**Clinical Epidemiology Definitions **

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**Absolute risk**: The observed or calculated probability of an event in the population
under study.

**Absolute risk difference**: the difference in the risk for disease or death between an exposed population and an unexposed population.**Absolute risk reduction**(ARR): the difference in the rates of adverse events between study and control populations (ie: the difference in risk between the control group and the treated group: ARR=CER-EER)

**Adjustment**: A summarizing procedure for a statistical measure in which the
effects of differences in composition of the populations being compared have been
minimized by statistical methods.

**Association**: Statistical dependence between two or more events, characteristics,
or other variables. An association may be fortuitous or may be produced by various other
circumstances; the presence of an association does not necessarily imply a causal
relationship.

**Bias** (Syn: systematic error): Deviation of results or
inferences from the truth, or processes leading to such deviation. See also Referral
Bias, Selection Bias.

**Blind(ed) study** (Syn: masked study): A study in which
observer(s) and/or subjects are kept ignorant of the group to which the subjects are
assigned, as in an experimental study, or of the population from which the subjects come,
as in a nonexperimental or observational study. Where both observer and subjects are kept
ignorant, the study is termed a **double-blind** study. If the statistical analysis is
also done in ignorance of the group to which subjects belong, the study is sometimes
described as **triple blind**. The purpose of "blinding" is to eliminate
sources of bias.

**Case-series**: Report of a number of cases of disease.

**Case-control study**: Retrospective comparison of exposures of
persons with disease (cases) with those of persons without the disease (controls) (see Retrospective study).

**Causality**: The relating of causes to the effects they produce. Most of
epidemiology concerns causality and several types of causes can be distinguished. It must
be emphasized, however, that epidemiological evidence by itself is insufficient to
establish causality, although it can provide powerful circumstantial evidence.

**Co-interventions**: Interventions other than the treatment
under study that are applied differently to the treatment and control groups.
Cointervention is a serious problem when double blinding is absent or
when the use of very effective non-study treatments is permitted.

**Cohort study**: Follow-up of exposed and non-exposed defined
groups, with a comparison of disease rates during the time covered.

**Comparison group**: Any group to which the index group is compared. Usually
synonymous with control group.

**Co-morbidity**: Coexistence of a disease or diseases in a
study participant in addition to the index condition that is the subject of study.

**Confidence interval** (CI): The range of numerical values in
which we can be confident (to a computed probability, such as 90 or 95%) that the
population value being estimated will be found. Confidence intervals indicate the strength
of evidence; where confidence intervals are wide, they indicate less precise estimates of
effect. See Precision

**Confounding variable, Confounder**: A variable that can cause or
prevent the outcome of interest, is not an intermediate variable, and is associated with
the factor under investigation. A confounding variable may be due chance or bias. Unless it is possible to adjust for confounding variables, their
effects cannot be distinguished from those of factor(s) being studied.

**Dose-response relationship**: A relationship in which change in
amount, intensity, or duration of exposure is associated with a change-either an increase
or decrease-in risk of a specified outcome.

**Determinant**: Any definable factor that effects a change in a health condition or
other characteristic.

**Effectiveness**: a measure of the benefit resulting from an intervention for a
given health problem under usual conditions of clinical care for a particular group; this
form of evaluation considers both the efficacy of an intervention and
its acceptance by those to whom it is offered, answering the question, "Does the
practice do more good than harm to people to whom it is offered?" See Intention
to treat.

**Efficacy**: a measure of the benefit resulting from an
intervention for a given health problem under the ideal conditions of an investigation; it
answers the question, "Does the practice do more good than harm to people who fully
comply with the recommendations?"

**Exclusion Criteria**: Conditions which preclude entrance of candidates into an
investigation even if they meet the inclusion criteria.

**Follow-up**: Observation over a period of time of an individual,
group, or initially defined population whose relevant characteristics have been assessed
in order to observe changes in health status or health-related variables.

**Gold standard**: A method, procedure, or measurement that is widely accepted as
being the best available.

**Incidence**: The number of new cases of illness commencing, or of persons falling
ill, during a specified time period in a given population. See also Prevalence.

**Intention to treat analysis**: A method for data analysis in a randomized clinical trial in which individual outcomes are analyzed
according to the group to which they have been randomized, even if they never received the
treatment they were assigned. By simulating practical experience it provides a better
measure of effectiveness. (versus efficacy**)**

**Interviewer bias**: Systematic error due to interviewer's
subconscious or conscious gathering of selective data.

**Lead-time bias**: If prognosis study patients are not all enrolled at similar,
well-defined points in the course of their disease, differences in outcome over time may
merely reflect differences in duration of illness.

**Likelihood ratio**: Ratio of the probability that a given
diagnostic test result will be expected for a patient with the target disorder rather than
for a patient without the disorder.

**Number Needed to Treat** (NNT): the number of patients who must
be exposed to an intervention before the clinical outcome of interest occurred; for
example, the number of patients needed to treat to prevent one adverse outcome. Equal to
the inverse of the absolute risk reduction: NNT=1/ARR = 1/CER-EER.

**Odds**: a proportion in which the numerator contains the number
of times an event occurs and the denominator includes the number of times the event does
not occur.

**Odds Ratio** (Syn: cross-product ratio, relative odds): a
measure of the degree of association; for example, the odds of exposure among the cases
compared with the odds of exposure among the controls.

**Precision**: The range in which the best estimates of a
true value approximate the true value. See Confidence interval.

**Predictive value**: In screening and diagnostic tests, the probability that a
person with a positive test is a true positive (i.e., does have the disease), or that a
person with a negative test truly does not have the disease. The predictive value of a
screening test is determined by the sensitivity and specificity
of the test, and by the prevalence of the condition for which the test is used.

**Prevalence**: the proportion of persons with a particular
disease within a given population at a given time.

**Prognosis**: the possible outcomes of a disease or condition and the likelihood
that each one will occur.

**Prognostic factor**: Demographic, disease-specific, or
co-morbid characteristics associated strongly enough with a condition's outcomes to
predict accurately the eventual development of those outcomes. Compare with risk factors. Neither prognostic or risk factors necessarily imply a
cause and effect relationship.

**Prospective study**: Study design where one or more groups (cohorts) of
individuals who have not yet had the outcome event in question are monitored for the
number of such events which occur over time.

**Randomized controlled trial**: Study design where treatments,
interventions, or enrollment into different study groups are assigned by random allocation
rather than by conscious decisions of clinicians or patients. If the sample size is large
enough, this study design avoids problems of bias and confounding
variables by assuring that both known and unknown determinants of outcome are evenly
distributed between treatment and control groups.

**Recall bias**: Systematic error due to the differences in
accuracy or completeness of recall to memory of past events or experiences.

**Referral filter bias**: The sequence of referrals that may lead
patients from primary to tertiary centres raises the proportion of more severe or unusual
cases, thus increasing the likelihood of adverse or unfavorable outcomes.

**Relative risk** (RR, or risk ratio): the ratio of the
probability of developing, in a specified period of time, an outcome among those receiving
the treatment of interest or exposed to a risk factor, compared with the probability of
developing the outcome if the risk factor or intervention is not present (ie., the ratio
of risk in the treated group to the risk in the control group: RR=EER/CER)

**Relative risk reduction** (RRR): the extent to which a treatment
reduces a risk, in comparison with patients not receiving the treatment of interest (ie.,
the percent reduction in events in treated compared to controls: RRR=[(CER-EER)/CER]).

**Reproducibility** (Repeatability, Reliability): the results of
a test or measure are identical or closely similar each time it is conducted.

**Retrospective study**: study design in which cases where
individuals who had an outcome event in question are collected and analyzed after the
outcomes have occurred (see also Case-control study).

**Risk factor**: patient characteristics or factors associated
with an increased probability of developing a condition or disease in the first place.
Compare with prognostic factors**.** Neither risk or prognostic factors necessarily imply a cause and effect relationship.

**Selection Bias**: a bias in assignment or a confounding
variable that arises from study design rather than by chance. These can occur when the
study and control groups are chosen so that they differ from each other by one or more
factors that may affect the outcome of the study.

**Sensitivity **(of a diagnostic test): the proportion of truly
diseased persons, as measured by the gold standard, who are identified as diseased by the
test under study.

**Specificity** (of a diagnostic test): the proportion of truly
nondiseased persons, as measured by the gold standard, who are so identified by the
diagnostic test under study.

**Stratification**: division into groups. Stratification may also refer to a process
to control for differences in confounding variables, by making separate
estimates for groups of individuals who have the same values for the confounding variable.

**Strength of Inference**: the likelihood that an observed difference between groups
within a study represents a real difference rather than mere chance or the influence of confounding factors, based on both p values and confidence
intervals. Strength of inference is weakened by various forms of bias
and by small sample sizes.* *

**Survival curve**: A graph of the number of events occurring over
time or the chance of being free of these events over time. The events must be discrete
and the time at which they occur must be precisely known. In most clinical situations, the
chance of an outcome changes with time. In most survival curves the earlier follow-up
periods usually include results from more patients than the later periods and are
therefore more precise.* *

**Validity**: the extent to which a variable or intervention
measures what it is supposed to measure or accomplishes what it is supposed to accomplish.

- The
**internal validity**of a study refers to the integrity of the experimental design. - The
**external validity**of a study refers to the appropriateness by which its results can be applied to non-study patients or populations.