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113 Cards in this Set
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epidemiology
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The study of the incidence, distribution, and determinants of health states in specified populations
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clinical epidemiology
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the application of the principles and methods of epidemiology to problems encountered in clinical medicine
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Evidence-based health care
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using the health care literature as the basis for clinical decisions in conjunction with experience, a strong education, and consideration of the patient's unique situation
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experimental
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intervention controlled by researcher
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Hierarchy of Evidence
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n of 1 trials
systematic review of RCTs Single RCT Sys. Rev. Observational studies Single Observational study Physiological/lab study Unsystematic clinical observation |
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Determining Causation
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-evidence from hierarchy
-strength of assocation -consistency of literature -temporal sequence (prospective?) -dose-response gradient -sense/plausibility |
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Internal Validity
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the ability of the study results to support a cause-effect relationship between the treatment and the observed outcome
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External Validity
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The generalizability of the results to patients outside the study
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Explanatory Study
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-strict eligibility criteria; high-risk patients
-not ITT analysis -experts give intervention -high freq. followup -follow-up stops with patient compliance -patient compliance closely monitored, strategies in place to enhance compliance -clinician compliance closely monitored with feedback -events are things researchers value |
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Pragmatic Study
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-all comers included
-ITT analysis -intervention like routine care -follow up intensity as usual care -followup until death or end of trial -patient compliance monitored without strategies -clinician compliance not really monitored -all events included in analysis |
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International Classification of functioning, disability and health
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health outcomes classified according to the effect on body function and structure (impairment), limitations in activities (disability), and participation (handicap)
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-Body function: physical
-Body structures: anatomical -Activity: performance of a task -Participation: meaningful role |
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Health-related QOL
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attempts to measure the broad concept of health
generic (general health) disease-specific (indicators relevant to a sub-population) region-specific: related to one anatomical area of the body |
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Utility measure
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the value people place on health benefits and avoiding poor outcomes
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Standard Gamble
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point of indecision between sure thing and gamble
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Validity
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The extent to which an instrument measures what it is intended to measure
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reliability
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the extent to which an instrument will give the same results in repeated administrations to a stable population
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sensitivity to change
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the ability of a measure to measure change
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responsiveness
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the ability to measure clinically meaningful change
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Criterion Validity
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the correlation of a scale with some other measure of the same thing (gold standard)
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Example: the correlation between diagnostic test Q and an MRI
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Construct Validity
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-how a measure preforms compared to different and similar measures
-testing of hypotheses |
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Content Validity
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is the measure representative of all content domains of the construct?
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Reliability
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a ratio between the true score and the true score + error (signal over noise)
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Mean difference
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= Mean (t1) - Mean (t2)
PRO: An indication of whether there is a systematic difference between groups CON: indication of agreement at group level, not ind. level |
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Standard error of measurement
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An est. of the measure's ability to differentiate among patients
Can be used to determine if a true change has occurred within an individual using the MDC |
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Minimally detectable Change (MDC)
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= (SEM x z) x root 2
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Kappa
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For a dichotomous variable
Picks up systematic differences 1 = no systematic difference |
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Weighted Kappa
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Ordered variable
Picks up systematic differences 1 = no systematic difference |
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ICC
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Continuous Variable
Picks up Systematic differences 1 = no systematic difference |
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Pearson's r/Spearman's r
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doesn't pick up systematic bias
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Standardized Response Mean
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used in a population expected to change; test given before and after change
= mean change/SD change >1 is good |
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Global Rating of Change
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Patient asked to indicate how much they changed
- average score of patients who indicated slight change |
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Minimally important difference (MID)
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the smallest difference in score that informed patients perceive as important; that would lead patients or clinicians to consider a change in mgmt
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Effect Size
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= mean(c) - mean(t)/sqrt(SD(c)^2) + (SD(t)^2)
0.2 small 0.5 mod 0.8 large |
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Number need to treat
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= 1/ARR
how many patients need to be treated for 1 person to experience important change |
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Surrogate endpoints
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outcome that is not important in and of itself, but reflects or predicts important outcome
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Composite Endpoint
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An endpoint that clusters several outcomes together
- increases number of events - may be carried by one outcome - all outcomes may not be equally important |
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Confounding Bias
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systematic error in the measurement of tx effect caused by its association with another causal factor
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Randomization
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allocating patients to groups in an unpredictable to reduce biases
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Blocking
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ensures equal numbers of patients in each group at any time during the trial
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Stratification
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ensures balance in prognostic factors between groups
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Allocation concealment
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protects allocation sequence before and up until patients are put in their group; CAN ALWAYS BE DONE!
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Balance of prognostic factors
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Table 1
should happen if randomization done properly |
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Blinding
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Protects allocation sequence after the allocation; not always possible
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Interviewer bias
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systematic error due to selective data gathering
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placebo effect
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an effect of treatment attributable to the expectation that the treatment will have an effect
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Bias of interpretation
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failure to consider every possible interpretation of results because of personal investment/bias
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Intention to treat analysis
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patients are analyzed within their allocated groups no matter what
-minimizes type 1 error - preserves prognostic balance - greater accountability for all patients - greater generalizability |
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Completeness of Follow up
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who is missing and why?
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Imputation methods
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Ways to deal with missing data statistically
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Measures of central tendency
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mean, median, mode
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Measures of dispersion
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SD, SE, variance, range
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incidence
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proportion of NEW events
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prevalence
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proportion of events
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absolute risk (AR)
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event rate in control group
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Absolute risk reduction (ARR)
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the arithmetic difference in risk between 2 groups
= AR(t) - AR(c) |
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Relative Risk (RR)
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the proportion of the original risk that is left after therapy
= AR(t)/AR(c) |
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Relative Risk Reduction
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the proportion of original risk that is removed by therapy
= ARR/AR(c) or = 1-RR |
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Odds Ratio (OR)
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= odds in experiment/odds in control
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Hazard Ration (HR)
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= # of events/total observation time
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alpha
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chance of a false positive result (research says there is a difference when truth is that there is no difference)
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beta
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chance of a false negative (research says there is no difference when really there is)
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Confidence interval
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the interval with a given probability that the true value of the estimate of the Tx Effect is contained within that interval
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Equality Study
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Research Question: Is there a difference between Tx and Control?
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Superiority Study
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Research Question: Is a new treatment BETTER than control?
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Non-inferiority Study
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Research Question: Is a new treatment NO WORSE than control?
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Equivalence Study
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Research Question: Is a new treatment NO BETTER OR NO WORSE then control? (parameters defined)
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Co-intervention
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application of additional therapies to patients in either group
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Contamination
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application of tx to control group or no tx to tx group
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carry-over effects
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change in txA vs TxB
change in CtA vs CtB Did effects from treatment carryover? |
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Order Effects
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(change in TxA-CtA) - (change in TxB-CtB) = 0
Does it matter which order the patients had the Tx? |
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Patients are selected based on their treatment, free of outcome of interest and incidence of events are recorded
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Prospective Cohort
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Patients selected based on their treatment and outcomes of interest are recorded retrospectively
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Retrospective Cohort
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Patients are selected based on outcome and then we look at which treatment they received; always retrospective
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Case-control study
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An inception cohort is selected
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Prognosis
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A disease-free population is selected; no control group; events are recorded as time goes on
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Risk
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Pre-test probability
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the initial chance that a patient has a specific disease: decided by clinician
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Diagnostic uncertainty
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between the treatment and test thresholds; require further testing to make diagnostic certainty
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select a representative sample of patients whose diagnosis is uncertain for a particular condition
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Diagnostic Test
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Receiver Operating Characteristic Curve
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Shows the usefulness of a diagnostic test
x = 1-specificity y = sensitivity |
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Sensitivity
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the proportion of patients with the target disorder who have a positive test result
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Specificity
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the proportion of patients without the target disorder who have a negative test result
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SnNout
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if the test has a high sensitivity, a negative test rules the disorder out
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SpPin
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if the test has a high specificity, a positive test rules the disorder in
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positive predictive value
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the proportion of patients with a positive test who have the disorder
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negative predictive value
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the proportion of patients with a negative test who do not have the disorder
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likelihood ratio
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the odds that a given level of diagnostic test would be expected in a patient with the disorder
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+ LR
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= Sensitivity/1-specificity
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- LR
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= 1-specificity/senstivity
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odds converted to probability
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=odds/odds + 1
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probability converted to odds
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= p/1-p
ex: 60% =60:40 =60/40 |
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critical point
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the point at which early diagnosis is possible and it is not too late to impact the outcome
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Lead time bias
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looks like screening prolongs life because you start counting earlier
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volunteer bias
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volunteers are generally healthier because they are proactive about their health
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the application of scientific strategies to limit bias in the gathering, critical appraisal, and synthesis of studies on a specific topic
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systematic review
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meta-analysis
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statistical analysis of the results from independent studies to produce a single est of tx effect
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Forest Plot
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Graphical representation of tx effects from each study in a systematic review + total effect estimate
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Formulate the research question
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a priori
picot |
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Formulate the search strategy
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define criteria explicitly
- type of study - population - intervention - outcome - length of FU - features that define methodological quality |
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Comprehensive search strategy
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consider several sources
reproducible |
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publication bias
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positive studies more likely to be published than negative trials
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timelag bias
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positive studies published faster than negative studies
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language bias
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English studies published more often than other languages
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multiple publication bias
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positive studies more likely to be published more than once
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citation bias
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positive studies more likely to be cited by others
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Funnel plot
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graphical representation of publication bias
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Quality Scales
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attempt to make it easy to assess quality, but there is much variation
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I squared
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measure of heterogeneity across studies in a systematic review
low 25% mod 50% high 75% |
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Sources of heterogeneity
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clinical elements or methodological elements that vary between studies
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Random effects
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accounts for differences in samples across studies
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Fixed effects
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assumes that all samples are drawn from the same popluation
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Weighted mean difference
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appropriate summary measure for studies that report the same outcome measure
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Standardized mean difference
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appropriate summary measure for studies that report difference outcome measures (OR, RR, etc.); makes them comparable
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Sensitivity Analyses
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explains differences due to heterogeneity between studies
- a priori hypotheses tested |
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