Some thoughts on how to interpret the results of studies on diagnostic tests: the DINO study.

4. Given that the purpose of the study is to evaluate the usefulness of the diagnostic questionnaire in question, using diagnoses from biometric tests as a standard, we believe that in addition to calculating sensitivity, specificity and predictive values, the coefficients of positive and negative probability (CPP and CPN respectively) should have been calculated as well. This is because the sensitivity and specificity values, despite completely defining validity (the degree to which a test measures what it is supposed to measure) for the diagnostic test, have the disadvantage of not providing relevant information when it comes to making a clinical decision when faced with a certain test result. The CPP and CPN express a unified summary of sensitivity and specificity, and therefore do not depend on the disease prevalence in each location and permit comparison between different studies, unlike predictive values, which are only valid for the location at which they were calculated.4,5 In this study, the CPP and CPN with 95% CI for each disease (CPP for diabetes, 161.46 [72.21-361.06]; AHT, 15.41 [10.84-21.9]; hyperlipaemia, 10.98 [7.07-17.05]; CPN for diabetes, 0.30 [0.24-0.38]; AHT, 0.52 [0.48-0.57]; hyperlipaemia, 0.68 [0.640.71]) indicate that the questionnaire is useful for diagnosing diabetes and hypertension (relevant CPP >10 with 95% CI) but they are not useful for ruling them out (CPN are not <0.1). With regard to hyperlipaemia, it will be necessary to design more studies (coefficients of probability are statistically significant, but not clinically conclusive). 5. When we refer to diagnostic test studies, parameters ≥80% are considered to be optimum or high, and for this reason, we cannot claim the sensitivities of the study as such.