Physicians do not often correctly interpret the informativeness measures of biomarkers provided in scientifi c papers. The most common estimates are sensitivity (Se) the probability that the biomarker is positive in a case of disease, specifi city (Sp) the probability that the marker is negative for patients who do not have a disease, the positive predictive value of a test result (PPV) the probability of a disease in a marker-positive patient, a negative predictive value (NPV) the probability that a marker-negative patient does not have a disease. Does the very high Se, Sp, PPV or NPV, as well as the revealed a statistically signifi cant association between marker and outcome, mean that the marker is effective? Not always so. The statistical signifi cance of the marker-outcome association is only a necessary condition, but not a suffi cient one. The practical use of the marker depends on its frequency of occurrence (PM) and the prevalence of the disease (PD) in the population under study. The fact that some conventional indices of informativeness can be high even in the absence of a real association between marker and outcome (defi ned in such a case only by PM and PD) can be misleading. This leads us to an important conclusion: conventional indices of biomarker informativeness (Se, Sp, PPV and NPV) must be supplemented by statistics that measure the strength of the relationship between marker and outcome (odds ratio or risk ratio), as well as integral measures of marker informativeness (screening or predictive balance accuracy-SBA or PBA). The quantity of empirically evaluated diagnostic performance measures is directly determined by the study design: The case-control study enables to measure directly Se, Sp, SBA, and OR, the cohort study allows to evaluate PPV, NPV, PBA, OR, and RR. The population-based study provides investigators with any performance indices of diagnostic tests. It also should be kept in mind that Se, Sp and SBA (AUC) characterize only the screening informativeness of the marker. PPV, NPV and PBA characterize only the predictive informativeness of the marker. OR and RR quantify the strength of the association between marker and outcome.