High Yield Concepts in General Pathology

High Yield Concepts in General Pathology

General Principles of Lab Medicine

Sensitivity of a tcst: "posith;iry ill disease"-

A. TP = pa.t.ienl with the disease

n. FN = palien( with disease who has a negative tesl result

C. fOflllUt:1 for sensitivity- TP I TP + FN

usc of a test " ... ith J 00 % sensith-ii)'-

best used 10 screen for disease

excludes disease when negative

includes people \.vith disease when positive '

catch words: excludes and includes

interpretation of a test with J 00% sensirivity when it returns nor11lal in a paticllt-

always has a ne!..!ative orediclive value of '100% (PY- = TN / TN + FN)

it mUSt be a TN lest re-sult (excludes disease) since there are no J-Ns: a TN is a true

negative or a nomlai [cst result in a person wilhout disease

e.g .. )ci'um ANA has 100% sensitivity for SLE: a negative serum ANA excludes SLE, interpretation of a test with 100% sensitivity wheu it returns positive i 11 a patient-

may be a TP or FP:

(I) FP = false positive or a positive test result in a nomlaJ person

(2) note that FPs are not in the fom1ula for sensitivit)l

people with the disease are a!wavs included

c.g., a positive senlm AKA result includes all ~le with SLE: it does nOT confirm SLE sinct! other diseases also have a positive ANA (e.g., rheumatoid a.rthritis. progressive

2.

4.

B. c.

systemic sclerosis)

Disease ;'\rIo D~ease

Positive test (TP) 100 (FP) 10

Negative test (FN) 0 (Ti\) 90

Calculate sensiriviry or the test: TP J TP + FN = 100 I 100 - 0 == 1000,,"i1 Calculate PY-: TN 1 TN + fN = 90 190 + 0 = 100%

"'"

Specificity or a rest:

"negativity in health"-

TN == normal test result in a person wilhom disease

FP = patient vv'ilholl! diseuse who has a positive test result

C. formula for specificity- TN / TN + FP

use of a test witb 100% specificity- confinns disease: there are no FP test results, therefore. a positive test must be a TP

interpretation of a test with 100% specificity when it returns positive in a patient-

confinns disease in that patient

positive predictive value is always ~:oO% (PV' ~ TP / TP + FP)

must be a TP (confirms disease) since there are no FPs

e.g., anti-Sm for SLE has 100% specificity (110 FPs): glLpatients with a posiLive anti-Sm have SLE

interpretation of a test with 100% specificity when it returns negative/normal In a patient-

may be a TN or FN: note that the FN rate is not in the formula for speci.ficity

it does not exclude SLE

e.g., anti-Sm is negative in a patient: ( I) does not exclude SLE

(2) use other tests to confirm SLE if your suspicions are high

Disease

No Disease

Positive test (TP) 90

(FP) 0

Negative test (FN) 10

(TN) 100

Calculate specificity of tl,e test: TN / TN + FP ~ 100 / 100 + 0 ~ 100% Calculate P: TP / TP + FP ~ 90 /90 + 0 ~ 100%

CalcuJate the reference interval of the t.est when given the mean of the test and 1 SD (standard deviation):

remember to double the SD- 2 SD covers 95% of the normal population

example- .

meanofthetest~IOOmzldLand I SD~5mgldL(2SD~IOmgldL)

reference interval ~ 90-110 mgldL (l 00 - 10 ~ 90 and 100 + I 0 ~ 110)

for each test, 5% of normal people wilt have test results outside the reference intenal-

chance of a FP increases when more than one test is ordered on a patient

example. 2 tests on a patient increases the chance of a FP test result on one of those tests ro-lO%

SD is a marker of the precision (reproducibility) of the test- it is not a marker of how accurate the test result is

Accuracy: good Accuracy: poor

Precision: good Precision: good

Effect of tcst sensitivity/specificity of a test on prevalence:

test with highest sensitivity (not specificity) increases prevalence of disease (number of people in a population tbat have disease)-

it picks lip more people with the disease since it is a good scree_ning test

tests with high specificity confinn disease and help differentiate a TP from a FP but they are poor screening tests

,Effect of increasing the upper limit of normal of a test reference interval (e.g., raising a reference lnten'a! of 0-4 ng/mL to 0-10 ng/mL) on sensitivity, specificity, PY+, and PV":

increases specificity and positive predictive value-

h.igher values are more likely to represent\.TPs than FPs

specificity always increases, which automatically increases PY+ decreases sensitivity and negative predictive value (PV)-

increasing specificity of a test always decreases its sensitivity and PV

FN rate increases, since more people. with disease are encountered as the reference interval increases

a nomlai test result is more likely to be a FN rarher than a TN

Effect of decreasing the upper limit of normal of a test reference interval (e.g., lowering the fasting glucose level (or diagnosing diabetes mellitus (DM] from >140 mg/dL to >126 mgldL) on sensitivity, specificity, PV, and PV:

increases sensitivity and negative predictive value (PV)-

dropping the upper limit to a lower value means that more people with a negative test

result are likely to be TNs (not have DM) rather than FNs

sensitivity and PV always i_T'lcrease when the upper limit ofa test is lowered decreases specificity and positive predictive vaJue (PV)-

fewer people are likely to have OM, a test result >126 mgldL is more likely to be a FP than a TP test result

summary schematic

2.

Pre\'alence:

Prevalence (number of people with disease in tbe popu.lation studied) == (number of new cases over a period of time) x Duration oftbe disease-

P~IxD

as duration (.D) decreases, prevalence (P) decreases

Incidence

-

as D increases, P increases

incidence (1) is a constant in this relationship-

prevalence c.lcuJation- TP + FN (all people with disease)1 TP + FN + TN + FP (all people with and without disease)

3, example- if treatment for leukemia lengthens the survival period but does not lead to its 'cure, prevalence (P) of leukemia Increases owin~ to the increase in dumtion (D): no effect on incidence (number of new cases of leukemiaY

Example of a calculation for sensitivity, specificity, PV+1 PV-, prevaJence:

Disease

No Disease

Positive test (TP) 60

(FP) 40

Negative test (FN) 20

(TN) 80

Sensitivity of the test: TP / TP + FN ~ 60 / 80 ~ 75% Specificity of the test: TN / TN + FP ~ 80 I 120 ~ 66%

PV-: TN I TN + FN ~ 80 1100 ~ 80% (80% chance it is a TN and a 20% chance it is a FN) p\,,: TP I TP + FP = 60 / 100 ~ 60% (60% chance it is a TP and 40% chance it is a FP) Prevalence: TP + FN I TP + FN + TN + FP ~ 80 1200 = 40%