Mini-Cog for the detection of dementia within a community setting.

BACKGROUND: Alzheimer's disease and related forms of dementia are becoming increasingly prevalent with the aging of many populations. The diagnosis of Alzheimer's disease relies on tests to evaluate cognition and discriminate between individuals with dementia and those without dementia. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings. OBJECTIVES: The primary objective of this review was to determine the accuracy of the Mini-Cog for detecting dementia in a community setting. Secondary objectives included investigations of the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity included the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality. Overall, the goals of this review were to determine if the Mini-Cog is a cognitive screening test that could be recommended to screen for cognitive impairment in community settings. SEARCH METHODS: We searched MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (Ovid SP), Science Citation Index (Web of Science), BIOSIS previews (Web of Science), LILACS (BIREME), and the Cochrane Dementia Group's developing register of diagnostic test accuracy studies to March 2013. We used citation tracking (using the database's 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data. SELECTION CRITERIA: We included all cross-sectional studies that utilized the Mini-Cog as an index test for the diagnosis of dementia when compared to a reference standard diagnosis of dementia using standardized dementia diagnostic criteria. For the current review we only included studies that were conducted on samples from community settings, and excluded studies that were conducted in primary care or secondary care settings. We considered studies to be conducted in a community setting where participants were sampled from the general population. DATA COLLECTION AND ANALYSIS: Information from studies meeting the inclusion criteria were extracted including information on the characteristics of participants in the studies. The quality of the studies was assessed using the QUADAS-2 criteria and summarized using risk of bias applicability and summary graphs. We extracted information on the diagnostic test accuracy of studies including the sensitivity, specificity, and 95% confidence intervals of these measures and summarized the findings using forest plots. Study specific sensitivities and specificities were also plotted in receiver operating curve space. MAIN RESULTS: Three studies met the inclusion criteria, with a total of 1620 participants. The sensitivities of the Mini-Cog in the individual studies were reported as 0.99, 0.76 and 0.99. The specificity of the Mini-Cog varied in the individual studies and was 0.93, 0.89 and 0.83. There was clinical and methodological heterogeneity between the studies which precluded a pooled meta-analysis of the results. Methodological limitations were present in all the studies introducing potential sources of bias, specifically with respect to the methods for participant selection. AUTHORS' CONCLUSIONS: There are currently few studies assessing the diagnostic test accuracy of the Mini-Cog in community settings. The limited number of studies and the methodological limitations that are present in the current studies make it difficult to provide recommendations for or against the use of the Mini-Cog as a cognitive screening test in community settings. Additional well-designed studies comparing the Mini-Cog to other brief cognitive screening tests are required in order to determine the accuracy and utility of the Mini-Cog in community based settings.

Mini-Cog for the detection of dementia within a secondary care setting.

BACKGROUND: The diagnosis of Alzheimer's disease dementia and other dementias relies on clinical assessment. There is a high prevalence of cognitive disorders, including undiagnosed dementia in secondary care settings. Short cognitive tests can be helpful in identifying those who require further specialist diagnostic assessment; however, there is a lack of consensus around the optimal tools to use in clinical practice. The Mini-Cog is a short cognitive test comprising three-item recall and a clock-drawing test that is used in secondary care settings. OBJECTIVES: The primary objective was to determine the accuracy of the Mini-Cog for detecting dementia in a secondary care setting. The secondary objectives were to investigate the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity will include the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality. SEARCH METHODS: We searched the following sources in September 2012, with an update to 12 March 2019: Cochrane Dementia Group Register of Diagnostic Test Accuracy Studies, MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Web of Knowledge), Science Citation Index (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We made no exclusions with regard to language of Mini-Cog administration or language of publication, using translation services where necessary. SELECTION CRITERIA: We included cross-sectional studies and excluded case-control designs, due to the risk of bias. We selected those studies that included the Mini-Cog as an index test to diagnose dementia where dementia diagnosis was confirmed with reference standard clinical assessment using standardised dementia diagnostic criteria. We only included studies in secondary care settings (including inpatient and outpatient hospital participants). DATA COLLECTION AND ANALYSIS: We screened all titles and abstracts generated by the electronic database searches. Two review authors independently checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool. We extracted data into two-by-two tables to allow calculation of accuracy metrics for individual studies, reporting the sensitivity, specificity, and 95% confidence intervals of these measures, summarising them graphically using forest plots. MAIN RESULTS: Three studies with a total of 2560 participants fulfilled the inclusion criteria, set in neuropsychology outpatient referrals, outpatients attending a general medicine clinic, and referrals to a memory clinic. Only n = 1415 (55.3%) of participants were included in the analysis to inform evaluation of Mini-Cog test accuracy, due to the selective use of available data by study authors. There were concerns related to high risk of bias with respect to patient selection, and unclear risk of bias and high concerns related to index test conduct and applicability. In all studies, the Mini-Cog was retrospectively derived from historic data sets. No studies included acute general hospital inpatients. The prevalence of dementia ranged from 32.2% to 87.3%. The sensitivities of the Mini-Cog in the individual studies were reported as 0.67 (95% confidence interval (CI) 0.63 to 0.71), 0.60 (95% CI 0.48 to 0.72), and 0.87 (95% CI 0.83 to 0.90). The specificity of the Mini-Cog for each individual study was 0.87 (95% CI 0.81 to 0.92), 0.65 (95% CI 0.57 to 0.73), and 1.00 (95% CI 0.94 to 1.00). We did not perform meta-analysis due to concerns related to risk of bias and heterogeneity. AUTHORS' CONCLUSIONS: This review identified only a limited number of diagnostic test accuracy studies using Mini-Cog in secondary care settings. Those identified were at high risk of bias related to patient selection and high concerns related to index test conduct and applicability. The evidence was indirect, as all studies evaluated Mini-Cog differently from the review question, where it was anticipated that studies would conduct Mini-Cog and independently but contemporaneously perform a reference standard assessment to diagnose dementia. The pattern of test accuracy varied across the three studies. Future research should evaluate Mini-Cog as a test in itself, rather than derived from other neuropsychological assessments. There is also a need for evaluation of the feasibility of the Mini-Cog for the detection of dementia to help adequately determine its role in the clinical pathway.

Mini-Cog for the detection of dementia within a primary care setting.

BACKGROUND: Alzheimer's disease and other forms of dementia are becoming increasingly common with the aging of most populations. The majority of individuals with dementia will first present for care and assessment in primary care settings. There is a need for brief dementia screening instruments that can accurately detect dementia in primary care settings. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings. OBJECTIVES: To determine the accuracy of the Mini-Cog for detecting dementia in a primary care setting. SEARCH METHODS: We searched the Cochrane Dementia and Cognitive Improvement Register of Diagnostic Test Accuracy Studies, MEDLINE, Embase and four other databases, initially to September 2012. Since then, four updates to the search were performed using the same search methods, and the most recent was January 2017. We used citation tracking (using the databases' 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data. SELECTION CRITERIA: We only included studies that evaluated the Mini-Cog as an index test for the diagnosis of Alzheimer's disease dementia or related forms of dementia when compared to a reference standard using validated criteria for dementia. We only included studies that were conducted in primary care populations. DATA COLLECTION AND ANALYSIS: We extracted and described information on the characteristics of the study participants and study setting. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria we evaluated the quality of studies, and we assessed risk of bias and applicability of each study for each domain in QUADAS-2. Two review authors independently extracted information on the true positives, true negatives, false positives, and false negatives and entered the data into Review Manager 5 (RevMan 5). We then used RevMan 5 to determine the sensitivity, specificity, and 95% confidence intervals. We summarized the sensitivity and specificity of the Mini-Cog in the individual studies in forest plots and also plotted them in a receiver operating characteristic plot. We also created a 'Risk of bias' and applicability concerns graph to summarize information related to the quality of included studies. MAIN RESULTS: There were a total of four studies that met our inclusion criteria, including a total of 1517 total participants. The sensitivity of the Mini-Cog varied between 0.76 to 1.00 in studies while the specificity varied between 0.27 to 0.85. The included studies displayed significant heterogeneity in both methodologies and clinical populations, which did not allow for a meta-analysis to be completed. Only one study (Holsinger 2012) was found to be at low risk of bias on all methodological domains. The results of this study reported that the sensitivity of the Mini-Cog was 0.76 and the specificity was 0.73. We found the quality of all other included studies to be low due to a high risk of bias with methodological limitations primarily in their selection of participants. AUTHORS' CONCLUSIONS: There is a limited number of studies evaluating the accuracy of the Mini-Cog for the diagnosis of dementia in primary care settings. Given the small number of studies, the wide range in estimates of the accuracy of the Mini-Cog, and methodological limitations identified in most of the studies, at the present time there is insufficient evidence to recommend that the Mini-Cog be used as a screening test for dementia in primary care. Further studies are required to determine the accuracy of Mini-Cog in primary care and whether this tool has sufficient diagnostic test accuracy to be useful as a screening test in this setting.

Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI).

BACKGROUND: Dementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people with mild cognitive impairment (MCI) will progress to dementia but others remain stable or recover full function. There is great interest in finding good predictors of dementia in people with MCI. The Mini-Mental State Examination (MMSE) is the best-known and the most often used short screening tool for providing an overall measure of cognitive impairment in clinical, research and community settings. OBJECTIVES: To determine the accuracy of the Mini Mental State Examination for the early detection of dementia in people with mild cognitive impairment SEARCH METHODS: We searched ALOIS (Cochrane Dementia and Cognitive Improvement Specialized Register of diagnostic and intervention studies (inception to May 2014); MEDLINE (OvidSP) (1946 to May 2014); EMBASE (OvidSP) (1980 to May 2014); BIOSIS (Web of Science) (inception to May 2014); Web of Science Core Collection, including the Conference Proceedings Citation Index (ISI Web of Science) (inception to May 2014); PsycINFO (OvidSP) (inception to May 2014), and LILACS (BIREME) (1982 to May 2014). We also searched specialized sources of diagnostic test accuracy studies and reviews, most recently in May 2014: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). No language or date restrictions were applied to the electronic searches and methodological filters were not used as a method to restrict the search overall so as to maximize sensitivity. We also checked reference lists of relevant studies and reviews, tracked citations in Scopus and Science Citation Index, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on MMSE for dementia diagnosis to try to locate possibly relevant but unpublished data. SELECTION CRITERIA: We considered longitudinal studies in which results of the MMSE administered to MCI participants at baseline were obtained and the reference standard was obtained by follow-up over time. We included participants recruited and clinically classified as individuals with MCI under Petersen and revised Petersen criteria, Matthews criteria, or a Clinical Dementia Rating = 0.5. We used acceptable and commonly used reference standards for dementia in general, Alzheimer's dementia, Lewy body dementia, vascular dementia and frontotemporal dementia. DATA COLLECTION AND ANALYSIS: We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. We assessed the identified full papers for eligibility and extracted data to create two by two tables for dementia in general and other dementias. Two authors independently performed quality assessment using the QUADAS-2 tool. Due to high heterogeneity and scarcity of data, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic curve. MAIN RESULTS: In this review, we included 11 heterogeneous studies with a total number of 1569 MCI patients followed for conversion to dementia. Four studies assessed the role of baseline scores of the MMSE in conversion from MCI to all-cause dementia and eight studies assessed this test in conversion from MCI to Alzheimer´s disease dementia. Only one study provided information about the MMSE and conversion from MCI to vascular dementia. For conversion from MCI to dementia in general, the accuracy of baseline MMSE scores ranged from sensitivities of 23% to 76% and specificities from 40% to 94%. In relationship to conversion from MCI to Alzheimer's disease dementia, the accuracy of baseline MMSE scores ranged from sensitivities of 27% to 89% and specificities from 32% to 90%. Only one study provided information about conversion from MCI to vascular dementia, presenting a sensitivity of 36% and a specificity of 80% with an incidence of vascular dementia of 6.2%. Although we had planned to explore possible sources of heterogeneity, this was not undertaken due to the scarcity of studies included in our analysis. AUTHORS' CONCLUSIONS: Our review did not find evidence supporting a substantial role of MMSE as a stand-alone single-administration test in the identification of MCI patients who could develop dementia. Clinicians could prefer to request additional and extensive tests to be sure about the management of these patients. An important aspect to assess in future updates is if conversion to dementia from MCI stages could be predicted better by MMSE changes over time instead of single measurements. It is also important to assess if a set of tests, rather than an isolated one, may be more successful in predicting conversion from MCI to dementia.

Plasma and cerebrospinal fluid ABeta42 for the differential diagnosis of Alzheimer's disease dementia in participants diagnosed with any dementia subtype in a specialist care setting.

BACKGROUND: Dementia is a syndrome that comprises many differing pathologies, including Alzheimer's disease dementia (ADD), vascular dementia (VaD) and frontotemporal dementia (FTD). People may benefit from knowing the type of dementia they live with, as this could inform prognosis and may allow for tailored treatment. Beta-amyloid (1-42) (ABeta42) is a protein which decreases in both the plasma and cerebrospinal fluid (CSF) of people living with ADD, when compared to people with no dementia. However, it is not clear if changes in ABeta42 are specific to ADD or if they are also seen in other types of dementia. It is possible that ABeta42 could help differentiate ADD from other dementia subtypes. OBJECTIVES: To determine the accuracy of plasma and CSF ABeta42 for distinguishing ADD from other dementia subtypes in people who meet the criteria for a dementia syndrome. SEARCH METHODS: We searched MEDLINE, and nine other databases up to 18 February 2020. We checked reference lists of any relevant systematic reviews to identify additional studies. SELECTION CRITERIA: We considered cross-sectional studies that differentiated people with ADD from other dementia subtypes. Eligible studies required measurement of participant plasma or CSF ABeta42 levels and clinical assessment for dementia subtype. DATA COLLECTION AND ANALYSIS: Seven review authors working independently screened the titles and abstracts generated by the searches. We collected data on study characteristics and test accuracy. We used the second version of the 'Quality Assessment of Diagnostic Accuracy Studies' (QUADAS-2) tool to assess internal and external validity of results. We extracted data into 2 x 2 tables, cross-tabulating index test results (ABeta42) with the reference standard (diagnostic criteria for each dementia subtype). We performed meta-analyses using bivariate, random-effects models. We calculated pooled estimates of sensitivity, specificity, positive predictive values, positive and negative likelihood ratios, and corresponding 95% confidence intervals (CIs). In the primary analysis, we assessed accuracy of plasma or CSF ABeta42 for distinguishing ADD from other mixed dementia types (non-ADD). We then assessed accuracy of ABeta42 for differentiating ADD from specific dementia types: VaD, FTD, dementia with Lewy bodies (DLB), alcohol-related cognitive disorder (ARCD), Creutzfeldt-Jakob disease (CJD) and normal pressure hydrocephalus (NPH). To determine test-positive cases, we used the ABeta42 thresholds employed in the respective primary studies. We then performed sensitivity analyses restricted to those studies that used common thresholds for ABeta42. MAIN RESULTS: We identified 39 studies (5000 participants) that used CSF ABeta42 levels to differentiate ADD from other subtypes of dementia. No studies of plasma ABeta42 met the inclusion criteria. No studies were rated as low risk of bias across all QUADAS-2 domains. High risk of bias was found predominantly in the domains of patient selection (28 studies) and index test (25 studies). The pooled estimates for differentiating ADD from other dementia subtypes were as follows: ADD from non-ADD: sensitivity 79% (95% CI 0.73 to 0.85), specificity 60% (95% CI 0.52 to 0.67), 13 studies, 1704 participants, 880 participants with ADD; ADD from VaD: sensitivity 79% (95% CI 0.75 to 0.83), specificity 69% (95% CI 0.55 to 0.81), 11 studies, 1151 participants, 941 participants with ADD; ADD from FTD: sensitivity 85% (95% CI 0.79 to 0.89), specificity 72% (95% CI 0.55 to 0.84), 17 studies, 1948 participants, 1371 participants with ADD; ADD from DLB: sensitivity 76% (95% CI 0.69 to 0.82), specificity 67% (95% CI 0.52 to 0.79), nine studies, 1929 participants, 1521 participants with ADD. Across all dementia subtypes, sensitivity was greater than specificity, and the balance of sensitivity and specificity was dependent on the threshold used to define test positivity. AUTHORS' CONCLUSIONS: Our review indicates that measuring ABeta42 levels in CSF may help differentiate ADD from other dementia subtypes, but the test is imperfect and tends to misdiagnose those with non-ADD as having ADD. We would caution against the use of CSF ABeta42 alone for dementia classification. However, ABeta42 may have value as an adjunct to a full clinical assessment, to aid dementia diagnosis.

Mini-Cog for the diagnosis of Alzheimer's disease dementia and other dementias within a secondary care setting.

BACKGROUND: The diagnosis of Alzheimer's disease dementia and other dementias relies on clinical assessment. There is a high prevalence of cognitive disorders, including undiagnosed dementia in secondary care settings. Short cognitive tests can be helpful in identifying those who require further specialist diagnostic assessment; however, there is a lack of consensus around the optimal tools to use in clinical practice. The Mini-Cog is a short cognitive test comprising three-item recall and a clock-drawing test that is used in secondary care settings. OBJECTIVES: The primary objective was to determine the diagnostic accuracy of the Mini-Cog for detecting Alzheimer's disease dementia and other dementias in a secondary care setting. The secondary objectives were to investigate the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity will include the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality. SEARCH METHODS: We searched the following sources in September 2012, with an update to 12 March 2019: Cochrane Dementia Group Register of Diagnostic Test Accuracy Studies, MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Web of Knowledge), Science Citation Index (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We made no exclusions with regard to language of Mini-Cog administration or language of publication, using translation services where necessary. SELECTION CRITERIA: We included cross-sectional studies and excluded case-control designs, due to the risk of bias. We selected those studies that included the Mini-Cog as an index test to diagnose dementia where dementia diagnosis was confirmed with reference standard clinical assessment using standardised dementia diagnostic criteria. We only included studies in secondary care settings (including inpatient and outpatient hospital participants). DATA COLLECTION AND ANALYSIS: We screened all titles and abstracts generated by the electronic database searches. Two review authors independently checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool. We extracted data into two-by-two tables to allow calculation of accuracy metrics for individual studies, reporting the sensitivity, specificity, and 95% confidence intervals of these measures, summarising them graphically using forest plots. MAIN RESULTS: Three studies with a total of 2560 participants fulfilled the inclusion criteria, set in neuropsychology outpatient referrals, outpatients attending a general medicine clinic, and referrals to a memory clinic. Only n = 1415 (55.3%) of participants were included in the analysis to inform evaluation of Mini-Cog test accuracy, due to the selective use of available data by study authors. There were concerns related to high risk of bias with respect to patient selection, and unclear risk of bias and high concerns related to index test conduct and applicability. In all studies, the Mini-Cog was retrospectively derived from historic data sets. No studies included acute general hospital inpatients. The prevalence of dementia ranged from 32.2% to 87.3%. The sensitivities of the Mini-Cog in the individual studies were reported as 0.67 (95% confidence interval (CI) 0.63 to 0.71), 0.60 (95% CI 0.48 to 0.72), and 0.87 (95% CI 0.83 to 0.90). The specificity of the Mini-Cog for each individual study was 0.87 (95% CI 0.81 to 0.92), 0.65 (95% CI 0.57 to 0.73), and 1.00 (95% CI 0.94 to 1.00). We did not perform meta-analysis due to concerns related to risk of bias and heterogeneity. AUTHORS' CONCLUSIONS: This review identified only a limited number of diagnostic test accuracy studies using Mini-Cog in secondary care settings. Those identified were at high risk of bias related to patient selection and high concerns related to index test conduct and applicability. The evidence was indirect, as all studies evaluated Mini-Cog differently from the review question, where it was anticipated that studies would conduct Mini-Cog and independently but contemporaneously perform a reference standard assessment to diagnose dementia. The pattern of test accuracy varied across the three studies. Future research should evaluate Mini-Cog as a test in itself, rather than derived from other neuropsychological assessments. There is also a need for evaluation of the feasibility of the Mini-Cog for the diagnosis of dementia to help adequately determine its role in the clinical pathway.

Aß and the dementia syndrome: Simple versus complex perspectives.

BACKGROUND: The amyloid cascade hypothesis (ACH) has dominated strategy in dementia research for decades despite evidence of its limitations including known heterogeneity of the dementia syndrome in the population and the narrow focus on a single molecule - the amyloid beta protein (Aß) as causal for all Alzheimer-type dementia. Other hypotheses relevant to Aß are the presenilin (PS) hypothesis (PSH) relating to the involvement of PS in the generation of Aß, and the amyloid precursor protein (APP) matrix approach (AMA), relating to the complex and dynamic breakdown of APP, from which Aß derives. MATERIALS AND METHODS: In this article we explore perspectives relating to complex disorders occurring mainly in older populations through a detailed case study of the role of Aß in AD. RESULTS: Scrutiny of the evidence generated so far reveals and a lack of understanding of the wider APP proteolytic system and how narrow research into the dementia syndrome has been to date. Confounding factors add significant limitations to the understanding of the current evidence base. CONCLUSIONS: A better characterisation of the entire APP proteolytic system in the human brain is urgently required to place Aß in its complex physiological context. From a molecular perspective, a combination of the alternative hypotheses, the PSH and the AMA may better describe the complexity of the APP proteolytic system leading to new therapeutic approaches. The reductionist approach is widespread throughout biomedical research and this example highlights how neglect of complexity can undermine investigations of complex disorders, particularly those arising in the oldest in our populations.

18F-FDG PET for Prediction of Conversion to Alzheimer's Disease Dementia in People with Mild Cognitive Impairment: An Updated Systematic Review of Test Accuracy.

BACKGROUND: A previous Cochrane systematic review concluded there is insufficient evidence to support the routine use of 18F-FDG PET in clinical practice in people with mild cognitive impairment (MCI). OBJECTIVES: To update the evidence and reassess the accuracy of 18F-FDG-PET for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease (AD) dementia at follow-up. METHODS: A systematic review including comprehensive search of electronic databases from January 2013 to July 2017, to update original searches (1999 to 2013). All key review steps, including quality assessment using QUADAS 2, were performed independently and blindly by two review authors. Meta-analysis could not be conducted due to heterogeneity across studies. RESULTS: When all included studies were examined across all semi-quantitative and quantitative metrics, exploratory analysis for conversion of MCI to AD dementia (n = 24) showed highly variable accuracy; half the studies failed to meet four or more of the seven sets of QUADAS 2 criteria. Variable accuracy for all metrics was also found across eleven newly included studies published in the last 5 years (range: sensitivity 56-100%, specificity 24-100%). The most consistently high sensitivity and specificity values (approximately ≥80%) were reported for the sc-SPM (single case statistical parametric mapping) metric in 6 out of 8 studies. CONCLUSION: Systematic and comprehensive assessment of studies of 18FDG-PET for prediction of conversion from MCI to AD dementia reveals many studies have methodological limitations according to Cochrane diagnostic test accuracy gold standards, and shows accuracy remains highly variable, including in the most recent studies. There is some evidence, however, of higher and more consistent accuracy in studies using computer aided metrics, such as sc-SPM, in specialized clinical settings. Robust, methodologically sound prospective longitudinal cohort studies with long (≥5 years) follow-up, larger consecutive samples, and defined baseline threshold(s) are needed to test these promising results. Further evidence of the clinical validity and utility of 18F-FDG PET in people with MCI is needed.

Dementia Research: Populations, Progress, Problems, and Predictions.

Alzheimer's disease (AD) is a clinicopathologically defined syndrome leading to cognitive impairment. Following the recent failures of amyloid-based randomized controlled trials to change the course of AD, there are growing calls for a re-evaluation of basic AD research. Epidemiology offers one approach to integrating the available evidence. Here we examine relationships between evidence from population-based, clinicopathological studies of brain aging and a range of hypotheses from all areas of AD research. We identify various problems, including a lack of systematic approach to measurement of clinical and neuropathological factors associated with dementia in experimental and clinical settings, poor understanding of the strengths and weaknesses of different observational and experimental designs, a lack of clarity in relation to disease definitions from the clinical, neuropathological, and molecular perspectives, inadequate characterization of brain aging in the human population, difficulties in translation between laboratory-based and population-based evidence bases, and a lack of communication between different sections of the dementia research community. Population studies highlight complexity and predict that therapeutic approaches based on single disease features will not be successful. Better characterization of brain aging in the human population is urgently required to select biomarkers and therapeutic targets that are meaningful to human disease. The generation of detailed and reliable evidence must be addressed before progress toward therapeutic interventions can be made.

Mini-Cog for the diagnosis of Alzheimer's disease dementia and other dementias within a primary care setting.

BACKGROUND: Alzheimer's disease and other forms of dementia are becoming increasingly common with the aging of most populations. The majority of individuals with dementia will first present for care and assessment in primary care settings. There is a need for brief dementia screening instruments that can accurately diagnose dementia in primary care settings. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings. OBJECTIVES: To determine the diagnostic accuracy of the Mini-Cog for diagnosing Alzheimer's disease dementia and related dementias in a primary care setting. SEARCH METHODS: We searched the Cochrane Dementia and Cognitive Improvement Register of Diagnostic Test Accuracy Studies, MEDLINE, Embase and four other databases, initially to September 2012. Since then, four updates to the search were performed using the same search methods, and the most recent was January 2017. We used citation tracking (using the databases' 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data. SELECTION CRITERIA: We only included studies that evaluated the Mini-Cog as an index test for the diagnosis of Alzheimer's disease dementia or related forms of dementia when compared to a reference standard using validated criteria for dementia. We only included studies that were conducted in primary care populations. DATA COLLECTION AND ANALYSIS: We extracted and described information on the characteristics of the study participants and study setting. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria we evaluated the quality of studies, and we assessed risk of bias and applicability of each study for each domain in QUADAS-2. Two review authors independently extracted information on the true positives, true negatives, false positives, and false negatives and entered the data into Review Manager 5 (RevMan 5). We then used RevMan 5 to determine the sensitivity, specificity, and 95% confidence intervals. We summarized the sensitivity and specificity of the Mini-Cog in the individual studies in forest plots and also plotted them in a receiver operating characteristic plot. We also created a 'Risk of bias' and applicability concerns graph to summarize information related to the quality of included studies. MAIN RESULTS: There were a total of four studies that met our inclusion criteria, including a total of 1517 total participants. The sensitivity of the Mini-Cog varied between 0.76 to 1.00 in studies while the specificity varied between 0.27 to 0.85. The included studies displayed significant heterogeneity in both methodologies and clinical populations, which did not allow for a meta-analysis to be completed. Only one study (Holsinger 2012) was found to be at low risk of bias on all methodological domains. The results of this study reported that the sensitivity of the Mini-Cog was 0.76 and the specificity was 0.73. We found the quality of all other included studies to be low due to a high risk of bias with methodological limitations primarily in their selection of participants. AUTHORS' CONCLUSIONS: There is a limited number of studies evaluating the accuracy of the Mini-Cog for the diagnosis of dementia in primary care settings. Given the small number of studies, the wide range in estimates of the accuracy of the Mini-Cog, and methodological limitations identified in most of the studies, at the present time there is insufficient evidence to recommend that the Mini-Cog be used as a screening test for dementia in primary care. Further studies are required to determine the accuracy of Mini-Cog in primary care and whether this tool has sufficient diagnostic test accuracy to be useful as a screening test in this setting.

CSF tau and the CSF tau/ABeta ratio for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

BACKGROUND: Research suggests that measurable change in cerebrospinal fluid (CSF) biomarkers occurs years in advance of the onset of clinical symptoms (Beckett 2010). In this review, we aimed to assess the ability of CSF tau biomarkers (t-tau and p-tau) and the CSF tau (t-tau or p-tau)/ABeta ratio to enable the detection of Alzheimer's disease pathology in patients with mild cognitive impairment (MCI). These biomarkers have been proposed as important in new criteria for Alzheimer's disease dementia that incorporate biomarker abnormalities. OBJECTIVES: To determine the diagnostic accuracy of 1) CSF t-tau, 2) CSF p-tau, 3) the CSF t-tau/ABeta ratio and 4) the CSF p-tau/ABeta ratio index tests for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease dementia or other forms of dementia at follow-up. SEARCH METHODS: The most recent search for this review was performed in January 2013. We searched MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Thomson Reuters Web of Science), Web of Science Core Collection, including Conference Proceedings Citation Index (Thomson Reuters Web of Science), PsycINFO (OvidSP), and LILACS (BIREME). We searched specialized sources of diagnostic test accuracy studies and reviews. We checked reference lists of relevant studies and reviews for additional studies. We contacted researchers for possible relevant but unpublished data. We did not apply any language or data restriction to the electronic searches. We did not use any methodological filters as a method to restrict the search overall. SELECTION CRITERIA: We selected those studies that had prospectively well-defined cohorts with any accepted definition of MCI and with CSF t-tau or p-tau and CSF tau (t-tau or p-tau)/ABeta ratio values, documented at or around the time the MCI diagnosis was made. We also included studies which looked at data from those cohorts retrospectively, and which contained sufficient data to construct two by two tables expressing those biomarker results by disease status. Moreover, studies were only selected if they applied a reference standard for Alzheimer's disease dementia diagnosis, for example, the NINCDS-ADRDA or Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. DATA COLLECTION AND ANALYSIS: We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies, and the full papers for eligibility. Two independent assessors performed data extraction and quality assessment. Where data allowed, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic (ROC) curve. MAIN RESULTS: In total, 1282 participants with MCI at baseline were identified in the 15 included studies of which 1172 had analysable data; 430 participants converted to Alzheimer's disease dementia and 130 participants to other forms of dementia. Follow-up ranged from less than one year to over four years for some participants, but in the majority of studies was in the range one to three years. Conversion to Alzheimer's disease dementia The accuracy of the CSF t-tau was evaluated in seven studies (291 cases and 418 non-cases).The sensitivity values ranged from 51% to 90% while the specificity values ranged from 48% to 88%. At the median specificity of 72%, the estimated sensitivity was 75% (95% CI 67 to 85), the positive likelihood ratio was 2.72 (95% CI 2.43 to 3.04), and the negative likelihood ratio was 0.32 (95% CI 0.22 to 0.47).Six studies (164 cases and 328 non-cases) evaluated the accuracy of the CSF p-tau. The sensitivities were between 40% and 100% while the specificities were between 22% and 86%. At the median specificity of 47.5%, the estimated sensitivity was 81% (95% CI: 64 to 91), the positive likelihood ratio was 1.55 (CI 1.31 to 1.84), and the negative likelihood ratio was 0.39 (CI: 0.19 to 0.82).Five studies (140 cases and 293 non-cases) evaluated the accuracy of the CSF p-tau/ABeta ratio. The sensitivities were between 80% and 96% while the specificities were between 33% and 95%. We did not conduct a meta-analysis because the studies were few and small. Only one study reported the accuracy of CSF t-tau/ABeta ratio.Our findings are based on studies with poor reporting. A significant number of studies had unclear risk of bias for the reference standard, participant selection and flow and timing domains. According to the assessment of index test domain, eight of 15 studies were of poor methodological quality.The accuracy of these CSF biomarkers for 'other dementias' had not been investigated in the included primary studies. Investigation of heterogeneity The main sources of heterogeneity were thought likely to be reference standards used for the target disorders, sources of recruitment, participant sampling, index test methodology and aspects of study quality (particularly, inadequate blinding).We were not able to formally assess the effect of each potential source of heterogeneity as planned, due to the small number of studies available to be included. AUTHORS' CONCLUSIONS: The insufficiency and heterogeneity of research to date primarily leads to a state of uncertainty regarding the value of CSF testing of t-tau, p-tau or p-tau/ABeta ratio for the diagnosis of Alzheimer's disease in current clinical practice. Particular attention should be paid to the risk of misdiagnosis and overdiagnosis of dementia (and therefore over-treatment) in clinical practice. These tests, like other biomarker tests which have been subject to Cochrane DTA reviews, appear to have better sensitivity than specificity and therefore might have greater utility in ruling out Alzheimer's disease as the aetiology to the individual's evident cognitive impairment, as opposed to ruling it in. The heterogeneity observed in the few studies awaiting classification suggests our initial summary will remain valid. However, these tests may have limited clinical value until uncertainties have been addressed. Future studies with more uniformed approaches to thresholds, analysis and study conduct may provide a more homogenous estimate than the one that has been available from the included studies we have identified.

Regional cerebral blood flow single photon emission computed tomography for detection of Frontotemporal dementia in people with suspected dementia.

BACKGROUND: In the UK, dementia affects 5% of the population aged over 65 years and 25% of those over 85 years. Frontotemporal dementia (FTD) represents one subtype and is thought to account for up to 16% of all degenerative dementias. Although the core of the diagnostic process in dementia rests firmly on clinical and cognitive assessments, a wide range of investigations are available to aid diagnosis.Regional cerebral blood flow (rCBF) single-photon emission computed tomography (SPECT) is an established clinical tool that uses an intravenously injected radiolabelled tracer to map blood flow in the brain. In FTD the characteristic pattern seen is hypoperfusion of the frontal and anterior temporal lobes. This pattern of blood flow is different to patterns seen in other subtypes of dementia and so can be used to differentiate FTD.It has been proposed that a diagnosis of FTD, (particularly early stage), should be made not only on the basis of clinical criteria but using a combination of other diagnostic findings, including rCBF SPECT. However, more extensive testing comes at a financial cost, and with a potential risk to patient safety and comfort. OBJECTIVES: To determine the diagnostic accuracy of rCBF SPECT for diagnosing FTD in populations with suspected dementia in secondary/tertiary healthcare settings and in the differential diagnosis of FTD from other dementia subtypes. SEARCH METHODS: Our search strategy used two concepts: (a) the index test and (b) the condition of interest. We searched citation databases, including MEDLINE (Ovid SP), EMBASE (Ovid SP), BIOSIS (Ovid SP), Web of Science Core Collection (ISI Web of Science), PsycINFO (Ovid SP), CINAHL (EBSCOhost) and LILACS (Bireme), using structured search strategies appropriate for each database. In addition we searched specialised sources of diagnostic test accuracy studies and reviews including: MEDION (Universities of Maastricht and Leuven), DARE (Database of Abstracts of Reviews of Effects) and HTA (Health Technology Assessment) database.We requested a search of the Cochrane Register of Diagnostic Test Accuracy Studies and used the related articles feature in PubMed to search for additional studies. We tracked key studies in citation databases such as Science Citation Index and Scopus to ascertain any further relevant studies. We identified 'grey' literature, mainly in the form of conference abstracts, through the Web of Science Core Collection, including Conference Proceedings Citation Index and Embase. The most recent search for this review was run on the 1 June 2013.Following title and abstract screening of the search results, full-text papers were obtained for each potentially eligible study. These papers were then independently evaluated for inclusion or exclusion. SELECTION CRITERIA: We included both case-control and cohort (delayed verification of diagnosis) studies. Where studies used a case-control design we included all participants who had a clinical diagnosis of FTD or other dementia subtype using standard clinical diagnostic criteria. For cohort studies, we included studies where all participants with suspected dementia were administered rCBF SPECT at baseline. We excluded studies of participants from selected populations (e.g. post-stroke) and studies of participants with a secondary cause of cognitive impairment. DATA COLLECTION AND ANALYSIS: Two review authors extracted information on study characteristics and data for the assessment of methodological quality and the investigation of heterogeneity. We assessed the methodological quality of each study using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool. We produced a narrative summary describing numbers of studies that were found to have high/low/unclear risk of bias as well as concerns regarding applicability. To produce 2 x 2 tables, we dichotomised the rCBF SPECT results (scan positive or negative for FTD) and cross-tabulated them against the results for the reference standard. These tables were then used to calculate the sensitivity and specificity of the index test. Meta-analysis was not performed due to the considerable between-study variation in clinical and methodological characteristics. MAIN RESULTS: Eleven studies (1117 participants) met our inclusion criteria. These consisted of six case-control studies, two retrospective cohort studies and three prospective cohort studies. Three studies used single-headed camera SPECT while the remaining eight used multiple-headed camera SPECT. Study design and methods varied widely. Overall, participant selection was not well described and the studies were judged as having either high or unclear risk of bias. Often the threshold used to define a positive SPECT result was not predefined and the results were reported with knowledge of the reference standard. Concerns regarding applicability of the studies to the review question were generally low across all three domains (participant selection, index test and reference standard).Sensitivities and specificities for differentiating FTD from non-FTD ranged from 0.73 to 1.00 and from 0.80 to 1.00, respectively, for the three multiple-headed camera studies. Sensitivities were lower for the two single-headed camera studies; one reported a sensitivity and specificity of 0.40 (95% confidence interval (CI) 0.05 to 0.85) and 0.95 (95% CI 0.90 to 0.98), respectively, and the other a sensitivity and specificity of 0.36 (95% CI 0.24 to 0.50) and 0.92 (95% CI 0.88 to 0.95), respectively.Eight of the 11 studies which used SPECT to differentiate FTD from Alzheimer's disease used multiple-headed camera SPECT. Of these studies, five used a case-control design and reported sensitivities of between 0.52 and 1.00, and specificities of between 0.41 and 0.86. The remaining three studies used a cohort design and reported sensitivities of between 0.73 and 1.00, and specificities of between 0.94 and 1.00. The three studies that used single-headed camera SPECT reported sensitivities of between 0.40 and 0.80, and specificities of between 0.61 and 0.97. AUTHORS' CONCLUSIONS: At present, we would not recommend the routine use of rCBF SPECT in clinical practice because there is insufficient evidence from the available literature to support this.Further research into the use of rCBF SPECT for differentiating FTD from other dementias is required. In particular, protocols should be standardised, study populations should be well described, the threshold for 'abnormal' scans predefined and clear details given on how scans are analysed. More prospective cohort studies that verify the presence or absence of FTD during a period of follow up should be undertaken.

Mini-Cog for the diagnosis of Alzheimer's disease dementia and other dementias within a community setting.

BACKGROUND: Alzheimer's disease and related forms of dementia are becoming increasingly prevalent with the aging of many populations. The diagnosis of Alzheimer's disease relies on tests to evaluate cognition and discriminate between individuals with dementia and those without dementia. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings. OBJECTIVES: The primary objective of this review was to determine the diagnostic accuracy of the Mini-Cog for detecting Alzheimer's disease dementia and related dementias in a community setting.Secondary objectives included investigations of the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity included the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality. Overall, the goals of this review were to determine if the Mini-Cog is a cognitive screening test that could be recommended to screen for cognitive impairment in community settings. SEARCH METHODS: We searched MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (Ovid SP), Science Citation Index (Web of Science), BIOSIS previews (Web of Science), LILACS (BIREME), and the Cochrane Dementia Group's developing register of diagnostic test accuracy studies to March 2013. We used citation tracking (using the database's 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data. SELECTION CRITERIA: We included all cross-sectional studies that utilized the Mini-Cog as an index test for the diagnosis of dementia when compared to a reference standard diagnosis of dementia using standardized dementia diagnostic criteria. For the current review we only included studies that were conducted on samples from community settings, and excluded studies that were conducted in primary care or secondary care settings. We considered studies to be conducted in a community setting where participants were sampled from the general population. DATA COLLECTION AND ANALYSIS: Information from studies meeting the inclusion criteria were extracted including information on the characteristics of participants in the studies. The quality of the studies was assessed using the QUADAS-2 criteria and summarized using risk of bias applicability and summary graphs. We extracted information on the diagnostic test accuracy of studies including the sensitivity, specificity, and 95% confidence intervals of these measures and summarized the findings using forest plots. Study specific sensitivities and specificities were also plotted in receiver operating curve space. MAIN RESULTS: Three studies met the inclusion criteria, with a total of 1620 participants. The sensitivities of the Mini-Cog in the individual studies were reported as 0.99, 0.76 and 0.99. The specificity of the Mini-Cog varied in the individual studies and was 0.93, 0.89 and 0.83. There was clinical and methodological heterogeneity between the studies which precluded a pooled meta-analysis of the results. Methodological limitations were present in all the studies introducing potential sources of bias, specifically with respect to the methods for participant selection. AUTHORS' CONCLUSIONS: There are currently few studies assessing the diagnostic test accuracy of the Mini-Cog in community settings. The limited number of studies and the methodological limitations that are present in the current studies make it difficult to provide recommendations for or against the use of the Mini-Cog as a cognitive screening test in community settings. Additional well-designed studies comparing the Mini-Cog to other brief cognitive screening tests are required in order to determine the accuracy and utility of the Mini-Cog in community based settings.

Mini-Mental State Examination (MMSE) for the detection of Alzheimer's disease and other dementias in people with mild cognitive impairment (MCI).

BACKGROUND: Dementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people with mild cognitive impairment (MCI) will progress to dementia but others remain stable or recover full function. There is great interest in finding good predictors of dementia in people with MCI. The Mini-Mental State Examination (MMSE) is the best-known and the most often used short screening tool for providing an overall measure of cognitive impairment in clinical, research and community settings. OBJECTIVES: To determine the diagnostic accuracy of the MMSE at various thresholds for detecting individuals with baseline MCI who would clinically convert to dementia in general, Alzheimer's disease dementia or other forms of dementia at follow-up. SEARCH METHODS: We searched ALOIS (Cochrane Dementia and Cognitive Improvement Specialized Register of diagnostic and intervention studies (inception to May 2014); MEDLINE (OvidSP) (1946 to May 2014); EMBASE (OvidSP) (1980 to May 2014); BIOSIS (Web of Science) (inception to May 2014); Web of Science Core Collection, including the Conference Proceedings Citation Index (ISI Web of Science) (inception to May 2014); PsycINFO (OvidSP) (inception to May 2014), and LILACS (BIREME) (1982 to May 2014). We also searched specialized sources of diagnostic test accuracy studies and reviews, most recently in May 2014: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). No language or date restrictions were applied to the electronic searches and methodological filters were not used as a method to restrict the search overall so as to maximize sensitivity. We also checked reference lists of relevant studies and reviews, tracked citations in Scopus and Science Citation Index, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on MMSE for dementia diagnosis to try to locate possibly relevant but unpublished data. SELECTION CRITERIA: We considered longitudinal studies in which results of the MMSE administered to MCI participants at baseline were obtained and the reference standard was obtained by follow-up over time. We included participants recruited and clinically classified as individuals with MCI under Petersen and revised Petersen criteria, Matthews criteria, or a Clinical Dementia Rating = 0.5. We used acceptable and commonly used reference standards for dementia in general, Alzheimer's dementia, Lewy body dementia, vascular dementia and frontotemporal dementia. DATA COLLECTION AND ANALYSIS: We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. We assessed the identified full papers for eligibility and extracted data to create two by two tables for dementia in general and other dementias. Two authors independently performed quality assessment using the QUADAS-2 tool. Due to high heterogeneity and scarcity of data, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic curve. MAIN RESULTS: In this review, we included 11 heterogeneous studies with a total number of 1569 MCI patients followed for conversion to dementia. Four studies assessed the role of baseline scores of the MMSE in conversion from MCI to all-cause dementia and eight studies assessed this test in conversion from MCI to Alzheimer´s disease dementia. Only one study provided information about the MMSE and conversion from MCI to vascular dementia. For conversion from MCI to dementia in general, the accuracy of baseline MMSE scores ranged from sensitivities of 23% to 76% and specificities from 40% to 94%. In relationship to conversion from MCI to Alzheimer's disease dementia, the accuracy of baseline MMSE scores ranged from sensitivities of 27% to 89% and specificities from 32% to 90%. Only one study provided information about conversion from MCI to vascular dementia, presenting a sensitivity of 36% and a specificity of 80% with an incidence of vascular dementia of 6.2%. Although we had planned to explore possible sources of heterogeneity, this was not undertaken due to the scarcity of studies included in our analysis. AUTHORS' CONCLUSIONS: Our review did not find evidence supporting a substantial role of MMSE as a stand-alone single-administration test in the identification of MCI patients who could develop dementia. Clinicians could prefer to request additional and extensive tests to be sure about the management of these patients. An important aspect to assess in future updates is if conversion to dementia from MCI stages could be predicted better by MMSE changes over time instead of single measurements. It is also important to assess if a set of tests, rather than an isolated one, may be more successful in predicting conversion from MCI to dementia.

¹8F-FDG PET for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

BACKGROUND: ¹8F-FDFG uptake by brain tissue as measured by positron emission tomography (PET) is a well-established method for assessment of brain function in people with dementia. Certain findings on brain PET scans can potentially predict the decline of mild cognitive Impairment (MCI) to Alzheimer's disease dementia or other dementias. OBJECTIVES: To determine the diagnostic accuracy of the ¹8F-FDG PET index test for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease dementia or other forms of dementia at follow-up. SEARCH METHODS: We searched the Cochrane Register of Diagnostic Test Accuracy Studies, MEDLINE, EMBASE, Science Citation Index, PsycINFO, BIOSIS previews, LILACS, MEDION, (Meta-analyses van Diagnostisch Onderzoek), DARE (Database of Abstracts of Reviews of Effects), HTA (Health Technology Assessment Database), ARIF (Aggressive Research Intelligence Facility) and C-EBLM (International Federation of Clinical Chemistry and Laboratory Medicine Committee for Evidence-based Laboratory Medicine) databases to January 2013. We checked the reference lists of any relevant studies and systematic reviews for additional studies. SELECTION CRITERIA: We included studies that evaluated the diagnostic accuracy of ¹8F-FDG PET to determine the conversion from MCI to Alzheimer's disease dementia or to other forms of dementia, i.e. any or all of vascular dementia, dementia with Lewy bodies, and fronto-temporal dementia. These studies necessarily employ delayed verification of conversion to dementia and are sometimes labelled as 'delayed verification cross-sectional studies'. DATA COLLECTION AND ANALYSIS: Two blinded review authors independently extracted data, resolving disagreement by discussion, with the option to involve a third review author as arbiter if necessary. We extracted and summarised graphically the data for two-by-two tables. We conducted exploratory analyses by plotting estimates of sensitivity and specificity from each study on forest plots and in receiver operating characteristic (ROC) space. When studies had mixed thresholds, we derived estimates of sensitivity and likelihood ratios at fixed values (lower quartile, median and upper quartile) of specificity from the hierarchical summary ROC (HSROC) models. MAIN RESULTS: We included 14 studies (421 participants) in the analysis. The sensitivities for conversion from MCI to Alzheimer's disease dementia were between 25% and 100% while the specificities were between 15% and 100%. From the summary ROC curve we fitted we estimated that the sensitivity was 76% (95% confidence interval (CI): 53.8 to 89.7) at the included study median specificity of 82%. This equates to a positive likelihood ratio of 4.03 (95% CI: 2.97 to 5.47), and a negative likelihood ratio of 0.34 (95% CI: 0.15 to 0.75). Three studies recruited participants from the same Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort but only the largest ADNI study (Herholz 2011) is included in the meta-analysis. In order to demonstrate whether the choice of ADNI study or discriminating brain region (Chételat 2003) or reader assessment (Pardo 2010) make a difference to the pooled estimate, we performed five additional analyses. At the median specificity of 82%, the estimated sensitivity was between 74% and 76%. There was no impact on our findings. In addition to evaluating Alzheimer's disease dementia, five studies evaluated the accuracy of ¹8F-FDG PET for all types of dementia. The sensitivities were between 46% and 95% while the specificities were between 29% and 100%; however, we did not conduct a meta-analysis because of too few studies, and those studies which we had found recruited small numbers of participants. Our findings are based on studies with poor reporting, and the majority of included studies had an unclear risk of bias, mainly for the reference standard and participant selection domains. According to the assessment of Index test domain, more than 50% of studies were of poor methodological quality. AUTHORS' CONCLUSIONS: It is difficult to determine to what extent the findings from the meta-analysis can be applied to clinical practice. Given the considerable variability of specificity values and lack of defined thresholds for determination of test positivity in the included studies, the current evidence does not support the routine use of ¹8F-FDG PET scans in clinical practice in people with MCI. The ¹8F-FDG PET scan is a high-cost investigation, and it is therefore important to clearly demonstrate its accuracy and to standardise the process of ¹8F-FDG PET diagnostic modality prior to its being widely used. Future studies with more uniform approaches to thresholds, analysis and study conduct may provide a more homogeneous estimate than the one available from the included studies we have identified.

(11)C-PIB-PET for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

BACKGROUND: According to the latest revised National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (now known as the Alzheimer's Association) (NINCDS-ADRDA) diagnostic criteria for Alzheimer's disease dementia, the confidence in diagnosing mild cognitive impairment (MCI) due to Alzheimer's disease dementia is raised with the application of imaging biomarkers. These tests, added to core clinical criteria, might increase the sensitivity or specificity of a testing strategy. However, the accuracy of biomarkers in the diagnosis of Alzheimer's disease dementia and other dementias has not yet been systematically evaluated. A formal systematic evaluation of the sensitivity, specificity, and other properties of positron emission tomography (PET) imaging with the (11)C-labelled Pittsburgh Compound-B ((11)C-PIB) ligand was performed. OBJECTIVES: To determine the diagnostic accuracy of the (11)C- PIB-PET scan for detecting participants with MCI at baseline who will clinically convert to Alzheimer's disease dementia or other forms of dementia over a period of time. SEARCH METHODS: The most recent search for this review was performed on 12 January 2013. We searched MEDLINE (OvidSP), EMBASE (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science and Conference Proceedings (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We also requested a search of the Cochrane Register of Diagnostic Test Accuracy Studies (managed by the Cochrane Renal Group).No language or date restrictions were applied to the electronic searches and methodological filters were not used so as to maximise sensitivity. SELECTION CRITERIA: We selected studies that had prospectively defined cohorts with any accepted definition of MCI with baseline (11)C-PIB-PET scan. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis for example NINCDS-ADRDA or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria. DATA COLLECTION AND ANALYSIS: We screened all titles generated by electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. The identified full papers were assessed for eligibility and data were extracted to create two by two tables. Two independent assessors performed quality assessment using the QUADAS 2 tool. We used the hierarchical summary receiver operating characteristic (ROC) model to produce a summary ROC curve. MAIN RESULTS: Conversion from MCI to Alzheimer's disease dementia was evaluated in nine studies. The quality of the evidence was limited. Of the 274 participants included in the meta-analysis, 112 developed Alzheimer's dementia. Based on the nine included studies, the median proportion converting was 34%. The studies varied markedly in how the PIB scans were done and interpreted.The sensitivities were between 83% and 100% while the specificities were between 46% and 88%. Because of the variation in thresholds and measures of (11)C-PIB amyloid retention, we did not calculate summary sensitivity and specificity. Although subject to considerable uncertainty, to illustrate the potential strengths and weaknesses of (11)C-PIB-PET scans we estimated from the fitted summary ROC curve that the sensitivity was 96% (95% confidence interval (CI) 87 to 99) at the included study median specificity of 58%. This equated to a positive likelihood ratio of 2.3 and a negative likelihood ratio of 0.07. Assuming a typical conversion rate of MCI to Alzheimer's dementia of 34%, for every 100 PIB scans one person with a negative scan would progress and 28 with a positive scan would not actually progress to Alzheimer's dementia.There were limited data for formal investigation of heterogeneity. We performed two sensitivity analyses to assess the influence of type of reference standard and the use of a pre-specified threshold. There was no effect on our findings. AUTHORS' CONCLUSIONS: Although the good sensitivity achieved in some included studies is promising for the value of (11)C-PIB-PET, given the heterogeneity in the conduct and interpretation of the test and the lack of defined thresholds for determination of test positivity, we cannot recommend its routine use in clinical practice.(11)C-PIB-PET biomarker is a high cost investigation, therefore it is important to clearly demonstrate its accuracy and standardise the process of the (11)C-PIB diagnostic modality prior to it being widely used.

Reporting standards for studies of diagnostic test accuracy in dementia: The STARDdem Initiative.

OBJECTIVE: To provide guidance on standards for reporting studies of diagnostic test accuracy for dementia disorders. METHODS: An international consensus process on reporting standards in dementia and cognitive impairment (STARDdem) was established, focusing on studies presenting data from which sensitivity and specificity were reported or could be derived. A working group led the initiative through 4 rounds of consensus work, using a modified Delphi process and culminating in a face-to-face consensus meeting in October 2012. The aim of this process was to agree on how best to supplement the generic standards of the STARD statement to enhance their utility and encourage their use in dementia research. RESULTS: More than 200 comments were received during the wider consultation rounds. The areas at most risk of inadequate reporting were identified and a set of dementia-specific recommendations to supplement the STARD guidance were developed, including better reporting of patient selection, the reference standard used, avoidance of circularity, and reporting of test-retest reliability. CONCLUSION: STARDdem is an implementation of the STARD statement in which the original checklist is elaborated and supplemented with guidance pertinent to studies of cognitive disorders. Its adoption is expected to increase transparency, enable more effective evaluation of diagnostic tests in Alzheimer disease and dementia, contribute to greater adherence to methodologic standards, and advance the development of Alzheimer biomarkers.

Plasma and cerebrospinal fluid amyloid beta for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

BACKGROUND: According to the latest revised National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (now known as the Alzheimer's Association) (NINCDS-ADRDA) diagnostic criteria for Alzheimer's disease dementia of the National Institute on Aging and Alzheimer Association, the confidence in diagnosing mild cognitive impairment (MCI) due to Alzheimer's disease dementia is raised with the application of biomarkers based on measures in the cerebrospinal fluid (CSF) or imaging. These tests, added to core clinical criteria, might increase the sensitivity or specificity of a testing strategy. However, the accuracy of biomarkers in the diagnosis of Alzheimer's disease dementia and other dementias has not yet been systematically evaluated. A formal systematic evaluation of sensitivity, specificity, and other properties of plasma and CSF amyloid beta (Aß) biomarkers was performed. OBJECTIVES: To determine the accuracy of plasma and CSF Aß levels for detecting those patients with MCI who would convert to Alzheimer's disease dementia or other forms of dementia over time. SEARCH METHODS: The most recent search for this review was performed on 3 December 2012. We searched MEDLINE (OvidSP), EMBASE (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science and Conference Proceedings (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We also requested a search of the Cochrane Register of Diagnostic Test Accuracy Studies (managed by the Cochrane Renal Group).No language or date restrictions were applied to the electronic searches and methodological filters were not used so as to maximise sensitivity. SELECTION CRITERIA: We selected those studies that had prospectively well defined cohorts with any accepted definition of cognitive decline, but no dementia, with baseline CSF or plasma Aß levels, or both, documented at or around the time the above diagnoses were made. We also included studies which looked at data from those cohorts retrospectively, and which contained sufficient data to construct two by two tables expressing plasma and CSF Aß biomarker results by disease status. Moreover, studies were only selected if they applied a reference standard for Alzheimer's dementia diagnosis, for example the NINCDS-ADRDA or Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. DATA COLLECTION AND ANALYSIS: We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. We assessed the identified full papers for eligibility and extracted data to create standard two by two tables. Two independent assessors performed quality assessment using the QUADAS-2 tool. Where data allowed, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic (ROC) curve. MAIN RESULTS: Alzheimer's disease dementia was evaluated in 14 studies using CSF Aß42. Of the 1349 participants included in the meta-analysis, 436 developed Alzheimer's dementia. Individual study estimates of sensitivity were between 36% and 100% while the specificities were between 29% and 91%. Because of the variation in assay thresholds, we did not estimate summary sensitivity and specificity. However, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary ROC curve. At the median specificity of 64%, the sensitivity was 81% (95% CI 72 to 87). This equated to a positive likelihood ratio (LR+) of 2.22 (95% CI 2.00 to 2.47) and a negative likelihood ratio (LR-) of 0.31 (95% CI 0.21 to 0.48).The accuracy of CSF Aß42 for all forms of dementia was evaluated in four studies. Of the 464 participants examined, 188 developed a form of dementia (Alzheimer's disease and other forms of dementia).The thresholds used were between 209 mg/ml and 512 ng/ml. The sensitivities were between 56% and 75% while the specificities were between 47% and 76%. At the median specificity of 75%, the sensitivity was estimated to be 63% (95% CI 22 to 91) from the meta-analytic model. This equated to a LR+ of 2.51 (95% CI 1.30 to 4.86) and a LR- of 0.50 (95% CI 0.16 to 1.51).The accuracy of CSF Aß42 for non-Alzheimer's disease dementia was evaluated in three studies. Of the 385 participants examined, 61 developed non-Alzheimer's disease dementia. Since there were very few studies and considerable variation between studies, the results were not meta-analysed. The sensitivities were between 8% and 63% while the specificities were between 35% and 67%.Only one study examined the accuracy of plasma Aß42 and the plasma Aß42/Aß40 ratio for Alzheimer's disease dementia. The sensitivity of 86% (95% CI 81 to 90) was the same for both tests while the specificities were 50% (95% CI 44 to 55) and 70% (95% CI 64 to 75) for plasma Aß42 and the plasma Aß42/Aß40 ratio respectively. Of the 565 participants examined, 245 developed Alzheimer's dementia and 87 non-Alzheimer's disease dementia.There was substantial heterogeneity between studies. The accuracy of Aß42 for the diagnosis of Alzheimer's disease dementia did not differ significantly (P = 0.8) between studies that pre-specified the threshold for determining test positivity (n = 6) and those that only determined the threshold at follow-up (n = 8). One study excluded a sample of MCI non-Alzheimer's disease dementia converters from their analysis. In sensitivity analyses, the exclusion of this study had no impact on our findings. The exclusion of eight studies (950 patients) that were considered at high (n = 3) or unclear (n = 5) risk of bias for the patient selection domain also made no difference to our findings. AUTHORS' CONCLUSIONS: The proposed diagnostic criteria for prodromal dementia and MCI due to Alzheimer's disease, although still being debated, would be fulfilled where there is both core clinical and cognitive criteria and a single biomarker abnormality. From our review, the measure of abnormally low CSF Aß levels has very little diagnostic benefit with likelihood ratios suggesting only marginal clinical utility. The quality of reports was also poor, and thresholds and length of follow-up were inconsistent. We conclude that when applied to a population of patients with MCI, CSF Aß levels cannot be recommended as an accurate test for Alzheimer's disease.

Group-based parent training programmes for improving parental psychosocial health.

BACKGROUND: Parental psychosocial health can have a significant effect on the parent-child relationship, with consequences for the later psychological health of the child. Parenting programmes have been shown to have an impact on the emotional and behavioural adjustment of children, but there have been no reviews to date of their impact on parental psychosocial wellbeing. OBJECTIVES: To address whether group-based parenting programmes are effective in improving parental psychosocial wellbeing (for example, anxiety, depression, guilt, confidence). SEARCH METHODS: We searched the following databases on 5 December 2011: CENTRAL (2011, Issue 4), MEDLINE (1950 to November 2011), EMBASE (1980 to week 48, 2011), BIOSIS (1970 to 2 December 2011), CINAHL (1982 to November 2011), PsycINFO (1970 to November week 5, 2011), ERIC (1966 to November 2011), Sociological Abstracts (1952 to November 2011), Social Science Citation Index (1970 to 2 December 2011), metaRegister of Controlled Trials (5 December 2011), NSPCC Library (5 December 2011). We searched ASSIA (1980 to current) on 10 November 2012 and the National Research Register was last searched in 2005. SELECTION CRITERIA: We included randomised controlled trials that compared a group-based parenting programme with a control condition and used at least one standardised measure of parental psychosocial health. Control conditions could be waiting-list, no treatment, treatment as usual or a placebo. DATA COLLECTION AND ANALYSIS: At least two review authors extracted data independently and assessed the risk of bias in each study. We examined the studies for any information on adverse effects. We contacted authors where information was missing from trial reports. We standardised the treatment effect for each outcome in each study by dividing the mean difference in post-intervention scores between the intervention and control groups by the pooled standard deviation. MAIN RESULTS: We included 48 studies that involved 4937 participants and covered three types of programme: behavioural, cognitive-behavioural and multimodal. Overall, we found that group-based parenting programmes led to statistically significant short-term improvements in depression (standardised mean difference (SMD) -0.17, 95% confidence interval (CI) -0.28 to -0.07), anxiety (SMD -0.22, 95% CI -0.43 to -0.01), stress (SMD -0.29, 95% CI -0.42 to -0.15), anger (SMD -0.60, 95% CI -1.00 to -0.20), guilt (SMD -0.79, 95% CI -1.18 to -0.41), confidence (SMD -0.34, 95% CI -0.51 to -0.17) and satisfaction with the partner relationship (SMD -0.28, 95% CI -0.47 to -0.09). However, only stress and confidence continued to be statistically significant at six month follow-up, and none were significant at one year. There was no evidence of any effect on self-esteem (SMD -0.01, 95% CI -0.45 to 0.42). None of the trials reported on aggression or adverse effects.The limited data that explicitly focused on outcomes for fathers showed a statistically significant short-term improvement in paternal stress (SMD -0.43, 95% CI -0.79 to -0.06). We were unable to combine data for other outcomes and individual study results were inconclusive in terms of any effect on depressive symptoms, confidence or partner satisfaction. AUTHORS' CONCLUSIONS: The findings of this review support the use of parenting programmes to improve the short-term psychosocial wellbeing of parents. Further input may be required to ensure that these results are maintained. More research is needed that explicitly addresses the benefits for fathers, and that examines the comparative effectiveness of different types of programme along with the mechanisms by which such programmes bring about improvements in parental psychosocial functioning.

Neuropsychological tests for the diagnosis of Alzheimer's disease dementia and other dementias: a generic protocol for cross-sectional and delayed-verification studies.

This is the protocol for a review and there is no abstract. The objectives are as follows: To determine the cross-sectional diagnostic accuracy of [index test] at various thresholds for ADD and other dementias [target condition] in [target population].ORTo determine the accuracy of [index test] at various thresholds for diagnosing ADD and other dementias [target condition] in [target population] after a follow-up period (delayed-verification studies).To investigate the heterogeneity of test accuracy in the included studies.To highlight the quality and quantity of research evidence available on the effectiveness of the index test in the target population.To identify gaps in the evidence and determine where further research is required.