, Method(s) for data analysis

A
  • Association of a risk factor and a disease

- Chi-square to assess association

95
Q

Accuracy [ACC]

A

= (TP + TN) / Total population

96
Q

Lipid Screening

A
  • Cholesterol and LDL measurement is recommended for healthy individuals when:
  • Men are above age 35
  • women are above age 45
  • It is recommended for all patients with diabetes, hypertension, coronary artery disease or equivalent like carotid, aortic or peripheral artery disease
97
Q

Standard error of th mean (SEM)

A

= SD / square root of n

98
Q

Crude Mortality Rate

A

Deaths / population

99
Q

Measures of dispersion

A
  • Standard deviation

- Standard Error of the Mean (SEM): it is decreases as sample size (n) increases

100
Q

What happens to incidence and prevalence if new effective treatment is initiated

A
  • I = no change

- P = decrease

101
Q

Pearson Correlation

A
  • 2 interval
  • Is there a linear relationship?
  • r is always between -1 and +1. The closer the absolute value of r to 1, the stronger the linear correlation between the 2 variables
  • Positive r value means positive correlation (variables are directly related)
  • Negative r value means negative correlation (variables are inversely related
  • Coefficient of determination = r^2 (value that is usually reported)
102
Q

Prostate Cancer Screening

A
  • 25% of patients with prostate cancer have normal PSA levels
  • 25% of those with elevated PSA levels have no prostate cancer
  • No benefit of PSA on mortality
  • Do it if the patient asks for it
103
Q

Type I error (alpha)

A
  • Also known as false-positive error
  • It is judged by p value. if p < 0.05, then there is less than a 5% chance that the data will show something that is not really there
104
Q

Cause-specific mortality rate

A

Deaths from cause / population

105
Q

Bias (Interpreting results)

A
  • Confounding bias
  • Lead-time bias
  • Late-look bias
106
Q

Attributable Risk (AR)

A

= [a/(a+b)] - [c/(c+d)]

107
Q

Secondary Disease Prevention

A

The detection of the disease early in its course to reduce the associated morbidity and mortality like screening tests

108
Q

Cervical Cancer Screening

A
  • Pap smear is done from 21 to 65 years of age every 3 years
  • Adding HPV testing to pap smear increases interval to 5 years
  • HPV vaccine is routine for all women between ages of 11 and 26
  • Chlamydia screen for women 15-25 years old
109
Q

Indications of Influenza vaccine

A
  • Everyone yearly
  • Healthcare workers
  • Pregnant women
110
Q

False Negative Rate [FNR] (Miss Rate)

A

= FN / (FN + TP)

- Type II error

111
Q

Confounding bias

Definition, association(s), solution(s)

A
  • Unanticipated factors obscure results
  • Hidden factors affect results
  • Multiple/repeated studies, Cross-over studies (subjects act as their own controls), Matching (patients with similar characteristics in both treatment and control groups), Restriction and Randomization
112
Q

Lead-time bias

Definition, association(s), solution(s)

A
  • Early detection confused with increased survival
  • Benefits of screening
  • Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)

Behavioral Sciences (6 decks)

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