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Disease prevalence matters

As explained elsewhere on this website the proportion of correct and incorrect classifications of healthy subjects and patients is co-determined by disease prevalence in the study population. On that account the predictive value of a test differs in principle strongly in general practice, in occupational medicine and in an outpatient or clinical population. This is exemplified by the following examples, in which the sensitivity and specificity are the same, and which relate to two populations comprising 1800 subjects, say population A in a hospital setting and population B in a GP setting.

Clinically Test result A Test result B
  + - Total + - Total
Sick 240 30 270 16 2 18
Not sick 60 1470 1530 71 1711 1782
Totals 300 1500 1800 87 1713 1800
   
Prevalence 15% 1%
Sensitivity 89% 89%
Specificity 96% 96%
+ Predictive value 80% 18.4%
- Predictive value 89% 99.9%
Efficiency 95% 95.9%

The table demonstrates what seems a common sense observation: if very few people in a population have the disease for which you are testing, then a very large proportion of subjects will be misdiagnosed as having the disease (low + predictive value), and very few will be incorrectly identified as not having the disease (high – predictive value). Conversely, if a large proportion of the population has the disease, a significant proportion of those who are sick will still be missed, and a significant proportion will be incorrectly identified as sick.

Using the software and associated databases we can apply this to the general population of men and women in the Netherlands and the UK, as well as to the Dutch hospital population.

LLN Criterion GOLD criterion
NL population
GOLD criterion
hospital population
GOLD criterion
UK population
  + - Total + - Total + - Total
Sick 710 379 1089 1397 324 1721 2470 621 3091
Not sick 5 3450 3455 28 2864 2892 785 19421 20206
Totals 715 3829 4544 1425 3188 4613 3255 20042 23297
   
Prevalence GOLD 23.97% 37.31% 13.97%
Prevalence LLN 15.73% 30.89% 13.27%
Sensitivity 99.30% 81.17% 79.91%
Specificity 90.10% 89.84% 96.12%
+ Predictive value 65.20% 81.17% 75.88%
- Predictive value 99.86% 99.03% 96.90
Efficiency 91.54% 92.37% 93.86%

Not surprisingly, if the disease is more prevalent (in the hospital population by a factor 2 based on the LLN criterion) the predictive value of a positive test result is greater.

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