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    EBM Guide

    EBM Chart, MD

    Applying clinical evidence to real patients is challenging enough, and being able to accurately interpret studies is only one part of the challenge. Appraising evidence is a necessary skill that any good clinician should have. MDCalc's EBM Guide is a quick resource for statistical terms and concepts to help providers in this regard. The Glossary has definitions of useful terms and concepts. It's not meant to be comprehensive, so see also the Evidence for Practice section for links to some of our favorite EBM resources.

    Evidence based medicine [EBM] is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients.

    - Sackett 1996

    If you have feedback on the EBM Guide, please send it to us at team@mdcalc.com and we'll be happy to review.

    Glossary
    Evidence for Practice

    Our EBM Glossary includes commonly-used terms in scientific research and our calculators’ Evidence Appraisal sections. To help categorize these terms, we’ve added icons for Function to show the area of research the term is most relevant for (risk, diagnosis, treatment, prognosis, any/all) and Stage to show where along the process of evidence generation it’s generally used (study design, study question, data collection, primary data analysis, secondary data analysis).

    TERM
    FUNCTIONSTAGE
    A

    Absolute risk

    Absolute riskAbsolute risk
    Definition: Probability of an outcome.
    Example: Using the ASCVD Risk Calculator we determined that a 50 year old African-American diabetic male nonsmoker with a total cholesterol of 300 mg/dL, HDL 80md/dL, and systolic BP 120, and not on hypertension medication has an 8.6% absolute risk of a cardiovascular event in the next 10 years, meaning that out of 100 patients like him, about 9 of them will have nonfatal MI or stroke, or die from MI or stroke. According to the ASCVD study, his absolute risk could be reduced to 3.9% if his risk factors were optimized (e.g. control diabetes, start statin).

    Absolute risk reduction/increase (ARR/ARI)

    Absolute risk reduction/increase (ARR/ARI)Absolute risk reduction/increase (ARR/ARI)
    Definition: Difference in absolute risk between the control group and the tested group OR exposed and unexposed population.
    ARR/ARI = |Group A risk - Group B risk|
    Also called: absolute risk difference
    Example: Using the ASCVD Risk Calculator we determined that a 50 year old African-American diabetic male nonsmoker with a total cholesterol of 300, HDL 80, and systolic BP 120, and not on hypertension medication has an 8.6% absolute risk of a cardiovascular event in the next 10 years. According to the ASCVD study, his absolute risk could be reduced to 3.9% if his risk factors were optimized (e.g. control diabetes, start statin).
    For the patient above, by optimizing risk factors his absolute risk reduction would be 4.7%.
    Pitfall: A related but different way of quantifying risk reduction is the relative risk reduction (RRR). For this patient, the RRR would be a whopping 54.7%. Drug and device manufacturers often quote the RRR of their treatment instead of the absolute risk reduction.

    Adjustment

    AdjustmentAdjustment
    Definition: Altering the absolute risk based on additional information (i.e., history, diagnostic tests, demographic information).
    Example: Younger patients tend to have better prognosis than older patients. How much better? HCT-CI creator, Mohamed Sorror, studied the impact of age on prognosis in patients with hematologic cancers and added an adjustment of 1 point for patients 40 years or older, thus creating the age-adjusted HCT-CI.
    see also: absolute risk
    B

    Bias

    BiasBias
    Definition: Manipulation of study design or results to achieve a favored outcome. May be intentional or unintentional.

    Blinding

    BlindingBlinding
    Definition: Hiding the intervention from the patients and those interpreting the results. A study may be blind (patient doesn’t know what treatment they’re getting), double-blind (doctor and patient don’t know what treatment they’re getting), or triple-blind (statistician analyzing data doesn’t know what treatment was given).
    Also called: blind, double-blind, or triple-blind.
    Use case: Method to remove bias from a study.
    C

    Case series

    Case seriesCase series
    Definition: Study that compares a series of patients with the same diagnosis. No control group.
    Use case: Compare outcomes across patients of the same diagnosis with varying demographics and treatments. If you’re an obstetrician and you noticed that you’ve delivered several babies in a row with birth defects whose mothers took the same morning sickness medication, you might publish a case series with information about the pregnancy and the mother in order to start looking for a cause. (This is the story of thalidomide.)

    Case-control study

    Case-control studyCase-control study
    Definition: Compares a group with the disease to one without the disease.
    Use case: Evaluate the relationship between an attribute and the disease. If you were trying to figure out if cigarette smoking is associated with lung cancer, you might start by looking at patients who have lung cancer and patients who don’t have lung cancer, and note how many smokers are in each group. Spoiler alert: this has already been done multiple times since the 1940s.

    Causality

    CausalityCausality
    Definition: Attribution of causes for an effect. There are two types of causes: 1) a necessary cause must come before the effect, and 2) a sufficient cause occurs before the effect but isn’t the only required cause.
    Also called: causation

    Central tendency

    Central tendencyCentral tendency
    Definition: A measure used to describe the center of data: mean, median, and mode.

    Clinical significance

    Clinical significanceClinical significance
    Definition: A difference that is significant enough to impact patient outcomes. Statistical significance does not always imply clinical significance.
    Example: A drug that lowers hemoglobin A1c by 1% might be statistically signficant, but may not be clinically significant if it doesn’t improve outcomes like cardiovascular death, diabetic nephropathy, or diabetic retinopathy.

    Cohort study

    Cohort studyCohort study
    Definition: A study that compares a control group who didn’t receive the intervention or exposure with a group who did receive the intervention or exposure, so incidence rates can be compared. Commonly done with large groups over long periods of time.

    Confidence interval (CI)

    Confidence interval (CI)Confidence interval (CI)
    Definition: An interval within which you can be confident (usually 95% confident) that the true value lies.

    Confounding variable

    Confounding variableConfounding variable
    Definition: A variable that affects the outcome but isn’t the variable you are interested in.
    Also called: confounder

    Correlation

    CorrelationCorrelation
    Definition: The relationship between two variables.

    Cross-sectional study

    Cross-sectional studyCross-sectional study
    Definition: A study that collects data on both exposure and outcomes at a single point in time.

    Crossover study

    Crossover studyCrossover study
    Definition: A study where subjects are exposed to a sequence of two or more treatments.
    D

    Dependent variable

    Dependent variableDependent variable
    Definition: The variable that is dependent on the effect of the independent variable.

    Dose-response relationship

    Dose-response relationshipDose-response relationship
    Definition: A relationship where varying the dose alters the outcome (i.e., a bigger dose has a bigger effect than a smaller dose).
    E

    Etiology

    EtiologyEtiology
    Definition: The origin.
    see also:

    Experimental event rate (EER)

    Experimental event rate (EER)Experimental event rate (EER)
    Definition: Measure of patients in the experimental group who experience an event.
    Also called: event rate

    External validation

    External validationExternal validation
    Definition: Validation that the study’s theorized cause and effect can be applied to a broader population.
    F

    Forest plot

    Forest plotForest plot
    Definition: Graphical representation of study outcomes in a meta-analysis.
    Also called: blobbogram
    Example: forest-plot-graph

    Funnel plot

    Funnel plotFunnel plot
    Definition: Scatterplot of outcomes for individual patients compared with expected results. Used in a meta-analysis to shed light on any bias.
    G

    Gold standard

    Gold standardGold standard
    Definition: The most widely accepted standard for diagnosis, measurement or evaluation.
    Also called: reference standard and criterion standard
    see also: index test
    H

    Hawthorne effect

    Hawthorne effectHawthorne effect
    Definition: Improved outcomes caused by the patient knowing that they are being studied.
    Also called: sentinel effect
    Example: Studies related to handwashing and hygiene had to account for the Hawthorne effect, because people who knew they were being observed were more likely to be compliant.

    Heterogeneity

    HeterogeneityHeterogeneity
    Definition: The amount of variation or incompatibility in studies that are part of a systematic review.

    Histogram

    HistogramHistogram
    Definition: A graph that represents the frequency of a variable.
    Example: histogram-graph
    I

    Incidence

    IncidenceIncidence
    Definition: How many cases occur over a defined period of time.
    Pitfall: Sometimes confused with prevalence, which is the number of cases present at a single time point.

    Index test

    Index testIndex test
    Definition: The measure of a test against the current gold standard.
    see also: gold standard

    Intention to treat analysis

    Intention to treat analysisIntention to treat analysis
    Definition: Analysis of subject in the groups that they were originally assigned, even if they crossed over, dropped out or died. This is done to minimize bias.

    Internal validation

    Internal validationInternal validation
    Definition: Validation that the study’s theorized cause and effect are accurate for the study subjects. “Is my theory proven in this particular group of patients I’ve studied?”
    Pitfall: Evidence that is only internally validated should be applied with caution in clinical practice.

    Interquartile range

    Interquartile rangeInterquartile range
    Definition: The middle 50%, or the range from 25th to 75th percentile.
    Example: interquartile-reange-graph
    K

    Kaplan-Meier survival graph

    Kaplan-Meier survival graphKaplan-Meier survival graph
    Definition: A graph of chances of an outcome over time. The number of subjects without an outcome divided by the number with the outcome at various time intervals. Usually more accurate at the earlier time intervals than towards the end.
    Also called: Kaplan-Meier curve, survival curve
    Example: kaplan-meier-graph
    L

    Likelihood ratio

    Likelihood ratioLikelihood ratio
    Definition: Likelihood of a given test result in patients with a diagnosis compared to patients without the diagnosis.

    Logistic regression

    Logistic regressionLogistic regression
    Definition: A predictive graph used to identify outcomes when there are multiple independent variables.
    Example: exam-pass-logisitic-curve
    M

    Medical subject headings (MeSH)

    Medical subject headings (MeSH)Medical subject headings (MeSH)
    Definition: Glossary, often used by papers and databases to define medical terms.
    see also:

    Meta-analysis

    Meta-analysisMeta-analysis
    Definition: The statistical process of combining data from multiple independent studies focused around the same question.
    Pitfall: Often used interchangeably with systematic review (erroneously).

    Multiple linear regression

    Multiple linear regressionMultiple linear regression
    Definition: Graphical representation of an outcome based on one dependent variable and two or more independent variables.
    Example: multiple-linear-regression-chart
    N

    N-of-1 trial

    N-of-1 trialN-of-1 trial
    Definition: A study with only one patient.
    see also: study design

    Negative predictive value (NPV)

    Negative predictive value (NPV)Negative predictive value (NPV)
    Definition: The probability of a negative test result when a disease is absent (i.e., how accurate a negative result is).

    Nominal data

    Nominal dataNominal data
    Definition: Qualitative or categorical data. Cannot be put into an order.
    Example: Colors: red, green, and blue.
    see also: ordinal data

    Normal distribution

    Normal distributionNormal distribution

    Null hypothesis

    Null hypothesisNull hypothesis
    Definition: A hypothesis that there is no difference between two variables.

    Number needed to harm (NNH)

    Number needed to harm (NNH)Number needed to harm (NNH)
    Definition: The number who need to be treated in order to cause one bad outcome. It is equal to 1/ARI.

    Number needed to treat (NNT)

    Number needed to treat (NNT)Number needed to treat (NNT)
    Definition: The number of patients who need to be treated in order to cause one good outcome. It is equal to 1/ARR.
    O

    Observational study

    Observational studyObservational study
    Definition: Study that occurs without intervention by the investigator.

    Odds ratio (OR)

    Odds ratio (OR)Odds ratio (OR)
    Definition: Ratio of the measured outcome for the treated group and control group.

    One-sided (tailed) test

    One-sided (tailed) testOne-sided (tailed) test
    Definition: A test to determine the null or alternative hypothesis. If the outcomes fall to one side of the normal distribution then the alternative hypothesis is accepted.

    Ordinal data

    Ordinal dataOrdinal data
    Definition: Data that can be ordered but also has a qualitative category.
    Example: Temperature: cold, colder, coldest
    see also: nominal data

    Outcomes study

    Outcomes studyOutcomes study
    P

    P value

    P valueP value
    Definition: The probability that an outcome is caused by chance.

    Patient expected event rate (PEER)

    Patient expected event rate (PEER)Patient expected event rate (PEER)
    Definition: The expected rate for an outcome in an individual who receives the standard or no treatment.
    Also called: expected event rate (EER)

    Patient-oriented evidence (POE)

    Patient-oriented evidence (POE)Patient-oriented evidence (POE)
    Definition: Evidence that pertains to areas that patients care about (e.g. symptoms, quality of life, mortality, etc), as opposed to clinical benchmarks like percent reduction of HgbA1c or decrease in systolic blood pressure points.

    Permuted block randomization

    Permuted block randomizationPermuted block randomization
    Definition: Strategy for further randomization. Patients are assigned to different treatment options for a block of time and then a different treatment option for the next block of time.

    Positive predictive value (PPV)

    Positive predictive value (PPV)Positive predictive value (PPV)
    Definition: The probability of a positive test result when a disease is present (how accurate a positive test result is).

    Post-marketing surveillance

    Post-marketing surveillancePost-marketing surveillance
    Definition: A process for evaluating outcomes and side effects for a medication after it is available to the public.
    see also:

    Post-test probability

    Post-test probabilityPost-test probability
    Definition: How likely it is that a patient has an outcome (after being tested).

    Power

    PowerPower
    Definition: The ability of a study to measure any statistically significant difference (if any exists).

    Pre-test probability

    Pre-test probabilityPre-test probability
    Definition: How likely it is that a patient has an outcome (before being tested). Often synonymous with prevalence.

    Prevalence

    PrevalencePrevalence
    Definition: How many cases are present at a single time point.
    Pitfall: Sometimes confused with incidence, which is the number of cases that occur over a defined period of time.
    see also: incidence

    Primary research

    Primary researchPrimary research

    Prospective study

    Prospective studyProspective study

    Publication bias

    Publication biasPublication bias
    Definition: The decision to publish (or not) based on the outcomes of the study.
    R

    Randomized controlled trial

    Randomized controlled trialRandomized controlled trial
    Definition: A trial where patients are randomly assigned to either the treatment or control group.

    Receiver operating characteristic (ROC) curve

    Receiver operating characteristic (ROC) curveReceiver operating characteristic (ROC) curve
    Definition: A graph of sensitivity vs (1 - specificity). Used to determine cutoff points and evaluate the quality of a study. An area under the ROC (AUROC) of 0.8 is generally considered good.

    Regression

    RegressionRegression

    Regression line

    Regression lineRegression line

    Relative risk (RR)

    Relative risk (RR)Relative risk (RR)
    Definition: Probability that an event will occur in the exposed group divided by probability it will occur in the unexposed group.
    Also called: risk ratio

    Relative risk reduction (RRR)

    Relative risk reduction (RRR)Relative risk reduction (RRR)
    Definition: Relative change in risk between the control and treatment groups.
    RRR = (Group A risk - Group B risk)/Group A risk x 100%

    Retrospective study

    Retrospective studyRetrospective study
    Definition: A study that is based on outcomes that have already occurred.

    Risk ratio

    Risk ratioRisk ratio
    Definition: Ratio for risk between the treated and control groups.
    S

    Sample size

    Sample sizeSample size
    Definition: The size of the sample or study participants. In general, a bigger sample size is better.

    Sampling bias

    Sampling biasSampling bias
    Definition: Bias introduced when sampling.

    Secondary research

    Secondary researchSecondary research
    Definition: A synthesis of single/indvidual studies (primary research), such as a systematic review.

    Selection bias

    Selection biasSelection bias
    Definition: Bias that occurs when choosing individuals for a study.

    Sensitivity

    SensitivitySensitivity
    Definition: The probability of a positive test result when a disease is present.

    SnNout

    SnNoutSnNout
    Definition: When the sensitivity of a tool is good enough to rule out a disease based on a negative result.

    SpPin

    SpPinSpPin
    Definition: When the specificity of a tool is good enough to rule in a disease based on a positive result.

    Specificity

    SpecificitySpecificity
    Definition: The probability of a negative test result when a disease is absent.

    Standard deviation

    Standard deviationStandard deviation
    Definition: The amount of variation in data points for a group. The implication of a high standard deviation (i.e., lots of variation in data) is that the data are less reliable.
    Calculated by 1) finding the deviation for each value (subtract each data point from the average and square it), 2) finding the average variance (find the average deviation), and 3) taking the square root of the variance.
    Example: standard-deviation-image

    Standard error of estimate

    Standard error of estimateStandard error of estimate
    Definition: The measurement of the accuracy of predictions that are made using a regression line.

    Statistical significance

    Statistical significanceStatistical significance
    Definition: The measure of confidence that an intervention was the cause for an altered outcome. A statistically significant result is one that you are fairly sure, according to your analysis, happened because of your intervention, and not by chance.

    Statistical validity

    Statistical validityStatistical validity
    Definition: How accurately an instrument measures data.

    Stepwise regression

    Stepwise regressionStepwise regression
    Definition: A technique that uses regression lines to find variables or subsets of variables that most accurately predict an outcome.

    Strength of inference

    Strength of inferenceStrength of inference
    Definition: The probability that a difference in outcome between treatment and control groups can be attributed to the treatment.

    Study design

    Study designStudy design

    Study validity

    Study validityStudy validity
    Definition: How accurately a study measures an outcome.

    Surrogate outcome/endpoint

    Surrogate outcome/endpointSurrogate outcome/endpoint
    Definition: Measures an endpoint in place of measuring the clinical benefit when it is not possible to measure benefit.
    Pitfall: Surrogate outcomes are sometimes used to act upon data, perhaps prematurely.

    Systematic review

    Systematic reviewSystematic review
    Definition: A review of the literature around a specific research question. Similar, but not equivalent, to a meta-analysis, which refers to the process of combining data (i.e., a systematic review may include a meta-analysis, but not every meta-analysis is necessarily part of a systematic review).
    Pitfall: Often used interchangeably with meta analysis (erroneously).
    T

    True negative

    True negativeTrue negative
    Definition: When a negative test indicates absence of a disease.

    True positive

    True positiveTrue positive
    Definition: When a positive test indicates the presence of a disease.

    Two-sided (tailed) test

    Two-sided (tailed) testTwo-sided (tailed) test
    Definition: A test used when the alternative hypothesis is nondirectional (could fall on the negative or positive side of the null hypothesis).

    Type I error

    Type I errorType I error
    Definition: An error made by accepting the alternate hypothesis when it is actually incorrect, e.g. imprisoning an innocent person.

    Type II error

    Type II errorType II error
    Definition: An error made by accepting the null hypothesis when it is actually incorrect, e.g. letting a guilty person go free.
    V

    Verification bias

    Verification biasVerification bias
    Definition: When patients that have a negative test result are not measured using the gold standard.