Although many doctors simply utilize one clinical test to identify dry eye illness, the author demonstrates that using several clinical tests coupled with a measure of symptoms will result in the highest degree of accuracy.
The study aims to shed light on the varying probabilities of making an accurate diagnosis of dry eye disease based on the clinical test methods employed. It emphasizes the need for a multi-test approach to minimize the risk of misdiagnosis.
- Utilized Bayes-Price rule to calculate the probability of correct diagnosis for various standard tests.
- Global specificity and sensitivity values for each test were estimated through the Beta distribution, combining data from a literature review.
- Assumed prevalence of dry eye disease was 11.6%.
- Highest probability of correct diagnosis with a single test: Corneal staining (0.28).
- Lowest probability: Ocular Surface Disease Index – OSDI (0.14).
- Best combination: 5-item Dry Eye Questionnaire (DEQ-5) + Corneal staining (0.42).
- Worst combination: OSDI + Tear Film Break Up Time (TBUT) (0.23).
- Simultaneous observation of conjunctival and corneal staining had a probability of 0.49.
- Probability of correct diagnosis increased with the number of positive tests, peaking at 0.90 when all tests were positive.
- Relying on any single test for diagnosing dry eye disease poses a significant risk of misdiagnosis. To mitigate this risk, clinicians should employ multiple tests and consider the simultaneous occurrence of conjunctival and corneal staining as a key diagnostic outcome.
“What is somewhat surprising is that corneal staining as a stand-alone test performs incorrectly in 72% of the cases. Conjunctival staining, coupled with corneal staining, exhibited a significantly increased likelihood of correctly diagnosing dry eye disease.”
– Leonard J. Press OD, FAAO, FCOV