Background: An increasing number of diagnostic tests and biomarkers have been validated during the last decades, and this will still be a prominent field of research in the future because of the need for personalized medicine. Strict evaluation is needed whenever we aim at validating any potential diagnostic tool, and the first requirement a new testing procedure must fulfill is diagnostic accuracy. Summary: Diagnostic accuracy measures tell us about the ability of a test to discriminate between and/or predict disease and health. This discriminative and predictive potential can be quantified by measures of diagnostic accuracy such as sensitivity and specificity, predictive values, likelihood ratios, area under the receiver operating characteristic curve, overall accuracy and diagnostic odds ratio. Some measures are useful for discriminative purposes, while others serve as a predictive tool. Measures of diagnostic accuracy vary in the way they depend on the prevalence, spectrum and definition of the disease. In general, measures of diagnostic accuracy are extremely sensitive to the design of the study. Studies not meeting strict methodological standards usually over- or underestimate the indicators of test performance and limit the applicability of the results of the study. Key Messages: The testing procedure should be verified on a reasonable population, including people with mild and severe disease, thus providing a comparable spectrum. Sensitivities and specificities are not predictive measures. Predictive values depend on disease prevalence, and their conclusions can be transposed to other settings only for studies which are based on a suitable population (e.g. screening studies). Likelihood ratios should be an optimal choice for reporting diagnostic accuracy. Diagnostic accuracy measures must be reported with their confidence intervals. We always have to report paired measures (sensitivity and specificity, predictive values or likelihood ratios) for clinically meaningful thresholds. How much discriminative or predictive power we need depends on the clinical diagnostic pathway and on misclassification (false positives/negatives) costs.

Background: Decreased concentrations of amyloid-β 1-42 (Aβ42 ) in cerebrospinal fluid (CSF) and increased retention of Aβ tracers in the brain on positron emission tomography (PET) are considered the earliest biomarkers of Alzheimer’s disease (AD). H

To assess the discriminating power of multiple cerebrospinal fluid (CSF) biomarkers for Parkinson's disease (PD), we measured several proteins playing an important role in the disease pathogenesis. The activities of β‐glucocerebrosidase and other lysosomal enzymes, together with total and oligomeric α‐synuclein, and total and phosphorylated tau, were thus assessed in CSF of 71 PD patients and compared to 45 neurological controls. Activities of β‐glucocerebrosidase, β‐mannosidase, β‐hexosaminidase, and β‐galactosidase were measured with established enzymatic assays, while α‐synuclein and tau biomarkers were evaluated with immunoassays. A subset of PD patients (n = 44) was also screened for mutations in the β‐glucocerebrosidase‐encoding gene (GBA1). In the PD group, β‐glucocerebrosidase activity was reduced (P < 0.05) and patients at earlier stages showed lower enzymatic activity (P < 0.05); conversely, β‐hexosaminidase activity was significantly increased (P < 0.05). Eight PD patients (18%) presented GBA1 sequence variations; 3 of them were heterozygous for the N370S mutation. Levels of total α‐synuclein were significantly reduced (P < 0.05) in PD, in contrast to increased levels of α‐synuclein oligomers, with a higher oligomeric/total α‐synuclein ratio in PD patients when compared with controls (P < 0.001). A combination of β‐glucocerebrosidase activity, oligomeric/total α‐synuclein ratio, and age gave the best performance in discriminating PD from neurological controls (sensitivity 82%; specificity 71%, area under the receiver operating characteristic curve = 0.87). These results demonstrate the possibility of detecting lysosomal dysfunction in CSF and further support the need to combine different biomarkers for improving the diagnostic accuracy of PD. © 2014 International Parkinson and Movement Disorder Society

Alzheimer’s disease (AD) pathology begins several years before the clinical onset. The long preclinical phase is composed of three stages according to the 2011National Institute on Aging and Alzheimer’s Association (NIA-AA) criteria, followed by mild cognitive impairment (MCI), a featured clinical entity defined as “due to AD”, or “prodromal AD”, when pathophysiological biomarkers (i.e., cerebrospinal fluid or positron emission tomography with amyloid tracer) are positive. In the clinical setting, there is a clear need to detect the earliest symptoms not yet fulfilling MCI criteria, in order to proceed to biomarker assessment for diagnostic definition, thus offering treatment with disease-modifying drugs to patients as early as possible. According to the available evidence, we thus estimated the prevalence and risk of progression at each preclinical AD stage, with special interest in Stage 3. Cross-sectional and longitudinal studies published from April 2008 to May 2018 were obtained through MEDLINE-PubMed, screened, and systematically reviewed by four independent reviewers. Data from included studies were meta-analyzed using random-effects models. Heterogeneity was assessed by I2 statistics. Estimated overall prevalence of preclinical AD was 22% (95% CI = 18–26%). Rate of biomarker positivity overlapped in cognitively normal individuals and people with subjective cognitive decline. The risk of progression increases across preclinical AD stages, with individuals classified as NIA-AA Stage 3 showing the highest risk (73%, 95% CI = 40–92%) compared to those in Stage 2 (38%, 95% CI = 21–59%) and Stage 1 (20%, 95% CI = 10–34%). Available data consistently show that risk of progression increases across the preclinical AD stages, where Stage 3 shows a risk of progression comparable to MCI due to AD. Accordingly, an effort should be made to also operationalize the diagnostic work-up in subjects with subtle cognitive deficits not yet fulfilling MCI criteria. The possibility to define, in the clinical routine, a patient as “pre-MCI due to AD” could offer these subjects the opportunity to use disease-modifying drugs at best.