epi.nomogram {epiR}R Documentation

Post-test probability of disease given sensitivity and specificity of a test

Description

Compute the post-test probability of disease given sensitivity and specificity of a test.

Usage

epi.nomogram(se, sp, lr, pre.pos, verbose = FALSE)

Arguments

se

test sensitivity (0 - 1).

sp

test specificity (0 - 1).

lr

a vector of length 2 listing the positive and negative likelihood ratio (respectively) of the test. Ignored if se and sp are not null.

pre.pos

the pre-test probability of the outcome.

verbose

logical, indicating whether detailed or summary results are to be returned.

Value

A list containing the following:

lr

a data frame listing the likelihood ratio of a positive and negative test.

prior

a data frame listing the pre-test probability of being outcome (i.e. disease) positive, as entered by the user.

post

a data frame listing: opos.tpos the post-test probability of being outcome (i.e. disease) positive given a positive test result and opos.tneg the post-test probability of being outcome (i.e. disease) positive given a negative test result.

References

Caraguel C, Vanderstichel R (2013). The two-step Fagan's nomogram: ad hoc interpretation of a diagnostic test result without calculation. Evidence Based Medicine 18: 125 - 128.

Hunink M, Glasziou P (2001). Decision Making in Health and Medicine - Integrating Evidence and Values. Cambridge University Press, pp. 128 - 156.

Examples

## EXAMPLE 1:
## You are presented with a dog with lethargy, exercise intolerance, 
## weight gain and bilaterally symmetric truncal alopecia. You are 
## suspicious of hypothyroidism and take a blood sample to measure 
## basal serum thyroxine (T4).

## You believe that around 5% of dogs presented to your clinic with 
## a signalment of general debility have hypothyroidism. The serum T4 
## has a sensitivity of 0.89 and specificity of 0.85 for diagnosing 
## hypothyroidism in the dog. The laboratory reports a serum T4 
## concentration of 22.0 nmol/L (reference range 19.0 to 58.0 nmol/L). 
## What is the post-test probability that this dog is hypothyroid?

epi.nomogram(se = 0.89, sp = 0.85, lr = NA, pre.pos = 0.05, verbose = FALSE)

## If the test is positive the post-test probability that this dog is  
## hypothyroid is 0.24. If the test is negative the post-test probability 
## that this dog is hypothyroid is 0.0068.


## EXAMPLE 2:
## A dog is presented to you with severe pruritis. You suspect sarcoptic 
## mange and decide to take a skin scraping (LR+ 9000; LR- 0.1). The scrape 
## returns a negative result (no mites are seen). What is the post-test 
## probability that your patient has sarcoptic mange? You recall that you 
## diagnose around 3 cases of sarcoptic mange per year in a clinic that 
## sees approximately 2 -- 3 dogs per week presented with pruritic skin disease.


## Calculate the pre-test probability of sarcoptes:
pre.pos <- 3 / (3 * 52)
## The pre-test probability that this dog is sarcoptes positive is 0.019. 

epi.nomogram(se = NA, sp = NA, lr = c(9000, 0.1), pre.pos = pre.pos, 
   verbose = FALSE)

## If the skin scraping is negative the post-test probability that this dog 
## has sarcoptic mange is 0.002.


[Package epiR version 2.0.31 Index]