Negative predictive value

Last revised by Matt A. Morgan on 13 Mar 2015

Negative predictive value of a test/investigation is defined as the proportion of patients with negative results being truly disease free.


Negative predictive value = true negatives detected / total negative results

(where "total negative results" = true negative + false negative)

Bayes' theorem

One can also determine the NPV with an estimate of sensitivity, specificity, and pretest probability (p).

NPV = [(specificity) x (1 - p)] / [specificity x (1 - p) + (1 - sensitivity) x (p)]

Practical points

  • unlike sensitivity and specificity, NPV is highly dependent on the prevalence of the disease in the target population

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Cases and figures

  • Figure 1
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