Which statement about LR- is true?

Which statement about LR- is true?

• A. Lower LR- values indicate better ability to rule OUT disease.
• B. LR- equals Sn / Sp.
• C. LR- is used only for positive test results.
• D. LR- increases post-test probability when negative.

Answer: (A)

Negative likelihood ratio shows how much a negative test result changes the odds of having the disease. The smaller the LR-, the more a negative result helps rule out disease. It’s calculated as (1 − sensitivity) divided by specificity, meaning it compares the chance of a negative result in diseased people to the chance of a negative result in non-diseased people. In practice, you multiply the pre-test odds by the LR- to get post-test odds after a negative result; a very small LR- greatly reduces the post-test probability of disease. That’s why lower LR- values indicate better ability to rule out disease. The other statements don’t fit: LR- is not Sn/Sp; it’s (1 − Sn)/Sp. It is used for interpreting negative results, not only positive ones. And a negative result with an LR- less than 1 reduces, rather than increases, the post-test probability of disease.

Negative likelihood ratio shows how much a negative test result changes the odds of having the disease. The smaller the LR-, the more a negative result helps rule out disease. It’s calculated as (1 − sensitivity) divided by specificity, meaning it compares the chance of a negative result in diseased people to the chance of a negative result in non-diseased people. In practice, you multiply the pre-test odds by the LR- to get post-test odds after a negative result; a very small LR- greatly reduces the post-test probability of disease. That’s why lower LR- values indicate better ability to rule out disease.

The other statements don’t fit: LR- is not Sn/Sp; it’s (1 − Sn)/Sp. It is used for interpreting negative results, not only positive ones. And a negative result with an LR- less than 1 reduces, rather than increases, the post-test probability of disease.