Negative predictive value
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The negative predictive value is the proportion of patients with negative test results who are correctly diagnosed.
Contents |
[edit] Worked example
- Relationships among terms
| Condition (as determined by "Gold standard") |
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| True | False | |||
| Test outcome |
Positive | True Positive | False Positive (Type I error, P-value) |
→ Positive predictive value |
| Negative | False Negative (Type II error) |
True Negative | → Negative predictive value | |
| ↓ Sensitivity |
↓ Specificity |
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- A worked example
- the Fecal occult blood (FOB) screen test is used in 203 people to look for bowel cancer:
| Patients with bowel cancer (as confirmed on endoscopy) |
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| True | False | ? | ||
| FOB test |
Positive | TP = 2 | FP = 18 | = TP / (TP + FP) = 2 / (2 + 18) = 2 / 20 ≡ 10% |
| Negative | FN = 1 | TN = 182 | = TN / (TN + FN) 182 / (1 + 182) = 182 / 183 ≡ 99.5% |
|
| ↓ = TP / (TP + FN) = 2 / (2 + 1) = 2 / 3 ≡ 66.67% |
↓ = TN / (FP + TN) = 182 / (18 + 182) = 182 / 200 ≡ 91% |
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Related calculations
- False positive rate (α) = FP / (FP + TN) = 18 / (18 + 182) = 9% = 1 - specificity
- False negative rate (β) = FN / (TP + FN) = 1 / (2 + 1) = 33% = 1 - sensitivity
- Power = 1 − β
Hence with large numbers of false positives and few false negatives, a positive FOB screen test is in itself poor at confirming cancer (PPV=10%) and further investigations must be undertaken, it will though pickup 66.7% of all cancers (the sensitivity). However as a screening test, a negative result is very good at reassuring that a patient does not have cancer (NPV=99.5%) and at this initial screen correctly identifies 91% of those who do not have cancer (the specificity).
[edit] Definition
The Negative Predictive Value can be defined as:
or, alternatively,
[edit] See also
[edit] References
- Altman DG, Bland JM (9 Jul 1994). "Diagnostic tests 2: Predictive values". BMJ 309 (6947): 102. PMID 8038641.
