CVB MDM Flashcards
What is a derivation study, as it relates to a clinical prediction rule?
Usually a retrospective study
Used to develop a clinical prediction rule. Must be validated by another study
What is specificity?
How do you calculate specificity?
Given the absence of disease, the probability that a test will be negative
Specificity = TN / (FP+TN)
What is sensitivity?
How do you calculate sensitivity?
Given the presence of disease, the probability that a test will be positive
Sensitivity = TP / (TP+FN)
What is length time bias?
How can it be eliminated?
Length time bias occurs when screening measures uncover less aggressive/less severe forms of disease, such as tumors with a better prognosis. The misconception that arises is that catching the tumor early leads to better prognosis, when in reality these tumors had a better prognosis to begin with
This occurs because more severe tumors are likely to progress and present as disease before they have a chance to be caught with screening
To eliminate: Study the screening test using an RCT with intention to treat analysis
How can you convert probability into odds?
Odds = probability / (1 – probability)
What is a training set, as it referes to clinical prediction rules?
The data used to develop a prediction rule in a derivation study
(usually retrospective)
What is the formula for LR+?
LR+ = sensitivity / (1 - specificity)
What is the best negative LR?
0
If a test is perfect, a negative result = 0% likelihood that you have disease
What is lead time bias?
How can it be eliminated?
Lead time bias occurs when the time between disease diagnosis and death is increased only because screening caught the disease early, and not because screening helped to initiate treatment that prolonged life.
In other words, when screening offers no benefit in terms of prognosis/treatment: it only tells people they have the disease earlier.
To eliminate: compare age specific mortality instead of survival
What is secondary prevention?
Give some examples
Secondary prevention detects and treats disease early in the disease process, while it is still asymptomatic and “treatable”
Involves screening and follow-up diagnosis + treatment
- HIV testing
- PAP smears
What is the relationship between negative post-test probability and negative predictive value?
Negative post-test probability = 1 – negative predictive value
Negative predictive value = 1 - Negative post-test probability
(use bottom row)
Is sensitivity used to rule a disease in or out?
SNOUT - sensitivity, rules a disease out
What kind of prevention does surveillance fall under?
Tertiatry prevention
What is chemoprevention?
Give some examples
The use of drugs to prevent disease
Examples:
- Folate during pregnancy to prevent neural tube defect
- Antibiotic prophylaxis
- Aspirin to prevent clotting
- Statins
What is the relationship between positive predictive value and positive post-test probability?
Positive predictive value = positive post-test probability = TP / (TP+FP)
(use top row)
What is tertiatry prevention?
Give some examples
Tertiary prevention prevents the deterioration/progression of the disease. The goal is to reduce complications of the disease, given that it is already present
Basically, long term treatment. Surveillane is necessary
- Beta blocers to reduce death in patients with past myocardial infarction
- Insulin/blood glucose control in diabetics
To determine whether a screening test is effective in altering disease progression, why would you analyze age-specific mortality (as opposed to survival rates?)
Analyzing age-specific mortality eliminates lead-time bias
It can also help to control for length-time bias
What is primary prevention?
Give some examples
Primary prevention prevents disease from occuring by removing the cause of disease
May be carried out in community or clinical settings
- Immunizations
- Behavioral counseling
- Prophylactic surgery
- Seatbelt campaigns
What is compliance bias?
How can it be eliminated?
Compliance bias occurs when patients who are more compliant with treatment have a beter prognosis for reasons other than their compliance with the treatment
For example, patients who comply with treatment are more likley have better baseline health or more investment in healthy lifestyle in general
Eliminate by studying the treatmeng with a RCT with intention to treat analysis
What is the formula for negative post-test probability?
Negative post-test probability = FN / (TN+FN)
What is the formula for LR-?
LR- = (1 - sensitivity) / specificity
What is a completely unhelpful LR?
1
With a + or - result, you are equally likely to have the disease
What must be true of a disease for screening to be beneficial?
The disease that is screened for should have…
- A significant burden of suffering
- A latent period where the disease is present but not yet clinically significant
- An intervention that would improve outcomes if the disease is found early
- A good screening tool
What is the relationship between pre-test odds, LR, and post-test odds?
Pre-test odds x LR = Post-test Odds
Is specificity used to rule a disease in or out?
SPIN - specificity, rules a disease in
What is the formula for positive post-test probability?
Positive post-test probability = TP / (TP+FP)
OR
Pre-test odds x LR = Post-test odds, and then convert post-test odds to probability
What is the best positive LR?
Infinity
In a perfect test, a positive result means that you always have the disease
If a test has a high LR+, like 100, then a positive result means you are 100x more likely to have the disease
Describe a validation study, as it relates to a clinical prediction rule
Usually prospective studies in a clinical setting with close follow-up and a broad-spectrum definition of disease
Must use a patient population different from the derivation study
What is a test set, as it referes to clinical prediction rules?
The data used to validate a clinical prediction role in a validation study
Must use a population different than the derivation study
(Usually prospective studies in a clinical setting with close follow-up and a broad-spectrum definition of disease)
How can you convert odds into probability?
Probability = odds / (1 + odds)
How does sensitivity relate to the true positive rate of a clinical prediction rule?
Sensitivity = True positive rate
How does specificity relate to the false positive rate of a clinical prediction rule?
Specificity = 1 - false positive rate
