first aid Flashcards
Observational studies Study type: Case series
Design: Describes several individual patients with the same diagnosis, treatment, or outcome.
Measures/Example: Description of clinical findings and symptoms. Has no comparison group, thus cannot show risk factor association with disease.
Observational studies
Study type: Cross-sectional study
Frequency of disease and frequency of risk-related factors are assessed in the present.
Measures/Example: Asks, “What is happening?” Disease prevalence. Can show risk factor association with disease, but does not establish causality.
Observational studies
Study type: Case-control study
Design: Retrospectively compares a group of people with disease to a group without disease.
Measures/Example: Asks, “What happened?” Odds ratio (OR). Control the case in the OR. Patients with COPD had higher odds of a smoking history than those without COPD.
Observational studies
Study type: Cohort study
Design: Compares a group with a given exposure or risk factor to a group without such exposure.
Measures/Example: Looks to see if exposure or risk factor is associated with later development of disease. Can be prospective or retrospective. Disease incidence. Relative risk (RR). People who smoke had a higher risk of developing COPD than people who do not. Cohort = relative risk.
Observational studies
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Study type: Twin concordance study
Design: Compares the frequency with which both monozygotic twins vs both dizygotic twins develop the same disease.
Measures/Example: Measures heritability and influence of environmental factors (“nature vs nurture”).
Observational studies
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Study type: Adoption study
Design: Compares siblings raised by biological vs adoptive parents.
Measures/Example: Measures heritability and influence of environmental factors.
Observational studies
Study type: Ecological study
Design: Compares frequency of disease and frequency of risk-related factors across populations.
Measures/Example: Measures population data not necessarily applicable to individuals (ecological fallacy). Used to monitor population health. COPD prevalence was higher in more polluted cities.
Design: Describes several individual patients with the same diagnosis, treatment, or outcome.
Observational studies Study type: Case series
Frequency of disease and frequency of risk-related factors are assessed in the present.
Measures/Example: Asks, “What is happening?”
Observational studies
Study type: Cross-sectional study
Design: Retrospectively compares a group of people with disease to a group without disease.
Observational studies
Study type: Case-control study
Design: Compares a group with a given exposure or risk factor to a group without such exposure.
Observational studies
Study type: Cohort study
Compares the frequency with which both monozygotic twins vs both dizygotic twins develop the same disease.
Observational studies
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Study type: Twin concordance study
Design: Compares siblings raised by biological vs adoptive parents.
Observational studies
Back of card:
Study type: Adoption study
Design: Compares frequency of disease and frequency of risk-related factors across populations.
Observational studies
Study type: Ecological study
Phase 1 clinics
- Small number of healthy volunteers
- Determine safety, dosage, side effects
- Assess pharmacokinetics and pharmacodynamics
Phase 2 clinical trials
- Larger number of patients with the condition/disease studied
- Assess if treatment has therapeutic effect
- Determine optimal dosage and explore adverse effects
Phase 3 clinical trial
- Large-scale study with randomized treatment and control groups
- Evaluate treatment efficacy, safety, and dosing under normal clinical conditions
- Typically involves hundreds to thousands of patients
Phase 4 clinical trial
- Post-marketing surveillance after drug approval
- Long-term safety and efficacy monitoring
- Observational studies, registries, and adverse event reporting
phase 5 clinical trial
- Continual monitoring of drug in general population
- Evaluate long-term safety and effectiveness
- Compare treatment with other available interventions
Crossover study
Definition: Compares the effect of a series of ≥2 treatments on a participant. Order in which participants receive treatments is randomized. Washout period occurs between treatments.
Allows participants to serve as their own controls.
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Bradford Hill criteria
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Definition: A group of principles that provide limited support for establishing evidence of a causal relationship between presumed cause and effect.
Definition: A group of principles that provide limited support for establishing evidence of a causal relationship between presumed cause and effect.
Bradford Hill criteria
Bradford Hill criteria
Strength:
- Association does not imply causation, but the stronger the association, the more evidence for causation
Bradford Hill criteria Consistency:
Repeated observations of the findings in multiple distinct samples.
Bradford Hill criteria
Strength:
Association does not imply causation, but the stronger the association, the more evidence for causation
Bradford Hill criteria
Consistency
Repeated observations of the findings in multiple distinct samples.
Bradford Hill criteria
Specificity
The more specific the presumed cause is to the effect, the stronger the evidence for causation
Bradford Hill Criteria:
Temporality
The presumed cause precedes the effect by an expected amount of time.
Bradford Hill Criteria: Biological gradient
Greater effect observed with greater exposure to the presumed cause (dose-response relationship).
Bradford Hill Criteria:
Plausibility
A conceivable mechanism exists by which the cause may lead to the effect
Bradford Hill Criteria: Coherence
The presumed cause and effect do not conflict with existing scientific consensus.
Bradford Hill Criteria: Experiment
Empirical evidence supporting the presumed cause and effect (eg, animal studies, in vitro studies).
Bradford Hill Criteria: Analogy
The presumed cause and effect are comparable to a similar, established cause and effect.
Odds ratio
Typically used in case-control
studies. Represents the odds of
exposure among cases (a/c) vs odds
of exposure among controls (b/d).
OR = 1 odds of exposure are
equal in cases and controls.
OR > 1 odds of exposure are
greater in cases.
OR < 1 odds of exposure are
greater in controls.
Relative risk
Typically used in cohort studies.
Risk of developing disease in the
exposed group divided by risk in
the unexposed group.
RR = 1 no association between
exposure and disease.
RR > 1 exposure associated with
disease occurrence.
RR < 1 exposure associated with disease occurrence.
Relative risk
reduction
The proportion of risk reduction
attributable to the intervention as
compared to a control.
Attributable
risk
.
The difference in risk between
exposed and unexposed groups
Absolute
risk
reduction
The difference in risk (not the
proportion) attributable to the
intervention as compared to a
control.
Number
needed to
treat
Number of patients who need to
be treated for 1 patient to benefit.
Lower number = better treatment.
Number
needed to
harm
Number of patients who need to
be exposed to a risk factor for 1
patient to be harmed. Higher
number = safer exposure.
Case fatality
rate
Percentage of deaths occurring
among those with disease.
Mortality
rate
Number of deaths (in general or
due to specific cause) within a
population over a period, typically
scaled to deaths per 1000 people
per year
Attack rate
Proportion of exposed people who
become ill.
Likelihood ratio
Sensitivity (true-positive rate
Proportion of all people with disease who test
positive, or the ability of a test to correctly
identify those with the disease.
Value approaching 100% is desirable for ruling
out disease and indicates a low false-negative
rate.
Specificity (true-negative rate
Proportion of all people without disease who
test negative, or the ability of a test to correctly
identify those without the disease.
Value approaching 100% is desirable for ruling
in disease and indicates a low false-positive
rate
Positive predictive
value
Probability that a person who has a positive test
result actually has the disease.
Negative predictive
value
Probability that a person with a negative test
result actually does not have the disease
Receiver operating
characteristic curve
ROC curve demonstrates how well a diagnostic
test can distinguish between 2 groups (eg,
disease vs healthy). Plots the true-positive rate
(sensitivity) against the false-positive rate
(1 – specificity).
The better performing test will have a higher
area under the curve (AUC), with the curve
closer to the upper left corner
Precision (reliability)
The consistency and reproducibility of a test. The absence of random variation in a test
Random error decrease precision in a test.
high precision = decrease standard deviation.
increased precision = increased statistical power (1 − β)
Accuracy (validity)
The closeness of test results to the true values. The absence of systematic error or bias in a test.
Systematic error decrease accuracy in a test.
Incidence
Prevalence
Increase in survival time causes what for incidence & prevalence
doesn’t effect incidence & increase prevalence
Increase in mortality time causes what for incidence & prevalence
no change in incidence & decreased prevalence
Faster recovery time causes what for incidence & prevalence
No change in incidence & decreased prevalence
Extensive vaccine administration causes what for incidence & prevalence
Decreased incidence & decreased prevelance
Decreased risk factors causes what for incidence & prevalence
decreased incidence & prevalence
Increased diagnostic sensitivity causes what for incidence & prevalence
Increased incidence & prevalence
Selection bias
Nonrandom sampling
or treatment allocation
of subjects such that
study population is not
representative of target
population
Most commonly a sampling
bias
Nonrandom sampling
or treatment allocation
of subjects such that
study population is not
representative of target
population
Most commonly a sampling
bias
Selection bias
Berkson bias (selection bias)
cases and/
or controls selected from
hospitals (bedside bias) are
less healthy and have different
exposures
Attrition bias (selection bias)
participants lost
to follow up have a different
prognosis than those who
complete the study
Recall bias
Awareness of disorder alters
recall by subjects; common in
retrospective studies
Measurement bias
Information is gathered in a
systemically distorted manner
Procedure bias
Subjects in different groups are
not treated the same
Observer-expectancy
bias
Researcher’s belief in the
efficacy of a treatment changes
the outcome of that treatment
(aka, Pygmalion effect)
Researcher’s belief in the
efficacy of a treatment changes
the outcome of that treatment
(aka, Pygmalion effect)
Observer-expectancy
bias
Subjects in different groups are
not treated the same
Procedure bias
Measurement bias
Information is gathered in a
systemically distorted manner