USMLE Step 2 (Fach) / Epidemiology & Stats (Lektion)

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• Prevention Primary prevention:- Prevent the onset of specific diseases via risk reduction by altering behaviors or exposures that can lead to disease, or by enhancing resistance to the effects of exposure to a disease ...
• Randomized controlled trials Aim: determines the possible effect of a specific intervention on a population of interest Study method: patients are randomly allocated as either treatment or control subjects, after which they are monitored ...
• Clinical drug trials Studies involving human subjects to assess new health interventions to provide safe and effective medical care- Compares the benefits of a single treatment vs. a placebo or between 2 or more drugs Preclinical ...
• Case-control study Aim: to study if an exposure is associated with an outcome (e.g., disease) Study method:1. Researchers begin by selecting patients with the disease (cases) and without the disease (controls) with matching ...
• Selection biases Ascertainment (sampling) bias: Study population differs from target population due to nonrandom selection methods Nonresponse bias: High nonresponse rate to surveys/questionnaires can cause errors if ...
• Observational biases Recall bias: Common in retrospective studies, subjects with negative outcomes are more likely to report certain exposures than control subjects Observer bias: Observers misclassify data due to individual ...
• Analysis of variance (ANOVA) Calculates the statistically significant difference between ≥ 3 independent groups by comparing their means (an extension of the t-test). One-way analysis of variance:- Assesses 1 variable (e.g., the ...
• Chi-square test Categorical test (test used to evaluate the statistically significant difference between groups with categorical variables)Categorical variable (nominal variable): A variable that has two or more categories ...
• Ecological study Aim: to identify an exposure with an outcome (eg, disease), especially if the outcome is rare Study method: assess aggregated data where at least one variable (eg, an outcome) is at a population level ...
• Ascertainment bias Sampling bias Study population differs from target population due to nonrandom selection methods. Occurs when the results from an atypical population are extrapolated into the entire population.
• Berkson bias Disease studied using only hospital-based patients may lead to results not applicable to target population.
• Survival (prevalence-incidence or Neyman) bias Exposures that happen long before disease assessment can cause study to miss diseased patients that die early or recover. Eg, a hospital-based study on snow shoveling and myocardial infarction will miss ...
• Attrition bias Significant loss of study participants may cause bias if those lost to follow-up differ significantly from remaining subjects.
• Reporting bias Subjects over- or under-report exposure history due to perceived social stigmatization.
• Surveillance (detection) bias Risk factor itself causes increased monitoring in exposed group relative to unexposed group, which increases probability of identifying a disease.An outcome (e.g., disease) is diagnosed more frequently ...
• Types of epidemiological studies Descriptive studies: Studies that try to identify individual characteristics (age, sex, occupation), place (e.g., residence, hospital), or time of events (e.g., during diagnosis, reporting) in relation ...
• Descriptive studies Case report: a report of a disease presentation, treatment, and outcome in a single subject or event- Example: report of a single case of cervical cancer in a 25-year-old female subject Case series report: ...
• Factorial study Aim: to test the effect and interactions of two or more factors (e.g., treatments) Study method: Individuals are randomly assigned to groups receiving different doses and combinations of drugs. Example: ...
• Crossover study Aim: to obtain a more efficient comparison of treatments with fewer patients Study method: each patient switches from one treatment to another during the trial period and serves as their own control Example: ...
• Cross-sectional study (prevalence study) Aim: to determine the prevalence of exposure and disease Study method: the prevalence of disease and other variables (e.g., risk factors) are measured simultaneously at a particular point in time (i.e., ...
• Cohort study Aim: to study the incidence rate and whether the exposure is associated with the outcome of interest (e.g., a disease) Study method and examples:- Retrospective cohort study→ Starts with individuals ...
• Absolute risk ∼ Incidence rate Measures the probability of acquiring disease/injury in a given study population Used in cohort studies Formula: (number of new cases) / (total individuals at risk of developing disease) ...
• Relative risk (RR; risk ratio) The risk of an outcome (e.g., disease) among one group compared to the risk among another group Measures how strongly a risk factor (e.g., death/injury/disease) in exposed individuals is associated with ...
• Attributable risk (AR) The proportion of cases in exposed individuals that can be attributed to the exposure Used in cohort studies Formula- Population AR: (incidence rate entire study population) - (incidence rate in unexposed ...
• Odds ratio (OR) Compares the odds of exposure in individuals with disease/injury to those without disease/injury Used in case-control studies Rare disease assumption- Since case control studies do not track patients ...
• Absolute risk reduction (ARR) The difference in risk as a result of an intervention compared to the control group (e.g., risk of death) Formula: risk in intervention group – risk in control group = (c/(c + d)) – (a/(a + b))
• Number needed to treat (NNT) The number of individuals that must be treated, in a particular time period, for one person to benefit from treatment (i.e., not develop disease/injury) Formula: 1/absolute risk reduction (ARR)
• Number needed to harm (NNH) The number of individuals who need to be exposed to a certain risk factor before one person develops disease/injury Formula: 1/attributable risk (AR)
• Hazard ratio The measure of an effect of an intervention on an outcome (death/cure) over a period of timeWhile similar to the risk ratio, the risk ratio only takes into account the occurrence of the event, not the ...
• Allocation bias A systematic difference in the way that participants are assigned to treatment or intervention groups E.g., assigning all female patients to one group and all male patients to another group
• Recall bias Awareness of condition by subjects changes their recall of related risk factors; common in retrospective studies Example: Subjects recall a certain exposure after finding out about others with the same ...
• Response bias Study participants do not respond truthfully or accurately because of the manner in which questions are phrased (e.g., leading questions) and/or the possibility of more socially acceptable answer options; ...
• Observer bias (Experimenter-expectancy effect or Pygmalion ... Measurement of a variable or classification of subjects is influenced by the experimenter's knowledge or expectations
• Confirmation bias The tendency of the investigator to include only those results which support his/her hypothesis and ignore the rest
• Hawthorne effect Subject's change their behavior once they are aware that they are being observed; especially relevant for psychiatric research; difficult bias to eliminate
• Lead-time bias Lead time: the average length of time between detection of a disease and the predetermined outcomeEarly detection of disease is misinterpreted as increased survival Example:- Often discussed in the context ...
• Length-time bias A phenomenon whereby a screening test preferentially detects less aggressive forms of a disease and therefore increases the apparent survival time.Length-time bias occurs because the duration of observation ...
• Confounding Definition: any third variable that has not been considered in the study but that correlates with the exposure and the outcome Example: A confounder can be responsible for the observed relationship between ...
• Effect modification Definition: a third variable that positively or negatively influences a study outcome; occurs when the exposure has a different effect between groups; not considered a type of bias in itself Example: ...
• Sensitivity and specificity Sensitivity (true positive rate):- The proportion of individuals that correctly register as positive in a clinical test designed to identify a disease- A test with a high sensitivity will yield a low ...
• Verifying the presence or absence of a disease Screening test:- Used to identify disease in asymptomatic individuals. E.g., mammogram for breast cancer or a Pap smear for cervical cancer- Should have a high sensitivity Confirmatory test:- Confirms ...
• Receiving operating characteristic curve (ROC curve) ... A graph that compares the sensitivity and specificity of a diagnostic test Used to show the trade-off between clinical sensitivity and specificity for every possible cutoff value to evaluate the ability ...
• T-test Calculates the difference between the means of two samples (E.g., comparing the mean heart rate between men and women) Two sample t-test: Calculates whether the means of two groups differ from one another ...
• Normal distribution (Bell curve, Gaussian distribution) ... Normal distributions differ according to their mean and variance, but share the following characteristics: The same basic shape; the following assumptions about the data distribution can be made:- 68% ...
• Nonnormal distributions Bimodal distribution:- Data distribution with two peaks (a peak = mode (epidemiology)- Two subgroups within the study population Positively skewed distribution- Data set that is skewed to the right- Mean ...
• Non-parametric tests Definition: tests used to evaluate the statistically significant difference between groups when the sample has non-normal distribution and the sample size is small. Spearman correlation coefficient:- ...
• Screening HIV test: at least once in life between 13-64 years of age High blood pressure: annually in patients > 40 years Pap smear: every 3 years starting at 21 years or every 5 years at 30 years, if combined ...
• Attributable risk percent (ARP) The percentage of incidence of disease among exposed individuals that can be attributed to the exposure Formula: ARP = (RR - 1)/RR Alternatively, ARP = AR/(incidence of disease in exposed group) * 100
• Likelihood ratio Determines the utility of a diagnostic test in clinical practice; likelihood ratio is not influenced by disease prevalence Reflects how much more likely the disease is in a person with a positive (positive ...
• Intention-to-treat analysis All patients who initially enrolled in the study (including drop-outs) are included in the analysis of study data; helps to reduce selection bias; preserves randomization

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