Cross-sectional study
Collects data from a group of people to assess frequency of disease at a particular point in time ("snap-shot").Asks, "What is happening?" Measures disease prevalence.Can show risk factor association with disease, but does not establish casuality.
Case-control study
Compares a group of people with disease to a group without disease.Looks to see if odds of prior exposure or risk factor differs by disease state.Asks, "What happened?" Almost always retrospective. Measures odds ratio (OR).Patients with COPD had higher odds of a smoking history than those without COPD.
Cohort study
Compares a group with a given exposure or risk factor to a group without such exposure. Looks to see if exposure or risk factor is associated with later development of disease. Can be prospective (asks, "Who will develop disease?") or retrospective (asks, "Who developed the disease [exposed vs nonexposed]?). Measures relative risk (RR).Smokers had a higher risk of developing COPD than nonsmokers.
Clinical trial
Experimental study involving humans. Compares therapeutic benefits of 2 or more treatments, or of treatment and placebo. Study quality improves when study is randomized, controlled, and double-blined. Triple-blind refers to the additional blinding of the researchers analyzing the data. Phase I: Small number of healthy volunteers or patients with disease of interest."Is it safe?" Assesses safety, toxicity, pharmacokinetics, and pharmacodynamics. Phase II: Moderate number of patients with disease of interest."Does it work?" Assesses treatment efficacy, optimal dosing, and adverse effects. Phase III: Large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo)."Is it good or better?" Compares the new treatment to the current standard of care. Phase IV: Postmarketing surveillance of patients after treatment is approved."Can it stay?" Detects rare or long-term adverse effects. Can result in treatment being withdrawn from market.
Sensitivity (true-positive rate)
Proportion of all people with disease who test positive, or the probability that when the disease is present, the test is positive. Value approaching 100% is desirable for ruling out disease and indicates a low false-negative rate. High sensitivity test used for screening in diseases with low prevalence. = TP/(TP + FN)= 1 - FN rate If sensitivity is 100%, then FN is zero. So, all negatives must be TNs.
Specificity (true-negative rate)
Proportion of all people without disease who test negative, or the probability that when the disease is absent, the test is negative. Value approaching 100% is desirable for ruling in disease and indicates a low false-positive rate. High specificity test used for confirmation after a positive screening test. = TN/(TN + FP)= 1 - FP rate If specificity is 100%, then FP is zero. So, all positives must be TPs.
Positive predictive value
Proportion of positive test results that are true positive. Probability that a person who has a positive test result actually has the disease. PPV = TP/(TP + FP) PPV varies directly with pretest probability (baseline risk, such as prevalence of disease). High pretest probability → high PPV
Negative predictive value
Proportion of negative test results that are true negative. Probability that a person with a negative test result actually does not have the disease. NPV = TN/(TN+FN) NPV varies inversely with prevalence or pretest probability.
Incidence vs prevalence
Incidence = # of new cases/# of people at risk (during a specified time period) Prevalence = # of existing cases/total # of people (at a point in time) Prevalence/1-prevalence = incidence rate x average duration of disease Prevalence ≈ incidence for a short duration disease (eg, common cold).Prevalence > incidence for chronic diseases, due to large # of existing cases (eg, diabetes). Prevalence ~ pretest probability.↑ prevalence → ↑ PPV and ↓ NPV.
Odds ratio
Typically used in case-control studies. Odds ratio depicts the odds of a certain exposure given an event (eg, disease) vs the odds of exposure in the absence of that event (eg, no disease). Odds that the group with the disease (cases) was exposed to a risk factor divided by the odds that the group without the disease (controls) was exposed. OR = (a/c)/(b/d)
Relative risk
Typically used in cohort studies. Risk of developing disease in the exposed group divided by the risk in the unexposed group (eg, if 21% of smokers develop lung cancer vs 1% of nonsmokers, RR = 21. For rare diseases (low prevalence), OR approximates RR. RR = 1 → no associationRR >1 → exposure associated with ↑ disease occurenceRR = 1 → exposure associated with ↓ disease occurence RR = (a/[a+b])/(c/[c+d])
Attributable risk
The difference in risk between exposed and unexposed groups, or the proportion of disease occurrences that are attributable to the exposure (eg, if risk of lung cancer in smokers is 21% and the risk in nonsmokers is 1%, then 20% of lung cancer risk in smokers is attributable to smoking). AR = a/(a+b) - c/(c+d)
Relative risk reduction
The proportion of risk reduction attributabe to the intervention as compared to a control (eg, if 2% of paitents who receive a flu shot develop the flu, while 8% of unvaccinated patients develop the flu, then RR = 2/8 = 0.25, and RRR = 0.75) RRR = 1 - RR
Absolute risk reduction
The difference in risk (not the proportion) attributable to the intervention as compared to a control (eg, if 8% of people who receive a placebo vaccine develop the flu vs. 2% of people who receive a flu vaccine, then ARR = 8%-2% = 6% = 0.06) ARR = c/(c+d) - a/(a+b)
Number needed to treat
Number of patients who need to be treat for 1 patient to benefit.Lower number = better treatment. NNT = 1/ARR (absolute risk reduction)
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. NNH = 1/AR (attributable risk)
Selection bias
Nonrandom sampling or treatment allocation of subjects such that study population is not representative of target population. Most commonly a sampling bias. Berkson bias – study population selected from hospital is less healthy than general population Healthy worker effect – study population is healthier than the general population Non-response bias – participating subjects differ from nonrespondents in meaningful ways Strategies to reduce bias: Randomization; ensure the choice of the right comparison/reference group.
Measures of central tendency
Mean = (sum of values)/(total number of values)- Most affected by outliers (extreme values). Median = middle value of a list of data sorted from least to greatest- If there is an even number of values, the mean will be the average of the middle two values. Mode = most common value- Least affected by outliers.
Measures of dispersion
Standard deviation = how much variability exists in a set of values, around the mean of these values.σ = SD; n = sample sizeVariance = (SD)2 Standard error = an estimate of how much variability exists in a (theoretical) set of sample means around the true population mean.SE = σ/√nSE ↓ as n ↑
Nonnormal distributions
Bimodal: Suggests two different populations (eg, metabolic polymorphism such as fast vs slow acetylators; age at onset of Hodgkin lymphoma; suicide rate by age). Positive skew: Typically, mean > median > modeAsymmetry with longer tail on right. Negative skew: Typically, mean < median < modeAsymmetry with longer tail on left.
Statistical hypotheses
Null (H0): Hypothesis of no difference or relationship (eg, there is no association between the disease and the risk factor in the population). Alternative (H1): Hypothesis of some difference or relationship (eg, there is some association between the disease and the risk factor in the population).
Type I error (α)
Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis).Also known as false-positive error. α is the probability of making a type I error. p is judged against a preset α level of significance (usually 0.05). If p < 0.05, then there is less than a 5% chance that the data will show something that is not really there. You can never "prove" the alternative hypothesis, but you can reject the null hypothesis as being very unlikely.
Type II error (β)
Stating that there is not an effect or difference when one exists (null hypothesis is not rejected when it is in fact false).Also known as false-negative error. β is the probability of making a type II error. β is related to statistical power (1-β), which is the probability of rejecting the null hypothesis when it is false. ↑ power and ↓ β by:- ↑ sample size- ↑ expected effect size- ↑ precision of measurement
Confidence interval
Range of values within which the true mean of the population is expected to fall, with a specified probability. CI = mean ± Z(SE) The 95% CI (corresponding to α = 0.05) is often used. For the 95% CI, Z=1.96For the 99% CI, Z=2.58 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 two groups do not overlap → statistically significant difference exists.If the CIs between two groups overlap → usually no significant difference exists.
Twin concordance study
Compares the frequency with which both monozygotic twins vs both dizygotic twins develop the same disease. Measures heritability and influence of environmental factors ("nature vs nurture").
Likelihood ratio
Likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without the target disorder. LR+ >10 and/or LR- <0.1 indicate a very useful diagnostic test. LRs can be multiplied with pretest odds of disease to estimate posttest odds. LR+ = Sensitivity/(1-Specificity) = TP rate/FP rateLR- = (1-Sensitivity)/Specificity = FN rate/TN rate
Precision vs accuracy
Precision (reliability): The consistency and reproducibility of a test. The absence of random variation in a test.Random error ↓ precision in a test.↑ precision → ↓ standard deviation.↑ precision → ↑ statistical power (1-β). Accuracy (validity): The trueness of test measurements. The absence of systematic error or bias in a test.Systematic error ↓ accuracy in a test.
Meta-analysis
A method of statistical analysis that pools summary data (eg, means, RRs) from multiple studies for a more precise estimate of the size of an effect. Also estimates heterogeneity of effect sizes between studies. Improves strength of evidence and generalizability of study findings. Limited by quality of individual studies and bias in study selection.
Common statistical tests
t-test: Checks differences between means of 2 groups.Example: comparing the mean blood pressure between men and women. ANOVA (Analysis of variance): Checks differences between means of 3 or more groups. Example: comparing the mean blood pressure between members of 3 different ethnic groups. Chi-square (χ2): Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values).Example: comparing the percentage of members of 3 different ethnic groups who have essential hypertension.
Informed consent
A process (not just a document/signature) that requires:- Disclosure: discussion of pertinent information- Understanding: ability to comprehend- Capacity: ability to reason and make one's own decisions (distinct from competence, a legal determination)- Voluntariness: freedom from coercion and manipulation Patients must have an intelligent understanding of their diagnosis and the risks/benefits of proposed treatment and alternative options, including no treatment.Patient must be informed that he or she can revoke written consent at any time, even orally. Exceptions to informed consent:- Waiver – patient explicitly waives the right of informed consent- Legally incompetent – patient lacks decision-making capacity (obtain consent from legal surrogate)- Therapeutic privilege – withholding information when disclosure would severely harm the patient or undermine informed decision-making capacity- Emergency situation – implied consent may apply
Consent for minors
A minor is generally any person <18 years old. Parental consent laws in relation to healthcare vary by state. In general, parental consent should be obtained, but exceptions exist for emergency treatment (eg, blood transfusions) or if minor is legally emancipated (eg, married, self supporting, or in the military). Situations in which parental consent is usually not requires:- Sex (contraception, STIs, pregnancy)- Drugs (substance abuse)- Rock and roll (emergency/trauma)
Surrogate decision-maker
If a patient loses decision-making capacity and has not prepared an advance directive, individuals (surrogates) who know the patient must determine what the patient would have done. Priority of surrogates: spouse → adult children → parents → siblings → other relatives.
Confidentiality
Confidentiality respects patient privacy and autonomy. If the patient is incapacitated or the situation is emergent, disclosing information to family and friends should be guided by professional judgment of patient's best interest. The patient may voluntarily waive the right to confidentiality (eg, insurance company request). General principles for exceptions to confidentiality:- Potential physical harm to others is serious and imminent- Likelihood of harm to self is great- No alternative means exist to warn or to protect those at risk- Physicians can take steps to prevent harm Examples: - Suicidal/homicidal patients- Abuse- Duty to protect – state-specific laws that sometimes allow physician to inform or somehow protect potential victim from harm- Epileptic patients and other impaired automobile drivers- Reportable diseases (eg, STIs, hepatitis, food poisoning); physicians may have a duty to warn public officials, who will then notify people at risk. Dangerous communicable diseases, such as TB or Ebola, may require involuntary treatment.
Car seats for children
Children should ride in rear-facing car seats until they are 2 years old. Children should ride in car seats with a harness until they are 4 years old. Older children should use a booster seat until they are 8 years old or until the seat belt fits properly. Children <12 years old should not ride in a seat with a front-facing airbag.
Major medical insurance plants
Exclusive provider organization:Providers: Restricted to limited panel (except emergencies)Specialist care: No referral required Health maintenance organization:Providers: Restricted to limited panel (except emergencies)Payments: Denied for any service that does not meet established, evidence-based guidelinesSpecialist care: Requires referral from primary care provider- Low monthly premiums, low copayments and deductibles, and low total cost for the patient. Point of service:Provider: Patient can see providers outside networkPayments: Higher copays and deductibles for out-of-network servicesSpecialist care: Requires referral from primary care provider Preferred provider organization:Provider: Patient can see providers outside of networkPayments: Higher copays and deductibles for all servicesSpecialist care: No referral required
Healthcare payment models
Bundled payment: Healthcare organization receives a set amount per service, regardless of ultimate cost, to be divided among all providers and facilities involved. Capitation: Physicians receive a set amount per patient assigned to them per period of time, regardless of how much the patient uses the healthcare system. Used by some HMO. Discounted fee-for-service: Patient pays for each individual service at a discounted rate predetermined by providers and payers (eg, preferred provider organizations). Fee-for-service: Patients pays for each individual service. Global payment: Patient pays for all expenses associated with a single incident of care with a singal payment. Most commonly used during elective surgeries, as it covers the cost of surgery as well as the necesesary pre- and postoperative visits.
Medicare and Medicaid
Medicare and Medicaid – federal social healthcare programs that originated from amendments to the Social Security Act. Medicare is available to patients ≥65 years old <65 with certain disabilities, and those with end-stage renal disease.- Part A: Hospital insurance, home hospice care- Part B: Basic medical bills (eg, doctor's fees, diagnostic testing)- Part C: (parts A+B) delivered by approved private companies- Part D: Prescription drugs Medicaid is joint federal and state health assitance for people with limited income and/or resources.
Hospice care
Medical care focused on providing comfort and palliation instead of definitive cure. Available to patients on Medicare or Medicaid and in most private insurance plans whose life expectancy is <6 months. During end-of-life care, priority is given to improving the patient's comfort and relieving pain (often includes opioid, sedative, or anxiolytic medications). Facilitating comfort is prioritized over potential side effects (eg, respiratory depression). This prioritization of positive effects over negative effects is known as the principle of double effect.
Core ethical principles
Autonomy: Obligation to respect patients as individuals (truth-telling, confidentiality), to create conditions necessary for autonomous choice (informed consent), and to honor their preference in accepting or not accepting medical care. Beneficence: Physicians have a special ethica (fiduciary) duty to act in the patient's best interest. May conflict with autonomy (an informed patient has the right to decide) or what is best for society (eg, mandatory TB treatment). Traditionally, patient interest supersedes. Nonmaleficence: "Do no harm." Must be balanced against beneficience; if the benefits outweigh the risks, a patient may make an informed decision to proceed (most surgeries and medications fall into this category). Justice: To treat persons fairly and equitably. This does not always imply equally (eg, triage).
Recall bias
Awareness of disorder alters recall by subjects; common in retrospective sudies. Example: Patient with disease recall exposure after learning of similar cases. Strategy to reduce bias: Decrease time from exposure to follow-up.
Measurement bias
Information is gathered in a systematically distorted manner. Example: Association between HTN and MI not observed when using faulty automatic sphygmomanometer.- Hawthorne effect – participants change behavior upon awareness of being observed. Strategy to reduce bias: Use objective, standardized, and previously tested methods of data collection that are planned ahead of time. Use placebo group.
Procedure bias
Subjects in different groups are not treated the same. Example: Patients in treatment group spend more time in highly specialized hospital units. Strategy to reduce bias: Blinding and use of placebo reduce influence of participants and researchers on procedures and interpretation of outcomes as neither are aware of group allocation.
Observer-expectancy bias
Researcher's belief in the efficacy of a treatment changes the outcome of that treatment (aka, Pygmalion effect). Example: An observer expecting treatment group to show signs of recovery is more likely to document positive outcomes. Strategy to reduce bias: Blinding and use of placebo reduce influence of participants and researchers on procedures and interpretation of outcomes as neither are aware of group allocation.
Confounding bias
When a factor is related to both the exposure and outcome, but not on the causal pathway, it distorts or confuses effect of exposure on outcome.Contrast with effect modification. Example: Pulmonary disease is more common in coal workers than the general population; however, people who work in coal mines also smoke more frequently than the general population. Strategies to reduce bias: Multiple/repeated studies. Crossover studies (subjects act as their own controls). Matching (patients with similar characteristics in both treatment and control groups).
Lead-time bias
Early detection is confused with ↑ survival. Example: Early detection makes it seem like survival has increased, but the disease's natural history has not changed. Strategy to reduce bias: Measure "back-end" survival (adjust survival according to the severity of disease at the time of diagnosis).
Length-time bias
Screening test detects diseases with long latency period, while those with shorter latency period become symptomatic earlier.This can lead to an apparent improvement of survival when a terminal disease with a long clinical course is screened. Example: A slowly progressive cancer is more likely detected by a screening test than a rapidly progressive cancer. Strategy to reduce bias: A randomized controlled trial assigning subjects to the screening program or to no screening.
Normal distribution
Gaussian, also called bell-shaped. Mean = median = mode. -1σ to +1σ = 68%-2σ to +2σ = 95%-3σ to +3σ = 99.7%
Correct result
Stating that there is an effect or difference when one exists (null hypothesis rejected in favor of alternative hypothesis). Stating that there is no effect or difference when none exists (null hypothesis not rejected).
Pearson correlation coefficiant
r is always between -1 and +1. The closer the absolute value of r is to 1, the stronger the linear correlation between the 2 variables. Positive r value → positive correlation (as one variable ↑, the other variable ↑).Negative r value → negative correlation (as one variable ↑, the other variable ↓). Coefficient of determination = r2 (amount of variance in one variable that can be explained by variance in another variable).
Decision-making capacity
Physician must determine whether the patient is psychologically and legally capable of making a particular healthcare decision. Note that decisions made with capacity cannot be revoked simply if the patient later loses capacity. Capacity is determined by a physician for a specific healthcare-related decision (eg, to refuse medical care). Competency is determined by a judge and usually refers to more global categories of decision making (eg, legally unable to make any healthcare-related decision). Components:- Decision is consistent with patient's values and goals- Patient is informed- Patient expresses a choice- Decision is not a result of altered mental status (eg, delirium, psychosis, intoxication), mood disorder- Decision remains stable over time- Patient is ≥18 years of age or otherwise legally emancipated
