Appraising Dx Research studies Flashcards
Variables are categorical with no order and example
Nominal
Gender
Variables are in ordered Category and example
Ordinal
MMT
Variables are ordered precisely and continously
Has true 0
example?
Ratio
Muscle strength test
Variables are ordered precisely and continously has no true 0
Example
Interval
Temperature
Dx study includes
Pt. History
Systems review
Informed use of test and measures
Distinguish between people who have movement disorder and those who dont
Dx test.
Range of scores that captures individuals w/o mvt disorders
Reference interval
Individuals with mvt disorder fall where in reference interval
Outside
Most comon design for development of Dx test
Cohort
▪ Forward planning to collect data on both the clinical test (index test) under study and a gold standard comparison test
Prospective study
Looks back at previously collected findings and examines exposures to suspected risk or protection factors in relation to an outcome that is established at the start of the study
Retrospective
Which study has possible risk for bias
Retrospective
Masked application of both tests means that you require
At least 2 examiners completing only 1 of the tests
Pt definitely has condition
True +
Pt def doesnt have condition
True -
Doesnt have condition with gold standard, but + with clinical test
False +
Test positive on gold standard
Negative on clinical test
False -
Tests accuracy in correctly identifying presence of problem
Sensitivity
True positive rate ratio
Sensitivity
A/a+c
False negative rate
1-sensitivity
Tests ability to correctly identify absence of problem
Specificity
True negative Rate
Specificity
D/b+d
False positive rater
1- specificity
SpPin
High specificity, + test rules in Dx
SnNout
High sensitivity, - result rules out Dx
Plot of specificity and sensitivity values generated from a series of cutpoints in Dx test
Receiver operating Characteristic ROC curve
Used to determine optimal cutoff threshold in Dx test
ROC curve
Represent trade off b/w TPR and FPR
ROC curve
Likelihood a person testing positive actually has disease
Positive predictive value
PPV equation
A/a+b
Likelihood person testing negative is disease-free
Negative predictive Value
NPV equation
D/d+c
The probability of the target disorder before a diagnostic test result is known (i.e. the prevalence of a disease).
Pre-test Probability
When pre-test probability is VERY low
Disease is unlikely and test not needed
o When pre-test probability is VERY high,
Disease is likely and test may not be needed
Pre-test probability in midrange
May be worth pursuing
probability of a disease based on the outcome of a test.
Post-test probability
High Post test probability
Low?
Midrange??
Confirms Dx
Rule out Dx
More testing needed
Aids in determining post test probability
Likelihood ratios
how much more likely a positive test will be seen in someone with the disorder than someone without the disorder
LR+
LR+ equation
Sensitivity/1-specificity
Large LR+ rules a disease
IN
how much more likely a negative test will be seen in those with the disorder than in those without the disorder
Negative Likelihood ratio LR-
LR- equation
1-sensitivity/specificity
Low LR- rules disease
OUT
plot of both pre-test positive and negative likelihood ratios to visualize and quantify post-test probabilities
nomogram
Large LR+
Mod
Small
Negligible
> 10
5-10
2-5
<2
Large LR-
Mod
Small
Negligible
