EPIDEMIOLOGY EXAM 2

Sensitivity

The ability of a test to correctly identify people who have disease.

Specificity

The ability of a test to correctly identify people who do not have disease.

Sensitivity Calculation

a/a+c

Specificity Calculation

d/b+d

Positive Predictive Value

proportion of positive test results that are true positives

Negative Predictive Value

proportion of negative test results that are true negatives.

PPV Calculation

(a)/(a+b)

NPV Calculation

d/c+d

Measures of Association

• relative risk

• prevlance raito

• odds ration

measures of occurance

• incidence

• prevalence

Relative Risk

Best for cohort studies, ratio of risk of disease in exposed versus unexposed

Relative Risk Calculation

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

Odds Ratio

Best for Case Control Study, compares the odds that people with the disease were exposed compared to those without the disease, will approximate the relative risk / risk ratio when prevalence ratio is less than 10% (rare disesase)

Odds Ratio Calculation

([a*d)/(b*c)]

Prevalence Ratios

Best for cross sectional study, having” the outcome, same calc as RR

Risk Difference

Risk of disease in the unexposed, if exposure was removed how would the risk change?

Risk Difference Calculation

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

Bias

A systematic error in design or conduct of study which leads to error in estimation

of association

Systematic Error

This leads to bias, confounding leads to this → does not arise by chance!

Random Error

Arises by chance, hard to account for

Selection Bias

How participants care chosen for a study.

how it happens:

• Participant selection procedure 

• Non compliance selective survival

• Loss to follow up/missing data

Types of Selection Bias

• Admission rate bias (includes Berkson’s)

• Prevalence-Incidence Bias (aka Neyman’s)

• Membership Bias (includes “healthy worker effect”)

• Non-response bias (includes volunteer and compliance bias)

• Loss to follow-up bias

Information Bias

The way information is collected in a study, can result in misclassification

Information Bias Types

• Interviewer bias: ​​Systematic error due to the interviewer’s conscious or sub-conscious gathering of selective data.

• Observer bias: Systematic difference between a true value and what was observed due to observer variation

• Detection bias: When individuals with certain exposures are under closer surveillance by medical care system

• Temporal bias

• Publication bias: Occurs because of the influence of study results on the chance of publication

Recall Bias

People with disease remember or report exposures differently (more or less accurately) than those without disease

Confounding

leads to systematic error, failure to control for common causes of the exposure and outcome

Validity

Accuracy, The ability of the test to correctly identify people with and without disease-> when test can actually do the thang, but how often its doing the thang we dont know: sensitivity and specificity

Reliability

Precision, The ability of the test to give the same result on repeated tests

• Interobserver variation

Screening

The examination of asymptomatic people in order to classify them as likely or unlikely to have disease. (not a diagnosis)-> wants to lead to a diagnostic test

Detectable Preclinical Phase

The period between the earliest time at which the disease can be detected by screening and the usual time that a diagnosis would be made for a symptomatic patient. -> mass screening best at this time, high risk is prioritized.

• When Dpcp is prevalent in pop, mass screening is cost effective and reasonable

• When dpcp prevalence is low, targetted screening of hugh risk is best

The Natural History of Disease

Biologic onset of disease pathology→ disease detectable by screening(DPCP here) diagnosis due to symptoms→treatment→ outcome

Lead Time

The interval between disease detection by screening and the time that the disease would have been diagnosed due to symptoms.-> amt of time that screening improves disease diagnosis

Lead Time Bias

•  Overestimation of survival duration among screened cases compared to unscreened cases when survival is measured from time of diagnosis to time of death.-> overestimation of screening benefits

Casuality

An event, condition, or characteristic without which the disease would not have occurred. permits rational plans and actions to break the links between the

factors causing disease, and disease itself.

Direct Casuality

Factor → Disease

Indirect Casuality

Factor→ Step 1→ Step 2→ Disease

Necessary

In presence of the factor, the disease develops.The factor is ______ to cause disease (cant do it alone, but the factor is needed w/ something else)

Sufficient

Factor inevitably causes disease, the factor ALONE can cause the disease

Bradford Hill Criteria

• Strength of the association

• 2. Consistency - replication

• 3. Specificity of the association

• 4. Temporality: cause must be present before effects

• 5. Biological gradient: higher exposure=higher disease

• 6. Plausibility

• 7. Coherence

• 8. Experiment

• 9. Analogy

Bradford Hill Criteria Limitations

• Strength:Depends on the prevalence of other causes of disease present in the population, not a biologic characteristic

• Consistency: There are plausible reasons for not seeing consistent results, and these exceptions are best seen with hindsight

• Specificity: A cause can have many effects

• Temporality: Difficult to establish

• Biologic gradient: Threshold effects

• Plausibility: Too subjective

• Coherence: Vague; too similar to plausibility

• Experiment: Not always available or feasible

• Analogy: Analogies abound

Diseases Appropriate for Screening

• Serious with major consequences

• Earlier identification leads to more effective

treatment

• Progressive with a detectable preclinical phase

(DPCP)

• DPCP is long and prevalent in the target

population