Template:SensSpecPPVNPV: Difference between revisions

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A worked example
A diagnostic test with sensitivity 67% and specificity 91% is applied to 2030 people to look for a disorder with a population prevalence of 1.48%
Patients with bowel cancer
(as confirmed on endoscopy)
Condition positive Condition negative Prevalence
= (TP+FN)/Total_Population
= (20+10)/2030
1.48%
Accuracy (ACC) =
(TP+TN)/Total_Population
= (20+1820)/2030
90.64%
Fecal
occult
blood

screen
test
outcome
Test
outcome
positive
True positive
(TP) = 20
(2030 x 1.48% x 67%)
False positive
(FP) = 180
(2030 x (100 - 1.48%) x (100 - 91%))
Positive predictive value (PPV), Precision
= TP / (TP + FP)
= 20 / (20 + 180)
= 10%
False discovery rate (FDR)
= FP/(TP+FP)
= 180/(20+180)
= 90.0%
Test
outcome
negative
False negative
(FN) = 10
(2030 x 1.48% x (100 - 67%))
True negative
(TN) = 1820
(2030 x (100 -1.48%) x 91%)
False omission rate (FOR)
= FN / (FN + TN)
= 10 / (10 + 1820)
0.55%
Negative predictive value (NPV)
= TN / (FN + TN)
= 1820 / (10 + 1820)
99.45%
TPR, Recall, Sensitivity
= TP / (TP + FN)
= 20 / (20 + 10)
66.7%
False positive rate (FPR),Fall-out, probability of false alarm
= FP/(FP+TN)
= 180/(180+1820)
=9.0%
Positive likelihood ratio (LR+)
= TPR/FPR
= (20/30)/(180/2000)
7.41
Diagnostic odds ratio (DOR) = LR+/LR−
20.2
F1 score = 2 · Precision · Recall/Precision + Recall
0.174
False negative rate (FNR), Miss rate
= FN/(TP+FN)
= 10/(20+10)
33.3%
Specificity, Selectivity, True negative rate (TNR)
= TN / (FP + TN)
= 1820 / (180 + 1820)
= 91%
Negative likelihood ratio (LR−)
= FNR/TNR
= (10/30)/(1820/2000)
0.366

Related calculations

  • False positive rate (α) = type I error = 1 − specificity = FP / (FP + TN) = 180 / (180 + 1820) = 9%
  • False negative rate (β) = type II error = 1 − sensitivity = FN / (TP + FN) = 10 / (20 + 10) = 33%
  • Power = sensitivity = 1 − β
  • Likelihood ratio positive = sensitivity / (1 − specificity) = 0.67 / (1 − 0.91) = 7.4
  • Likelihood ratio negative = (1 − sensitivity) / specificity = (1 − 0.67) / 0.91 = 0.37

Hence with large numbers of false positives and few false negatives, a positive screen test is in itself poor at confirming the disorder (PPV = 10%) and further investigations must be undertaken; it did, however, correctly identify 66.7% of all cases (the sensitivity). However as a screening test, a negative result is very good at reassuring that a patient does not have the disorder (NPV = 99.5%) and at this initial screen correctly identifies 91% of those who do not have cancer (the specificity).

Note: This template is used as a portion of the articles on sensitivity, specificity, likelihood ratios in diagnostic testing, etc. See those articles for additional citations.