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The Cochrane Database of Systematic... Mar 2015Dementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people... (Review)
Review
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.
Topics: Alzheimer Disease; Cognitive Dysfunction; Dementia; Dementia, Vascular; Disease Progression; Frontotemporal Dementia; Humans; Lewy Body Disease; Mental Status Schedule; Neuropsychological Tests; Sensitivity and Specificity
PubMed: 25740785
DOI: 10.1002/14651858.CD010783.pub2 -
The Cochrane Database of Systematic... Jan 2015¹⁸F-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... (Meta-Analysis)
Meta-Analysis Review
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.
Topics: Aged; Alzheimer Disease; Brain; Cognitive Dysfunction; Dementia; Disease Progression; Early Diagnosis; Fluorodeoxyglucose F18; Humans; Middle Aged; Positron-Emission Tomography; Radiopharmaceuticals; Sensitivity and Specificity
PubMed: 25629415
DOI: 10.1002/14651858.CD010632.pub2 -
BMC Cancer Nov 2014We sought to determine the comparative diagnostic performance of standard b-value (800-1000 s/mm2) versus low b-value (400-500 s/mm2) diffusion-weighted magnetic... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
We sought to determine the comparative diagnostic performance of standard b-value (800-1000 s/mm2) versus low b-value (400-500 s/mm2) diffusion-weighted magnetic resonance imaging (DW-MRI) in the detection of renal cell carcinoma (RCC).
METHOD
After a systematic review of the available literature, studies were included that reported b-values, used a histopathological reference standard, and allowed construction of 2 × 2 contingency tables for detection of RCC lesions using DW-MRI. In addition, a summary receiver operating characteristic (SROC) analysis was performed.
RESULTS
Four articles that complied with all inclusion and exclusion criteria were selected for data extraction and analysis (n = 248 lesions in 266 patients). All four studies were high quality. Standard b-value DW-MRI displayed a pooled sensitivity of 0.59 (95% confidence interval (CI): 0.51-0.67) and a pooled specificity of 0.50 (95% CI: 0.30-0.70), while low b-value DW-MRI displayed a pooled sensitivity of 0.58 (95% CI: 0.48-0.63) and a pooled specificity of 0.23 (95% CI: 0.09-0.44). The SROC curve of standard b-value DW-MRI displayed an AUC of 0.61 and a Q*index of 0.59, while the SROC curve of low b-value DW-MRI displayed an AUC of 0.68 and a Q*index of 0.64.
CONCLUSION
Standard b-value DW-MRI showed a superior specificity but an approximately equivalent sensitivity to low b-value DW-MRI in detecting RCC lesions in the kidney. However, low b-value DW-MRI displayed an overall superior diagnostic accuracy over standard b-value DW-MRI.
Topics: Carcinoma, Renal Cell; Databases, Bibliographic; Diffusion Magnetic Resonance Imaging; Humans; Kidney Neoplasms; ROC Curve; Sensitivity and Specificity
PubMed: 25406910
DOI: 10.1186/1471-2407-14-843 -
The Cochrane Database of Systematic... Sep 2014Intracranial vascular malformations (brain or pial/dural arteriovenous malformations/fistulae, and aneurysms) are the leading cause of intracerebral haemorrhage (ICH) in... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Intracranial vascular malformations (brain or pial/dural arteriovenous malformations/fistulae, and aneurysms) are the leading cause of intracerebral haemorrhage (ICH) in young adults. Early identification of the intracranial vascular malformation may improve outcome if treatment can prevent ICH recurrence. Catheter intra-arterial digital subtraction angiography (IADSA) is considered the reference standard for the detection an intracranial vascular malformation as the cause of ICH. Computed tomography angiography (CTA) and magnetic resonance angiography (MRA) are less invasive than IADSA and may be as accurate for identifying some causes of ICH.
OBJECTIVES
To evaluate the diagnostic test accuracy of CTA and MRA versus IADSA for the detection of intracranial vascular malformations as a cause of ICH.
SEARCH METHODS
We searched MEDLINE (1948 to August 2013), EMBASE (1980 to August 2013), MEDION (August 2013), the Database of Abstracts of Reviews of Effects (DARE; August 2013), the Health Technology Assessment Database (HTA; August 2013), ClinicalTrials.gov (August 2013), and WHO ICTRP (International Clinical Trials Register Portfolio; August 2013). We also performed a cited reference search for forward tracking of relevant articles on Google Scholar (http://scholar.google.com/), screened bibliographies, and contacted authors to identify additional studies.
SELECTION CRITERIA
We selected studies reporting data that could be used to construct contingency tables that compared CTA or MRA, or both, with IADSA in the same patients for the detection of intracranial vascular malformations following ICH.
DATA COLLECTION AND ANALYSIS
Two authors (CBJ and RA-SS) independently extracted data on study characteristics and measures of test accuracy. Two authors (CBJ and PMW) independently extracted data on test characteristics. We obtained data restricted to the subgroup undergoing IADSA in studies using multiple reference standards. We combined data using the bivariate model. We generated forest plots of the sensitivity and specificity of CTA and MRA and created a summary receiver operating characteristic plot.
MAIN RESULTS
Eleven studies (n = 927 participants) met our inclusion criteria. Eight studies compared CTA with IADSA (n = 526) and three studies compared MRA with IADSA (n = 401). Methodological quality varied considerably among studies, with partial verification bias in 7/11 (64%) and retrospective designs in 5/10 (50%). In studies of CTA, the pooled estimate of sensitivity was 0.95 (95% confidence interval (CI) 0.90 to 0.97) and specificity was 0.99 (95% CI 0.95 to 1.00). The results remained robust in a sensitivity analysis in which only studies evaluating adult patients (≥ 16 years of age) were included. In studies of MRA, the pooled estimate of sensitivity was 0.98 (95% CI 0.80 to 1.00) and specificity was 0.99 (95% CI 0.97 to 1.00). An indirect comparison of CTA and MRA using a bivariate model incorporating test type as one of the parameters failed to reveal a statistically significant difference in sensitivity or specificity between the two imaging modalities (P value = 0.6).
AUTHORS' CONCLUSIONS
CTA and MRA appear to have good sensitivity and specificity following ICH for the detection of intracranial vascular malformations, although several of the included studies had methodological shortcomings (retrospective designs and partial verification bias in particular) that may have increased apparent test accuracy.
Topics: Adolescent; Adult; Cerebral Angiography; Cerebral Hemorrhage; Female; Humans; Intracranial Arteriovenous Malformations; Magnetic Resonance Angiography; Male; Middle Aged; Randomized Controlled Trials as Topic; Sensitivity and Specificity; Tomography, X-Ray Computed
PubMed: 25177839
DOI: 10.1002/14651858.CD009372.pub2 -
The Cochrane Database of Systematic... Jul 2014According to the latest revised National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association... (Meta-Analysis)
Meta-Analysis Review
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.
Topics: Aged; Alzheimer Disease; Aniline Compounds; Carbon Radioisotopes; Cognitive Dysfunction; Dementia; Disease Progression; Early Diagnosis; Humans; Positron-Emission Tomography; Prospective Studies; Sensitivity and Specificity; Thiazoles
PubMed: 25052054
DOI: 10.1002/14651858.CD010386.pub2