Critical appraisal 4 Flashcards
What is ROC?
Receiver operator curves/ characteristic
What does a ROC show?
graphical plot of true positive rate (sensitivity) against false positive rate (specificity)
useful for describing how good a diagnostic test is
the greater the area under the curve, the better the diagnostic test is
also helps provider an suitable cut-off value for a result
What is intention to treat analysis?
Intention-to-treat analysis A method of analysis for randomized trials in which all patients randomly assigned to one of the treatments are analyzed together, regardless of whether they completed or received that treatment, to preserve randomization.
reflects real-world application of intervention
What are pros of intention to treat analysis?
reflects real-world application of intervention - so if you get a positive conclusion, this is even more significant than a comparable RCT that has drop out
simplifies outcome/ bias as no patients are excluded
preserves baseline balance between groups
preserves sample size
What are cons of intention to treat analysis?
estimate of intervention effect is conservative due to dilution of drop outs/ non-compliance
heterogeneity introduced when noncompliants, dropouts and compliant subjects are mixed together
What are these alternatives to intention to treat analysis
As treated analysis
As treated analysis -
records classifies RCT participants according to the treatment that they received rather than according to the treatment that they were assigned to
subject to confounding in the same way as an observational study
What are these alternatives to intention to treat analysis
Per protocol/ on treatment analysis
‘Per protocol/on treatment” analysis -
only includes individuals who adhered to the clinical trial instructions as specified in the study protocol
subject to selection bias due to cross-over and loss to follow up
per protocol analysis may be appropriate when analysing adverse events in drug trials, as it can be argued that side-effects of actual treatment received is clinically relevant
What are these alternatives to intention to treat analysis
Modified intention to treat
Modified intention to treat -
allows the exclusion of some randomized subjects in a justified way (e.g. patients who were deemed ineligible after randomization or certain patients who never started treatment)
definitions used are irregular and arbitrary; consistent guidelines for its application are lacking
a subjective approach in entry criteria may lead to confusion, inaccurate results and bias
What is a Type I error?
Type I error is a false positive
What is a Type II error?
Type II error is a false negative
How to calculate sensitivity?
Probability of those with the disease, who test positive
TP/ TP + FN
A sensitive test helps rule out a disease when a test is negative
How to calculate specificity?
Probability of those without the disease, who test negative
measures ability to detect absence of the condition
TN/ TN + FP
A specific test helps rule in a disease when positive
What is the PPV?
probability that the disease is present, when the test is positive
PPV = TP/ TP + FP
this is different to sensitivity, as is depedends on the population prevalence of the disease
What if NPV?
probability that the disease is absent, when the test is negative
NPV = TN/ TN + FN
this is different to specificity, as is depends on the population prevalence of the disease
What are overall differences between sensitivity/ specificity and PPV/ NPV?
Sensitivity/ specificity - characteristics of the tests themselves. High values suggest a good test. They enable you to rule conditions in or out, but cannot definitely diagnose a condition
PPV/ NPV - main use is clinical relevance of a test
PPV/ NPV depend on prevalence of the disease in population. But can tell you how the likelihood of a test diagnosing a specific disease. As prevalence decreases, the PPV decreases, as a positive is more likely a false positive. NPV increases as there will be more true negatives
Example -
Ebola test is 90% sensitive. Your patient tests positive. It would be incorrect to say this patient has a 90% chance of having Ebola. Sensitivity only helps you rule out a disease when it is negative. If your test is 90% sensitive, and is negative, you can probably exclude that disease
If Ebola test has 90% PPV, then you can say there is a 90% chance of this positive test result meaning that the patient has 90% chance of having Ebola