Coverage Policy Manual
Policy #: 2009004
Category: Laboratory
Initiated: February 2009
Last Review: September 2018
  Biochemical Marker's, Alzheimer's Disease

Alzheimer’s disease (AD) is invariably diagnosed clinically, focusing on the exclusion of other causes of dementia. In 1984, the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer’s and Related Disorders Association (ADRDA) developed clinical criteria for the diagnosis of AD (Mckhann et al, 1984).  Three categories were defined: possible, probable, and definite AD. The diagnosis of definite AD requires a brain biopsy confirming the presence of characteristic neurofibrillary tangles. While definite AD is almost always diagnosed by autopsy, in approximately 85% of those with a diagnosis of probable AD, pathological findings are found to be consistent. The diagnostic categories are defined as follows:
Possible Alzheimer’s Disease
Clinical diagnosis of possible AD:
    • May be made on the basis of the dementia syndrome in the absence of other neurological, psychiatric, or systemic disorders sufficient to cause dementia, and in the presence of variations in the onset, the presentation, or the clinical course
    • May be made in the presence of a second systemic or brain disorder sufficient to produce dementia, which is not considered to be the cause of the dementia
    • Should be used in research studies when a single gradually progressive severe cognitive deficit is identified in the absence of other identifiable cause.
Probable Alzheimer’s Disease
The criteria for the clinical diagnosis of probable AD include:
    • Dementia, established by clinical examination and documented by the Mini-Mental State Examination, the Blessed Dementia Scale, or some similar examination and confirmed by neuropsychological tests
    • Should be used in research studies when a single gradually progressive severe cognitive deficit is identified in the absence of other identifiable cause.
    • Progressive worsening of memory and other cognitive functions
    • No disturbance of consciousness
    • Onset between ages 40 and 90, most often after the age of 65
    • Absence of systemic disorders or other brain diseases that in and of themselves could account for the progressive deficits in memory and cognition.
The diagnosis of probable AD is supported by:
    • Progressive deterioration of specific cognitive functions such as language (aphasia), motor skills (apraxia), and perception (agnosia)
    • Impaired activities of daily living and altered patterns of behavior
    • Family history of similar disorders, particularly if confirmed neuropathologically
    • Laboratory results: normal lumbar puncture as evaluated by standard techniques, normal pattern or nonspecific changes in the electroencephalogram (EEG), and evidence of cerebral atrophy on computed tomography (CT) scanning with progression documented by serial observation.
Other clinical features consistent with the diagnosis of probable AD, after exclusion of causes of dementia other than AD, include
    • Plateaus in the course of progression of the illness;
    • Associated symptoms of depression, insomnia, incontinence, delusions, illusions, hallucinations, sexual disorders, weight loss, and catastrophic verbal, emotional, or physical outbursts;
    • Other neurologic abnormalities in some patients, especially with more advanced disease and including motor signs such as increased muscle tone, myoclonus, or gait disorder;
    • Seizures in advanced disease CT normal for age
Features that make the diagnosis of probable AD uncertain or unlikely include:
    • Seizures in advanced disease CT normal for age
    • Focal neurological findings such as hemiparesis, sensory loss, visual field deficits, and incoordination early in the course of the illness
    • Seizures or gait disturbances at the onset or very early in the course of the illness
Definite Alzheimer’s Disease
Criteria for diagnosis of definite AD are:
    • Clinical criteria for probable Alzheimer’s disease AND
    • Histopathologic evidence obtained from a biopsy or autopsy
Accompanying advances defining the AD phenotype and pathophysiology “research criteria for the diagnosis of Alzheimer’s disease” have been recently proposed including clinical features, neuroimaging, genetic markers, and biomarkers Dubois et al, 2007).  However, existing evidence and current practice relies on the NINCDS/ADRDA classifications.
Because diagnosis of AD can be difficult for both physicians, patients, and families there has been considerable interest in identifying an accurate laboratory test for AD—particularly for use early in the course of disease. Abnormal cerebrospinal fluid (CSF) levels of the tau protein (phosphorylated [P-tau] or with a threonine moiety [T-tau]) or an amyloid beta (AB) peptide such as AB-42 have been found in patients with AD. Other potential CSF AND SERUM (Zhang, 2014),  peptide markers have also been explored. (Galasko et al, 1997) (Motter et al, 1995)  The tau protein is a microtubule-associated molecule that is found in the neurofibrillary tangles that are typical of AD. This protein is thought to be related to degenerating and dying neurons, and high levels of tau proteins in the CSF have been associated with AD. AB-42 is a subtype of amyloid beta peptide that is produced following the metabolism of amyloid precursor protein. AB-42 is the key peptide deposited in the amyloid plaques characteristic of AD. Low levels of AB-42 in the CSF have been associated with AD, perhaps because AB-42 is deposited in amyloid plaques instead of remaining in solution. Finally, investigators have suggested the Tau/AB-42 ratio a potentially more accurate diagnostic marker than either alone (Maddalena et al, 2003).  
Neural thread protein is associated with the neurofibrillary tangles of AD. Both CSF and urine levels of this protein have been investigated as a potential marker of AD. Urine and CSF tests for neural thread protein may be referred to as the AD7C™ test.
Regulatory Status
No biochemical marker tests for Alzheimer disease are currently approved by the U.S. Food and Drug Administration (FDA). Commercially available tests include:
  • AlzheimAlert™ (Nymox Pharmaceutical Corporation; Hasbrouck Heights, NJ)
  • Innotest® assays for T-tau, P-tau, and AB-42 (Fujirebio [previously Innogenetics]; Malvern, Pennsylvania)
  • AdMark® CSF analysis
These are laboratory-developed tests. Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests (LDTs) must meet the general regulatory standards of the Clinical Laboratory Improvement Act (CLIA). AlzheimAlert™ and AdMark® CSF analysis are available under the auspices of CLIA. Laboratories that offer LDTs must be licensed by CLIA for highcomplexity testing. To date, FDA has chosen not to require any regulatory review of these tests.
Nymox Pharmaceutical Corporation previously offered AD7C testing as an LDT but no longer lists the test on its web site.
There are no specific CPT codes for this testing.
CPT code 83520 (Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative; not otherwise specified) may be used to report testing for tau protein and amyloid beta peptides.
An example of this testing is the ADmark® CSF Analysis, which tests for phosphorylated-tau protein, total-tau protein, and AB42 peptide in CSF. A laboratory website lists this test as being reported with 3 units of code 83520.
There are no specific codes used for testing for neural thread protein.
An example of this testing is the AlzheimAlert™ test by Nymox Pharmaceutical Corporation. They list on their website that the test is reported with the unlisted urinalysis code 81099 when performed in urine and the unlisted immunology code 86849 when performed in CSF.
Genetic testing for AD has also been investigated and is considered separately in policy No. 1998137.

Measurement of cerebrospinal fluid or urinary biomarkers of Alzheimer's disease, including but not limited to tau protein, amyloid beta peptides, or neural thread proteins does not meet Primary Coverage Criteria that there be scientific evidence of effectiveness in improving health outcomes.
For contracts without Primary Coverage Criteria, measurement of cerebrospinal fluid or urinary biomarkers of Alzheimer's disease, including but not limited to tau protein, amyloid beta peptides, or neural thread proteins is investigational.  Investigational services are an exclusion in the member certificate of coverage.

The purposes of testing for AD-related biomarkers are to:
    • improve diagnostic accuracy or
    • predict conversion from mild cognitive impairment (MCI) to AD.
Evidence of health benefit, or clinical utility, following from testing requires demonstrating:
    • incremental improvement in diagnostic or prognostic accuracy over current practice, and
    • that incremental improvements lead to improved health outcomes (e.g., by informing clinical management decisions), and
    • generalizability.
A framework for evaluating evidence of health benefit requires considering the following: appropriate reference standard, requirements for predicting conversion from MCI to AD, how improved diagnostic accuracy or predicting conversion would lead to improved health outcomes, appropriate data analysis including assay cutoffs for assays, sample composition (inclusion and exclusion criteria), and validation of accuracy or prediction in independent samples as evidence of generalizability.
Referent Standard. The accuracy of clinical AD diagnostic criteria has been established by comparison to autopsy or the gold standard. Therefore, the gold standard must be employed to accurately assess incremental diagnostic improvement.
Predicting Conversion from MCI to AD. Predicting conversion from MCI to AD may rely on a clinical diagnosis, albeit with some attendant error and misclassification, because the prediction of interest is conversion and not the gold standard diagnosis.
Incremental Diagnostic Improvement. Incremental diagnostic or prognostic improvement is best demonstrated through evidence that the proposed predictor can correctly reclassify individuals with and without AD, or those with MCI who will and will not progress to AD (Pencina et al, 2008).  Alternative approaches such as classical ROC analyses, while providing some insight, do not allow directly translating improvements in diagnostic or prognostic accuracy to changes in health outcomes (Vickers, 2008).
Improved Health Outcomes (Clinical Utility). Although not without controversy because of modest efficacy, cholinesterase inhibitors are used to treat mild-to-moderate Alzheimer’s disease (Kaduszkiewicz et al, 2005). Memantine, a NMDA receptor antagonist, appears to provide a small benefit in those with moderate-to-advanced disease  (McShane et al, 2006).  Given available therapies, in principle more accurate diagnosis might allow targeting treatment to those most likely to benefit. However, clinical trial entry criteria and benefit have been based on clinical diagnosis. While the possibility that more accurate diagnosis might lead to improved outcomes is plausible, it is not based on current evidence. Pharmacologic interventions for MCI have not demonstrated benefit in reducing progression to Alzheimer’s disease (Raschetti et al, 2007).
Test Cutoffs. Almost all studies employ optimal (data-driven) test cutoffs to define test accuracy (sensitivity and specificity). This approach is typically accompanied by a degree of optimism and potentially overstates test accuracy.
Sample Definition. Clear description of whether samples included consecutive patients or were selective is required to evaluate potential bias and generalizability but almost absent in this literature.
Validation. Validation in independent samples is required to establish generalizability of markers but has been scant.
Relevant evidence and guidelines were identified by Medline search through October 2008.
Few studies have included autopsy confirmation; instead, they employed clinical AD diagnosis as the referent standard. Although not directly informative of potential benefit, they are of some interest primarily from revealing possible inaccuracies. Formichi et al  identified studies examining diagnostic accuracy of CSF markers for AD: T-tau (41 studies; 2,287 AD patients and 1,384 controls. While primarily a descriptive review, the test accuracies varied widely and only 1 study included a majority of autopsy-confirmed AD diagnoses.
Diagnostic Accuracy of CSF Markers with AD Autopsy Confirmation
Engelborghs et al assayed P-tau and AB-42 in banked CSF.  Samples were examined from 100 patients with and 100 without dementing illness seen between 1992 and 2003. All dementia diagnoses were autopsy proven (65 pure AD, 8 mixed, 37 non-AD dementias). Details of the sample selection were not provided; none indicated if CSF testing was routine or selective. Of those with dementia, 76 were evaluated in a memory clinic and the remainder in referring centers; all underwent clinical, neuropsychological, and imaging evaluations. The non-demented group was substantially younger (mean age 47 versus 76 years of age). Laboratory technicians performing assays were blinded to clinical diagnoses. Samples from 52 subjects required retesting due to questionable results. The sensitivity of clinical evaluation for a pure AD diagnosis was 83% with 75% specificity; of CSF P-tau and AB-42 80% and 93%, respectively. In models, the CSF biomarkers did not provide incremental diagnostic accuracy over the clinical diagnosis—“[a]lthough biomarkers did not perform significantly better comparing all unique clinical diagnoses, they were also not significantly worse, and could therefore add certainty to an established diagnosis.” 4 of 7 listed authors were employees of the test manufacturer.
In 2003, Clark et al  examined CSF from 106 patients with autopsy-confirmed dementia evaluated at 10 referral clinics and 73 controls (4 pathologically examined). Laboratory technicians were blinded to clinical diagnoses. An optimal cutoff of 234 pg/mL for total tau had sensitivity and specificity of 85% and 84%, respectively, for distinguishing those with AD from cognitively normal individuals ; AB-42 offered no incremental diagnostic value to total tau in ROC analyses. An optimal cutoff of 361 pg/mL had sensitivity and specificity of 72% and 69% for distinguishing AD  from frontotemporal dementia (FTD) and DLB .
In 2008, Bian et al assembled a sample from 2 institutions including 30 patients with FTD (19 autopsy-proven and 11 with known causal genetic mutations) and autopsy proven AD (n=19). Using an optimal cutoff total tau had sensitivity and specificity of 68% and 90%, respectively, for distinguishing FTD from AD. While the tau/AB-42 ratio appeared 100% sensitive distinguishing FTD from AD, it lacked specificity (53%).
As previously noted, among patients with clinically diagnosed AD some have suggested the tau/AB-42 ratio a more accurate measure than either alone. For example, using optimal cutoffs de Jong et al reported sensitivities and specificities for the ratio of 95% and 90% in a sample with clinically diagnosed AD  and VaD (de Jong et al, 2006).  In contrast, Le Bastard et al suggested the p-tau/AB-42 ratio lacked specificity distinguishing AD from vascular dementia (VaD) in a sample of 85 subjects (VaD  or AD ; 76/85 autopsy-confirmed diagnoses)—specificity 52% at a sensitivity of 91% to 95%.
There is limited existing evidence examining incremental diagnostic accuracy of CSF biomarkers for AD diagnosis employing autopsy as a referent standard. The evidence does not demonstrate improvement over a clinical diagnosis, or whether diagnosis using CSF biomarkers would lead to improved net health outcomes.
Neural Thread Protein
Data have been limited on neural thread protein as a marker for AD. Kahle and colleagues reported on the diagnostic potential of CSF levels of total tau protein and neural thread protein in a group of 35 patients with dementia (30 with probable or definite AD), 5 patients with Lewy body disease, 29 patients with Parkinson’s disease, and 16 elderly healthy control patients. Levels of both tau and neural thread protein were elevated in patients with AD compared to controls—sensitivities and specificities for tau and neural thread protein (Kahle et al, 2000).
In a prospective multicenter study conducted at 8 sites, Goodman and colleagues enrolled 168 patients with recent referral to memory clinics.  The urinary neural thread test was 91.4% sensitive for a diagnosis of probable AD (32/35) and 90.1% specific among healthy subjects. However, it was unclear whether the marker changed management or what the potential consequences of a 9.9% false-positive rate might be.
CSF Markers and Progression of Mild Cognitive Impairment
There have been a number of studies of patients with mild cognitive impairment (MCI) for whom the distinction between early stage AD and other etiologies may be more important.
Riemenschneider and colleagues assayed AB and tau levels in 28 patients with MCI who were followed up for 18 months.  Of the 28 patients, 10 progressed to AD, 2 developed frontotemporal dementia, 6 had progressive mild cognitive impairment, and 10 remained stable. Using previously defined cutoffs combining AB and tau results, sensitivity and specificity for conversion to AD were both 90%.
Andreasen and colleagues studied 32 controls and 44 patients with mild cognitive impairment who, after a 1-year follow-up, had progressed to probable AD. At the start of the study, the investigators evaluated total and p-tau and beta amyloid levels. At baseline, 79.5%, 70.4%, and 77.3% had abnormal levels of total tau, P-tau, and AB, respectively. More relevant results would have derived from including patients with mild cognitive development that did not progress to AD.
Hansson et al. obtained 137 CSF samples from a larger group of 180 consecutive individuals with MCI evaluated at a referral memory clinic between 1998 and 2001. CSF was also obtained from 39 controls. In the analytical sample  patients were 50 to 86 years of age at baseline and  were followed a median of 5.2 years.  Fifty-seven  progressed to AD. Using a predictor composed of T-tau and AB-42/P-tau181 employing optimal cutoffs, sensitivity and specificity for progression to clinical AD were 95% and 87% respectively. Patients were not categorized by the presence of amnestic MCI conferring increased risk of conversion to AD (Ganguli et al, 2004).
Bouwman and colleagues followed up 59 patients with MCI a mean of 19 months (range 4 to 45 months) obtaining baseline of CSF AB-42 and tau. Abnormal levels for AB-42 (<495 pg/mL) and tau (>356 pg/mL) were accompanied by increased, but imprecise, relative risks for progression to AD—5.0 and 5.3 respectively.
Parnetti et al examined 55 patients with MCI. At baseline, CSF AB-42, total tau, and p-tau were measured—38% had abnormal values. After 1 year, 4 of 33 stable patients had abnormal markers. Of those progressing to AD, Lewy body or frontotemporal dementia, 10 of 11 had 2 or more abnormal markers. While results from these studies are consistent with potential prognostic utility of markers, sample sizes were small. In addition, the type of MCI (amnestic or nonamnestic) was not distinguished but has important predictive value for progression to dementia (Ganguli et al, 2004).
Herrukka et al. reported on a sample of 106 patients evaluated at a university neurology department and 33 “from an ongoing prospective population-based study”; selection criteria other than agreeing to a lumbar puncture were not further described. 79 were diagnosed with MCI, 47 with amnestic type, 33 converting to dementia; 60 were included as controls. Average follow-up ranged from 3.5 years (MCI converters), 3.9 years (controls), to 4.6 years (stable MCI). CSF AB-42, P-tau and total tau were measured. Graphical representation of AB-42, P-tau, and total tau suggested considerable overlap between controls, those with stable MCI, and progressive MCI. Unfortunately test accuracy was not reported.
From 4 international clinical research centers, Ewers et al retrospectively assembled a sample of 88 patients with amnestic MCI based on both the availability of CSF samples and at least one follow-up between 1 and 3 years after initial evaluation; 57 healthy controls with baseline evaluations only were also included. Forty-three patients (49%) in the MCI group converted to AD over an average 1.5-year follow-up. Using a cutoff of 27.32 pg/mL sensitivity and specificity of p-tau for conversion were 87% and 73%. It should be noted that the conversion rate to AD in the sample was between two- and threefold the typical 15% found in amnestic MCI.
This evidence suggests testing may define increased risk of conversion from MCI to AD. The lack of clearly defined patient samples and distinction of amnestic MCI are significant limitations. Moreover, evidence that earlier diagnosis leads to improved health outcomes through delay of AD onset or improved quality of life is lacking.
American Academy of Neurology
In 2001, the Quality Standards Committee of the American Academy of Neurology issued a “Practice parameter: Diagnosis of dementia (an evidence-based review)”.   Relevant statements to the current policy include the following:
" laboratory tests have yet emerged that are appropriate or routine use in the clinical evaluation of patients with suspected AD. Several promising avenues genotyping, imaging and biomarkers are being pursued, but proof that a laboratory test has value is arduous. Ultimately, the putative diagnostic test must be administered to a representative sample of patients with dementia who eventually have pathologic confirmation of their diagnoses. A valuable test will be one that increases diagnostic accuracy over and above a competent clinical diagnosis."
"There are no CSF or other biomarkers recommended for routine use in determining the diagnosis of AD at this time."
The 3rd Canadian Consensus Conference on Diagnosis and Treatment of Dementia
To Primary Care Physicians
1. Biological markers for the diagnosis of AD should not, at this juncture, be included in the battery of tests routinely used by primary care physicians to evaluate subjects with memory loss (Grade C, Level 3). Consideration for such specialized testing in an individual case should prompt referral of the patient to a neurologist, psychiatrist, or geriatrician engaged in dementia evaluations or a Memory Clinic.
To Specialists
2. Although highly desirable, there currently are no blood- or urine-based AD diagnostics that can be unequivocally endorsed for the routine evaluation of memory loss in the elderly (Grade C, Level 3). The non-invasiveness of such tests, if and when they become available, would be suitable for mass screening of subjects with memory loss presenting to specialists in their private offices and Memory Clinics.
3. Due to their relative invasiveness and availability of other fairly accurate diagnostic modalities (clinical, neuropsychological, and neuroimaging), CSF biomarkers should not be routinely performed in all subjects undergoing evaluation for memory loss (Grade D, Level 2).
4. CSF biomarkers may be considered in the differential diagnosis of AD where there are atypical features and diagnostic uncertainty (Grade B, Level 2). For example, CSF biomarkers may prove useful in differentiating frontal variants of AD from FTD.
5. When a decision to obtain CSF biomarkers is made, combined Aß1-42 and ptau concentrations should be measured by validated ELISA (Grade A, Level 1). It may be best to convey the CSF samples to a centralized facility (commercial or academic) with a track record in generating high-quality, reproducible data.
6. CSF biomarker data in isolation are insufficient to diagnose or exclude AD (Grade C, Level 3). They should be interpreted in light of clinical, neuropsychological, other laboratory and neuroimaging data available for the individual under investigation.
European Federation of Neurological Sciences (EFNS)
CSF total tau, phospo-tau, and Ab42 can be used as an adjunct in cases of diagnostic doubt (Level B).
(Level B rating [established as probably useful/predictive or not useful/predictive] requires at least one convincing class II study or overwhelming class III evidence.)
Evidence that testing for AD-related biomarkers can improve health outcomes is lacking. A majority of studies derive from select samples and optimally defined test cutoffs without validation; generalizability of results is unclear. For the diagnosis of AD, evidence does not demonstrate incremental improvement in diagnostic accuracy over a clinical diagnosis. For predicting conversion from MCI to AD, limited evidence suggests testing might define increased risk. Whether earlier diagnosis leads to improved health outcomes through delay of AD onset or quality of life is lacking. Guidelines are consistent with these conclusions. Thus, the policy statements are unchanged.
2010 Update
A review of the literature has been conducted through August 2010.  There was no new literature identified that would prompt a change in the coverage statement.
De Meyer and colleagues published results of their study in which they used a mixture modeling approach to analyze Cerebrospinal Fluid (CSF) biomarker data to identify biomarker patterns for Alzheimer’s disease (AD) without using information on the clinical diagnosis ( De Meyer, 2010). Using the mixture model, a distinct signature feature of AD was identified of low β-amyloid 1-42 (A β1-42) level, high T-tau level and elevated P-tau 181 level which was detected in more than 90% of the AD group.  In one data set 64 out of 68 patients with autopsy-confirmed diagnosis of Alzheimer’s disease were correctly classified with the AD feature.  In addition, in a separate data set, 57 patients with mild cognitive impairment (MCI) were followed for 5 years. The model correctly identified 100% of MCI cases progressing to AD.  The authors summarize that the analytical approach used, “demonstrates that mixture modeling provides valuable insights for biomarker assessment in the field of AD”.
2011 Update
The National Institute on Aging and the Alzheimer’s Association published revised clinical diagnostic criteria and guidelines in three documents which separate the disease into three distinct phases; the asymptomatic, preclinical phase (Sperling, 2011), the symptomatic predementia phase (Albert, 2011), and the dementia phase (McKhann, 2011).
The guidelines specify that Alzheimer’s biomarkers-including abnormal levels of the proteins amyloid and tau, and shrinkage of certain brain areas- should not yet be put into widespread use, but used only with patients enrolled in clinical trials. In the introduction to the recommendations (Jack, 2011) the author explains that “much additional work needs to be done to validate the application of biomarkers as they are proposed in the workgroup documents”.  Standardization and interpretation of the tests is also limited.  The guidelines also urge caution because there is currently no drug known to halt or significantly delay the onset of symptoms, so people told they are likely to get Alzheimer’s have no effective medication to take.  At this time, there is a lack of scientific evidence that the use of biomarkers in the diagnosis, treatment or management of Alzheimer’s disease improves health outcomes. Therefore, the coverage statement is unchanged.
2012 Update
A search of the MEDLINE database was conducted through August 2012.  There was no new information identified that would prompt a change in the coverage statement. The following is a summary of the key identified literature.
A 2011 meta-analysis included 119 studies on biomarkers and diagnostic imaging in Alzheimer’s disease (AD) (Bloudek, 2011). Sensitivity and specificity were calculated for distinguishing AD from non-demented controls, and for distinguishing AD from non-AD dementias with and without MCI, if available. The included studies of CSF biomarkers used a variety of thresholds, and the reference standard could be either clinical diagnosis or autopsy. Twenty studies were included with the CSF marker AB-42; pooled analysis resulted in sensitivity of 76% and specificity of 77%. CSF total tau was evaluated in 30 included studies with a resulting sensitivity of 79% and specificity of 85%. CSF P-tau was evaluated in 24 included studies resulting in a pooled sensitivity of 78% and specificity of 81%. Six studies evaluated CSF P-tau as a biomarker to distinguish AD patients from patients with MCI, with a pooled sensitivity of 73% and specificity of 69%. The combination of total tau and AB-42 was evaluated in 12 included studies with a pooled sensitivity of 80% and specificity of 76%. When comparing CSF biomarkers, the area under the ROC curve was highest for the test of P-tau alone (85%). Heterogeneity in the studies was considered to be due to the use of different thresholds, although differences in assay kits may also have contributed to the heterogeneity. Sensitivity analysis that only included studies that used autopsy as the reference standard for P-tau resulted in slightly higher sensitivity (82%) and lower specificity (57%).
Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Initiated in 2003, the ADNI is a public-private effort designed to aid researchers and clinicians to develop new treatments and monitor their effectiveness, as well as lessen the time and cost of clinical trials. Participants have been recruited across the U.S. and Canada with follow-up every 6 months for 2-3 years. The participants undergo neuropsychological tests, imaging and biomarker evaluations to determine whether these measures can be combined to measure the progression of MCI and AD. Ongoing results from the study span diagnostic and prognostic questions addressed here.
In a 2011 report, Schmand et al. evaluated the value of neuropsychologic tests, neuroimaging, and biomarkers (AB and tau in CSF) for diagnosing AD in all participants in the ADNI database who had a lumbar puncture (Schmand, 2011). This included 105 normal controls, 179 individuals with MCI, and 91 with AD. Neuropsychologic tests and magnetic resonance imaging (MRI) were found to be the most informative techniques, with 84% and 82% correct classifications, respectively. CSF assessments had 73% correct classifications, respectively, and did not add diagnostic information when all the techniques were combined. CSF assessments were less informative in patients aged 75 years and older (70% correct classification vs. 77% for patients <75).
Two reports from 2009 compared MRI scans and CSF biomarkers for diagnosis and prognosis among 399 participants undergoing both exams (109 normal, 192 amnestic MCI, and 98 AD) (Vemure, 2009; Vemuri, 2009).  In ROC analyses, the c-statistic for MRI as diagnostic of probable AD compared to normal was 0.90, for P-tau/AB-42 0.84 (Vemuri, 2009). In the longitudinal evaluation, both MRI and biomarkers were associated with conversion to AD, a c-index for MRI of 0.69 and for T-tau/AB-42 0.62 (Vemuri, 2009).  Reclassification measures were not reported. In these studies, MRI appeared to provide greater diagnostic (for probable AD) and prognostic information.
In a 2012 report, Schmand et al. evaluated the value of neuropsychologic tests, neuroimaging, and biomarkers (AB and tau in CSF) for predicting the conversion to AD in 175 patients with MCI (Schmand, 2012). With a mean follow-up of 2.7 years (range, 0.5 to 4.6 years), 81 patients (46%) had converted to AD. Neuropsychologic assessment and MRI variables predicted conversion with 63% to 67% classification success both in patients younger and older than 75 years. CSF biomarkers correctly classified 64% of patients younger than 75 years and 60% of patients >75 years. The difference in prediction for the combined markers (70%) was not significantly better than the individual markers.
Landau et al. examined predictors of conversion to clinically diagnosed AD and cognitive decline in 85 patients with amnestic MCI in the ANDI (Landau, 2010). Twenty-eight patients developed AD over a mean 1.9-year follow-up. In multivariate models, CSF markers (P-tau, T-tau, P-tau/AB-42, T-tau/AB-42) were not associated with conversion to AD.
De Meyer et al. developed a model using biomarkers (CSF AB-42/P-tau) in the US-ADNI sample (114 cognitively normal, 200 MCI, and 102 AD patients) (De Meyer, 2010). Sensitivity and specificity in the development set were 90% and 64%, respectively (1/3 of cognitively normal individuals had false-positive results). The model was then validated in a Belgian data set of 73 subjects with autopsy-confirmed dementia correctly identifying 64 of 68 AD patients. In a separate data set of 57 patients with MCI, the model identified all patients progressing to AD.
Alzheimer’s Association
The Alzheimer’s Association has initiated a quality control program for CSF markers, noting that “Measurements of CSF AD biomarkers show large between laboratory variability, likely caused by factors related to analytical procedures and the analytical kits. Standardization of laboratory procedures and efforts by kit vendors to increase kit performance might lower variability, and will likely increase the usefulness of CSF AD biomarkers” (Mattsson, 2011).
2013 Update
A search of the MEDLINE database through 2013 did not reveal any new literature that would prompt a change in the coverage statement. Two studies composed of patients enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were identified.
Lowe et al. evaluated CSF AB-42, amyloid PET, fluorodeoxyglucose-positron emission testing (FDG-PET), and MRI 211 in ADNI (Lowe, 2013). Using the most recent diagnostic criteria, in the 92 patients undergoing all tests, AB-42 had a 94% sensitivity for a positive FDG-PET or MRI. They concluded, “[m]ore correlation and validation studies of biomarkers in the AD population will be essential to understand biomarker performance and correlation with autopsy data.”
In 181 ADNI patients with MCI, Richard et al. found neither MRI nor CSF biomarkers improved classification of patients developing AD over a brief memory test (Richard, 2013). The net reclassification improvement obtained by adding MRI results to the memory test was 1.1% and for CSF AB-42/P-tau, 2.2%.
2014 Update
A literature search conducted through September 2014 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
Diagnostic Accuracy of CSF Markers Versus Clinical Diagnosis
Most studies have relied on clinically diagnosed AD as the criterion standard. These studies are described below.
Rosa et al (2013) conducted a systematic review with meta-analysis of studies of CSF AB-42 in patients with clinically-diagnosed AD (Rosa, 2014). Literature was searched to May 2013, and 41 prospective or retrospective, cohort, case-control, and cross-sectional studies were included (total N=5086 [2932 AD, 2154 nondemented controls]). Patients with MCI were excluded. Seventy-six percent of studies satisfied all quality domains of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Publication bias was detected. A summary ROC curve was generated from all reported thresholds. Pooled sensitivity and specificity were 84% (95% confidence interval [CI], 81 to 85) and 79% (95% CI, 77 to 81), respectively.
Positive and negative likelihood ratios were 4.5 (95% CI, 3.7 to 5.4) and 0.18 (95% CI, 0.14 to 0.22), respectively, and their ratio, the diagnostic odds ratio, was 29 (95% CI, 21 to 40). Statistical heterogeneity was substantial (I2=68%); studies varied in test cutoffs used and severity of AD across patient samples. Eleven studies (total N=1459 [830 AD, 629 controls]) reported AB-42 CSF levels. Mean (SD) CSF AB-42 was 467 pg/mL (189) in patients with AD and 925 pg/mL (414) in controls (weighted mean difference, 450 pg/mL [95% CI, –600 to –289]; p<0.001). However, statistical heterogeneity was considerable (I2=99%). Ferreira et al (2014) published a meta-review of systematic reviews with meta-analyses to assess the use of CSF biomarker tests for AD after publication of revised AD diagnostic criteria in 2011 (Ferreira, 2014). Literature was searched in September 2013, and 7 systematic reviews were included. None were published after introduction of the revised AD diagnostic criteria, so primary studies were searched. Twenty-six prospective or retrospective case-control, cross-sectional, or longitudinal studies were included. Most included studies used clinical criteria for AD diagnosis or did not specify. Results for both the systematic reviews and the individual studies are summarized in Table 1. For differentiating AD from non-demented controls, positive and negative likelihood ratios for all 3 biomarkers ranged from 4-8 and from 0.1-0.3, respectively. For differentiating AD from other dementias, 1 systematic review of 7 studies reported positive and negative likelihood ratios of 46 and 0.09, respectively, for differentiating AD (n=175) from Creutzfeldt–Jakob disease (n=110) (van Harten, 2011). With this systematic review excluded, positive and negative likelihood ratios ranged from 2-7 and from 0.15-0.4, respectively.
Several studies have examined the diagnostic performance of CSF biomarkers for distinguishing probable AD from non-demented controls and from patients with other types of dementia. The range of reported sensitivities and specificities is broad; in systematic reviews with meta-analyses, sensitivity and specificity were 80%-82% and 82%-90%, respectively, for differentiating AD from non-demented controls, and 73% and 67%, respectively, for differentiating AD from other dementias. Positive and negative likelihood ratios were 2-8 and 0.2-0.4, respectively, in either setting. This evidence does not indicate that
CSF biomarkers improve the accuracy of clinical diagnostic criteria.
Cure et al (2014) conducted a systematic review with meta-analysis of CSF and imaging studies for the diagnosis of definite AD (autopsy-confirmed) (Cure, 2014). Literature was searched in January 2012, and 3 studies of CSF markers (P-tau, T-tau, AB-42, and AB-40) were identified (total N=337). Pooled sensitivity of all CSF tests was 82% (95% CI, 72 to 92), and pooled specificity was 75% (95% CI, 60 to 90). Statistical heterogeneity was not reported, but studies varied in AD definitions, controls (non-demented patients or patients with dementia due to other causes), and test thresholds. Area under the summary ROC curve constructed using multiple test thresholds was 0.84.
CSF Markers in Combination
CSF AB-42 level normalized to CSF AB-40 (ie, the AB-42/AB-40 ratio) is being investigated as a marker for patients with uncertain clinical diagnosis. Because AB-40 is not incorporated into amyloid plaques,
CSF levels are more stable than those of AB-42. Sauvee et al (2014) examined the AB-42/AB-40 ratio in
122 patients with atypical dementia who had discordant CSF biomarker results (ie, tau, P-tau, and AB-
42) (Sauvee, 2014). Using 0.05 as the ratio threshold, biological profiles were clarified in 72 (59%) of 122 patients with the addition of the AB-42/AB-40 ratio. However, of 35 patients diagnosed with AD by biological profile, 9 (26%) did not meet clinical criteria for AD or mixed dementia.
Clinical utility of CSF biomarkers used in combination has not been demonstrated.
Neural Thread Protein
Zhang et al (2014) conducted a systematic review and meta-analysis of urinary AD-associated neural thread protein for diagnosing AD in patients with suspected AD (Zhang, 2014). Nine studies were included (total N=841 patients with probable or possible AD, 37 patients with MCI, 992 non-AD demented or non-demented controls). For probable AD, pooled sensitivity and specificity were 89% (95% CI, 86 to 92) and 90% (95% CI, 88 to 92), respectively. Pooled positive and negative likelihood ratios were 8.9 (95% CI, 7.1 1 to 11.1) and 0.12 (95% CI, 0.09 to 0.16), respectively.
Data on neural thread protein as a marker for AD are limited. In 2 studies and 1 meta-analysis, estimated sensitivity and specificity ranged from 70%-91% and from 80%-90%, respectively. Clinical utility of neural thread protein testing has not been demonstrated.
Ritchie et al (2014) published a Cochrane review of CSF amyloid beta protein (primarily AB-42) for detecting which patients with MCI would progress to AD or other dementias (Ritchie, 2014). Literature was searched in December 2012, and 14 prospective or retrospective cohort studies of AD, including 1 discussed below, were included (total N=1349 patients with MCI). Studies that enrolled patients less than 50 years of age or with less than 2 years of follow-up were excluded. Risk of bias was moderate to high in most studies. AD, diagnosed by clinical criteria, developed in 436 (32%) of 1349 patients. Sensitivity ranged from 36%- 100%, and specificity from 29%-91%. Due to heterogeneity of thresholds used, summary sensitivity and specificity were not calculated. However, a summary ROC curve was generated using the median specificity of 64%; pooled sensitivity was 81% (95% CI, 72 to 87). Positive and negative likelihood ratios were 2.2 (95% CI, 2.0 to 2.5) and 0.31 (95% CI, 0.21 to 0.48), respectively. Analysis of the pre- and posttest probabilities of conversion to AD among patients with MCI in primary and secondary care settings showed little incremental value of AB-42 testing in either setting.
The 2014 meta-review of systematic reviews by Ferriera et al (discussed above) included studies of CSF biomarkers for differentiating patients with MCI who progress to AD from those who do not (Ferriera, 2014). In systematic reviews with meta-analyses, sensitivity and specificity of AB-42 were 67% (95% CI, 59 to 75) and 71% (95% CI, 65-78), respectively; for T-tau, 82% (95% CI, 76 to 86) and 70% (95% CI, 65 to 85), respectively; and for P-tau, 81% (69 to 91) and 65%-76%, respectively. Positive and negative likelihood ratios for all 3 tests ranged from 2-3 and from 0.3-0.5, respectively.
In 2012, the Alzheimer's Biomarkers Standardization Initiative published consensus recommendations for standardization of preanalytical aspects (eg, fasting, tube types, centrifugation, storage time and temperature) of CSF biomarker testing (Vanderstichele, 2012).
In 2013, the Alzheimer’s Association published recommendations for operationalizing the detection of cognitive impairment during the Medicare annual wellness visit in primary care settings (Cordell, 2013). The recommended algorithm for cognitive assessment was based on “current validated tools and commonly used rule-out assessments.” Guideline authors noted that use of biomarkers (eg, CSF tau and beta amyloid proteins) “was not considered as these measures are not currently approved or widely available for clinical use.”
The 4th Canadian Consensus Conference on Diagnosis and Treatment of Dementia (CCCDTD4)
CCCDTD4 published updated evidence-based consensus recommendations in 2012 (Gauthier, 2012; Rosa-Neto, 2013). There was consensus that plasma AB-42 measurement is unreliable and is not recommended for clinical practice. There was lack of consensus for measurement of CSF AB-42 and tau levels in patients with atypical dementia. Conference participants concluded that “for now, measurement of CSF AB1-42 and tau have no clinical utility in Canada, although they are part of research protocols in observational and therapeutic studies.”
European Federation of Neurological Societies (EFNS)-European Neurological Society (ENS)
In 2012, EFNS-ENS published updated evidence-based consensus guidelines on the diagnosis and management of disorders associated with dementia. A Level B recommendation (probably effective based on Class 3 [unblinded] evidence) that CSF AB-42/tau/p-tau assessment helps to differentiate AD was included.
2015 Update
A literature search conducted using the MEDLINE database through August 2015 did not reveal any new information that would prompt a change in the coverage statement.     
2016 Update
A literature search conducted through June 2016 did not reveal any new information that would prompt a change in the coverage statement.
2017 Update
A literature search conducted through July 2017 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
The evaluation of a biomarker test for diagnosis or prognosis focuses on 3 main principles: (1) analytic validity (technical accuracy of the test in detecting the marker that is present or in excluding a marker that is absent); (2) clinical validity (diagnostic performance of the test [sensitivity, specificity, positive and negative predictive values] in detecting clinical disease or defining prognosis); and (3) clinical utility (ie, a demonstration that the diagnostic or prognostic information can be used to improve patient health outcomes).
Analytic Validity
Analytic validity is the ability of a test to accurately and reliably measure the marker of interest. Measures of analytic validity include sensitivity (detection rate), specificity (1􀀐 false-positive rate), reliability (repeatability of test results), and assay robustness (resistance to small changes in preanalytic or analytic variables). Measurements of the cerebrospinal fluid (CSF) concentrations of the amyloid-β peptide 1-42 (Aβ42), total tau protein (tTau), and phosphorylated (pTau) have high variability within and across different laboratories and across different analytic platforms. Shaw and colleagues reported a 7 center interlaboratory standardization study using Alzheimer Disease Neuroimaging Initiative (ADNI) participants for CSF Aβ42, tTau, and pTau measures with a within-laboratory percent coefficient of variation (CV) ranging from 5.3% to 10.8% and interlaboratory percent CV ranging from 13.1% to 17.9% (Shaw, 2011).  Lewczuk and colleagues reported comparison of CSF Aβ-42, tTau, and pTau measurements across 14 laboratories in Germany, Austria, and Switzerland with interlaboratory percent CV of 20% to 30% (Lewczuk, 2006). Verwey and colleagues reported interlaboratory % percent CV of 37%, 16%, and 15% for CSF Aβ42, tTau, and pTau, respectively, and within-laboratory % percent CV of 25%, 18%, and 7% (Verwey, 2009). Monge-Argilés and colleagues found that enzyme-linked immunosorbent assay (ELISA) and a multiplex (xMAP) technology for measurement of CSF Aβ42, tTau, and pTau yielded different absolute values for the various analytes, always higher in ELISA, although the values were highly correlated (Monge-Argiles, 2014).  Mattsson and colleagues reported results of an external quality control program for CSF biomarkers (Mattsson, 2011).Forty laboratories using commercially available kits for Aβ, tTau, or pTau were sent CSF samples for analysis several times a year from a central source. Total CVs between the laboratories were ranged from 13% to 36%.
Janelidze and colleagues also found that the CSF Aβ42/Aβ40 ratio was significantly better than Aβ42 alone in detecting brain amyloid deposition in prodromal AD and in differentiating AD dementia from non-AD dementias across 3 different immunoassays and 3 patient cohorts (Janelidze, 2016).
In 2016, Olsson and colleagues performed a comprehensive systematic review and meta-analysis of 231 articles including 15,699 patients with AD and 13,018 controls published between 1984 and 2014 describing both diagnostic and prognostic performance of CSF biomarkers (Olsson, 2016). Five articles were classified as high quality and 226 as medium quality; only studies with autopsy confirmation were eligible to be scored as high quality. Diagnostic and prognostic accuracy were not reported due to large variation in cutoffs for positivity. Instead, biomarker performance was summarized using the ratio of biomarker concentration in patients with AD and controls (ie, fold change) or the ratio of biomarker concentration in those with MCI due to AD and those with stable mild cognitive impairment who had no further cognitive decline during 2 years of follow-up. A fold change ratio above one indicates that the concentration of the biomarker is higher in the AD population than the control population, and a ratio below one indicates the concentration is higher in the control population than the AD population. Summary fold change was calculated with random-effects meta-analysis. CSF tTau, pTau, and Aβ42 were consistently and strongly associated with AD diagnosis: CSF tTau average ratio 2.54 (95% CI, 2.44 to 2.64); pTau average ratio 1.88 (95% CI, 1.79 to 1.97); and Aβ42 average ratio 0.56 (95% CI, 0.55 to 0.58). All 3 biomarkers were also able to differentiate between cohorts with MCI due to AD and those with stable MCI: Aβ42 average ratio 0.67 (95% CI, 0.63 to 0.73); pTau average ratio 1.72 (95% CI, 1.46 to 2.02); and tTau average ratio 1.76 (95% CI, 1.64 to 1.89).
Analytic validity
One publication describing components of analytic validity for a competitive enzyme-linked immunosorbent assay (ELISA) format affinity assay to measure neural thread protein (NTP) in urine samples was found (Levy, 2007). Seven-hundred-twenty replicates were assayed at 4 different clinical laboratories by 4 different trained personnel, on 3 different days each, consisting of high, medium, and low NTP urines in 20 replicates each per day. The CVs were reported to vary from 2.3% to 7.1% in high-NTP urine, 1.5% to 8.5% in medium-NTP urine, and 2.5% to 15% in low-NTP urine. Between and within laboratory variation was not given. Three lots of high-, medium-, and, low-NTP controls were tested in 4 replicates each for 3 days. The CVs varied from 4.3 to 8.6%. Twenty replicates of low-NTP urine samples were spiked with known concentrations of NTP to 18.9, 23.9, 28.9, 33.9, and 38.9 mg/mL; mean recovery was 05.5%.
2018 Update
A literature search was conducted through August 2018.  There was no new information identified that would prompt a change in the coverage statement.  The key identified literature is summarized below.
Diagnosis of Alzheimer Disease
Howell et al evaluated the clinical validity of CSF biomarkers in diverse populations by prospectively recruiting 135 older Americans to undergo detailed clinical, neuropsychological, genetic, magnetic resonance imaging, and CSF analysis (Howell, 2017). Despite finding comparable levels of CSF Aβ42 and Aβ42/Aβ40, cognitive impairment in African Americans was noted to be associated with smaller changes in CSF tau markers but greater impact from similar magnetic resonance imaging white matter hyperintensity burden than Caucasians leading to the conclusion that race-associated differences in CSF tau markers and ratios may lead to underdiagnosis of AD in African Americans.
A multicenter study by Park et al drew 194 patients from 6 memory clinics in South Korea. Of the 194 patients, 76 showed Alzheimer disease dementia (ADD); 47 had other neurologic disorders (OND) involving cognitive impairment; and 71 had no sign of cognitive impairment, and thus served as a control group (Park, 2017).  The primary aim was to find accurate cutoff values for CSF biomarkers to distinguish between AD and either control or OND. When the ADD group was compared with the control group, cutoff values were as follows: 481 pg/mL (Aß42), 326 pg/mL (tTau), 57 pg/mL (pTau), with improved tTau/Aß42 ratios (0.55; sensitivity, 99%; specificity, 95%) and pTau/Aß42 (0.10; sensitivity, 96%; specificity, 96%). When the ADD group was compared with the OND group, the same pattern held for ratio cutoff values (especially tTau/Aß42) being more accurate than those of individual proteins (ie, Aß42=478 pg/mL, tTau=327 pg/mL, pTau=48 pg/mL, [sensitivity range, 83%-93%; specificity range, 70%-85%] vs tTau/Aß42=0.76 [sensitivity, 93%; specificity, 92%]; and pTau/Aß42=0.12 [sensitivity, 95%; specificity, 89%). Additionally, area under the curve measurements showed greater accuracy in ratios (tTau/Aß42 and pTau/ Aß42) than in individual biomarkers: for ADD vs control, the area under the curve for both ratio biomarkers were 0.99 (95% CI, 0.98 to 1.0), and for ADD vs OND, area under the curve measurements were similar (0.94 for both). While study limitations included a younger-than-average group of AD patients and a small comparison group with several neurologic disorders, the authors concluded that the combined biomarker ratio was superior to individual markers at accurately predicting AD. They based this conclusion on the comparability of cutoff values between this study and previous studies.
Prognosis for Progression of MCI
Studies have evaluated the prognostic value of CSF biomarkers for progression of MCI and conversion to clinically manifest AD.
Ritchie et al published a Cochrane review of CSF amyloid-β protein (primarily Aβ42) for detecting which patients with MCI would progress to AD or other dementias (Ritchie, 2014). Literature was searched in December 2012, and 14 prospective or retrospective cohort studies of AD were included (1349 patients with MCI). Studies that enrolled patients younger than 50 years of age or with less than 2 years of follow-up were excluded. Risk of bias was moderate to high in most studies. Diagnosed by clinical criteria, AD developed in 436 (32%) of 1349 patients. Sensitivity ranged from 36% to 100%, and specificity from 29% to 91%. Due to heterogeneity of thresholds used, summary sensitivity and specificity were not calculated. However, a summary receiver operating characteristic curve was generated using the median specificity of 64%; pooled sensitivity was 81% (95% CI, 72% to 87%). Positive and negative likelihood ratios were 2.2 (95% CI, 2.0 to 2.5) and 0.31 (95% CI, 0.21 to 0.48), respectively. Analysis of the pre- and posttest probabilities of conversion to AD among patients with MCI in primary and secondary care settings showed little incremental value of Aβ42 testing in either setting.

81099Unlisted urinalysis procedure
81479Unlisted molecular pathology procedure
86849Unlisted immunology procedure

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