Herein, we comment on the methodological pitfalls of this article in particular, and the accuracy of the research on diagnostic tests in general. Basic steps in the design of diagnostic

accuracy studies include determination of study objectives, identification of target-patient population, and selection of the gold standard as well as selection of measures of accuracy.2 The first and second steps have been managed properly in the study by Sanaei and colleagues. However, the authors’ approach to the third and fourth steps needs more clarification. The selection of a gold standard Inhibitors,research,lifescience,medical is the most difficult step in studies involving diagnostic tests. Some investigators believe that there is no a true gold standard, since no test or procedure is entirely accurate to differentiate patients and healthy

individuals. However, for all studies on the accuracy of diagnostic tests, it is important to establish an operational standard.2 Although the presence of a test with the highest sensitivity and specificity is ideal, some issues including availability, cost and invasiveness of the Inhibitors,research,lifescience,medical test should be considered. Any change in the gold standard alters the sensitivity and specificity of a diagnostic test. Accordingly, when the gold standard was changed (table 3 of the paper), the measure of accuracy of ELISA test was changed as well. Therefore, Inhibitors,research,lifescience,medical the authors should have chosen a test, which had a specified sensitivity and specificity, as the gold standard. 2Methoxyestradiol Application

of an imperfect gold standard usually leads to the underestimation of test accuracy, which is termed imperfect gold standard bias.2 The selection of measures of accuracy is another step in the design of studies on diagnostic tests accuracy. The paper by Sanaei and colleagues has reported the positive and negative predictive Inhibitors,research,lifescience,medical values. The predictive value is a post-test probability, and is affected by the prevalence of the disease. In contrast to the sensitivity and specificity, the predictive value is not a measure of intrinsic diagnostic accuracy, and varies with any change in the pre-test Inhibitors,research,lifescience,medical probability. Therefore, the results of any test must be interpreted considering the pre-test probability of the disease in the desired population.
Antiphospholipid syndrome (APS) is an autoimmune disease. The disease has two forms including a primary and a secondary. The primary form is an isolated diagnosis, and the secondary form is associated with lupus or other diseases like rheumatoid Rutecarpine arthritis. The correct diagnosis of the disease requires one clinical criterion such as thrombosis or abortion, and a positive moderate to high serum titer for anticardiolipin or Antiβ2glycoprotein. About 60 to 80% of patients with APS are women. Moreover, 10% of first-stroke victims, especially those who are young, and up to 21% of women with three or more consecutive fetal losses have APS.1 APS is a multisystem disease, and affects all organ systems.