BlueCross and BlueShield of Montana Medical Policy/Codes
Biochemical Markers of Alzheimers Disease (AD)
Chapter: Medicine: Tests
Current Effective Date: October 25, 2013
Original Effective Date: April 18, 2013
Publish Date: October 25, 2013
Description

A variety of biochemical changes have been associated with Alzheimer’s disease pathology and are being evaluated to aid in the diagnosis of Alzheimer’s disease (AD). Some of the most commonly studied biomarkers are amyloid beta peptide 1-42 (AB-42), and total or phosphorylated tau protein (T-tau or P-tau) in cerebrospinal fluid (CSF).

The diagnosis of AD is divided into 3 categories: possible, probable, and definite AD. (1) A diagnosis of definite AD requires post-mortem confirmation of AD pathology, including the presence of extracellular beta amyloid plaques and intraneuronal neurofibrillary tangles in the cerebral cortex. (2) Probable AD dementia is diagnosed clinically when the patient meets core clinical criteria for dementia and has a typical clinical course for AD. A typical clinical course is defined as an insidious onset, with the initial and most prominent cognitive deficits being either amnestic or non-amnestic, e.g., language, visuospatial, or executive function deficits, and a history of progressively worsening cognition over time. A diagnosis of possible AD dementia is made when the patient meets the core clinical criteria for AD dementia but has an atypical course or an etiologically mixed presentation.

Mild cognitive impairment (MCI) may be diagnosed when there is a change in cognition, but not sufficient impairment for the diagnosis of dementia. (3) Features of MCI are evidence of impairment in one or more cognitive domains and preservation of independence in functional abilities. In some patients, MCI may be a predementia phase of AD. Patients with MCI or suspected AD may undergo ancillary testing (e.g., neuroimaging, laboratory studies, and neuropsychological assessment) to rule out vascular, traumatic, and medical causes of cognitive decline and to evaluate genetic factors. Because clinical diagnosis can be difficult, particularly early in the course of disease, there has been considerable interest in developing an accurate laboratory test for AD. There are several potential biomarkers of AD that are associated with Alzheimer’s disease pathology (i.e., beta amyloid plaques and neurofibrillary tangles).

Elevated cerebrospinal fluid (CSF) levels of P-tau or T-tau or an amyloid beta peptide such as AB-42 have been found in patients with AD. Other potential CSF peptide markers have also been explored. (4, 5) 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 a Tau/AB-42 ratio, a potentially more accurate diagnostic marker than either alone. (6) A variety of kits are commercially available to measure AB-42 and tau proteins, and there is large between-laboratory variability in cerebrospinal fluid (CSF) biomarker measurement. (7)

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, as developed by Nymox Pharmaceutical Corporation.

Abnormal levels of the tau protein have been discovered in nasal mucosa tissue of patients with AD. These changes were detected in autopsy derived material of confirmed AD cases as well as clinically definite AD patients.

Heavy metal mercury blood levels are under investigation as a marker of AD. In clinical studies, blood mercury levels were more than two-fold higher in patients with AD as compared to the control groups. Mercury exposure may be from an environmental factor that influences the risk of acquiring AD or it may be released from brain tissue with the advancement of neuronal death that occurs as the AD progresses.

Policy

Each benefit plan, summary plan description or contract defines which services are covered, which services are excluded, and which services are subject to dollar caps or other limitations, conditions or exclusions. Members and their providers have the responsibility for consulting the member's benefit plan, summary plan description or contract to determine if there are any exclusions or other benefit limitations applicable to this service or supply.  If there is a discrepancy between a Medical Policy and a member's benefit plan, summary plan description or contract, the benefit plan, summary plan description or contract will govern.

Coverage

Measurement of biochemical markers of Alzheimer’s disease (AD) are considered experimental, investigational and unproven. These measurements include, but are not limited to, ANY of the following:

  • Cerebrospinal fluid (CSF) biomarkers, including tau protein, amyloid beta (AB) peptides, or neural thread proteins, OR
  • Urinary biomarkers, including neural thread proteins, OR
  • Nasal mucosa tissue biomarkers, including tau protein, OR
  • Blood levels of heavy metal mercury as a biomarker.

Policy Guidelines

Specific CPT codes for biochemical markers of Alzheimer’s disease are not available.

Rationale

The clinical purposes of testing for Alzheimer’s disease (AD)-related biomarkers are to improve diagnostic accuracy or to predict conversion from mild cognitive impairment (MCI) to AD.

Evidence of health benefit or clinical utility 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 supporting health benefit following testing requires considering the following: appropriate reference standard, requirements for predicting conversion from MCI to AD, how better 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, comparison with autopsy is most appropriate to validly assess incremental diagnostic improvement accompanying biomarkers.

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. (8) Alternative approaches such as classical receiver operating characteristic (ROC) analyses, while providing insight, do not allow one to directly translate improvements in diagnostic or prognostic accuracy to changes in health outcomes. (9)

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, in turn overstating test accuracy.

Sample Definition. Clear description of whether samples included consecutive patients or were selective is required to evaluate potential bias—including verification bias (10)—and generalizability.

Validation. Validation in independent samples is required to establish generalizability of markers.

Relevant evidence and guidelines were identified by a MEDLINE search through July 2013.

Diagnostic Accuracy of CSF Markers Versus Clinical Diagnosis

Most studies have relied on clinically diagnosed AD as the referent standard. In a 2006 review of studies using clinical diagnosis as the referent standard, Formichi et al. (11) identified those examining diagnostic accuracy of cerebrospinal fluid (CSF) markers for AD: Total tau protein (T-tau) (41 studies; 2,287 AD patients and 1,384 controls; sensitivities 52% to 100%; specificities 50% to 100%), phosphorylated tau protein (P-tau) (12 studies; 760 AD patients and 396 controls; sensitivities 37% to 100%; specificities 80% to 100%), amyloid beta peptide 1-42 (AB-42) (14 studies; 688 AD patients and 477 controls; sensitivities 55% to 100%; specificities 80% to 100%). While primarily a descriptive review, test accuracies varied widely and a single study included a majority of autopsy-confirmed AD diagnoses.

A 2011 meta-analysis included 119 studies on biomarkers and diagnostic imaging in Alzheimer’s disease (AD). (12) 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, with clinical diagnosis or autopsy as the reference standard. 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 P-tau alone (0.85). Heterogeneity in the studies was considered to be due to the use of different thresholds, although differences in assay kits may also have contributed. Sensitivity analysis including studies that used autopsy as the reference standard for P-tau resulted in slightly higher sensitivity (82%) and lower specificity (57%).

Diagnostic Accuracy of CSF Markers with AD Autopsy Confirmation

Engelborghs et al. assayed P-tau and AB-42 in banked CSF. (13) 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; whether CSF testing was routine or selective was not indicated. 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 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.” Four of 7 listed authors were employees of the test manufacturer.

Clark et al. (14) 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 (n=73) from cognitively normal individuals (n=74); 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%, respectively, for distinguishing AD (n=74) from frontotemporal dementia (FTD) (n=3) and dementia with Lewy bodies (DLB) (n=10).

Bian et al. (15) 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 of 403 pg/mL, total tau had sensitivity and specificity of 68% and 90%, respectively, for distinguishing FTD from AD. A tau/AB-42 ratio of 1.06 had 97% specificity for distinguishing FTD from AD.

As previously noted, among patients with clinically diagnosed AD, some have suggested the tau/AB-42 ratio a more accurate predictor 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 (n=61) and vascular dementia (VaD) (n=61). (16) In contrast, Le Bastard et al. (17) found the P-tau/AB-42 ratio lacked specificity distinguishing AD from VaD in a sample of 85 subjects (VaD [n=64] or AD [n=21]; 76/85 autopsy-confirmed diagnoses)—specificity 52% at a sensitivity of 91% to 95%.

Conclusions: 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 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 (63% and 93%) and neural thread protein (70% and 80%, all respectively). (18)

In a prospective multicenter study conducted at 8 sites, Goodman and colleagues enrolled 168 patients with recent referral to memory clinics. (19) 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 (MCI)

Studies have also evaluated the prognostic value of markers for progression of MCI and conversion to clinically manifest AD.

Mattsson et al. recruited individuals from 12 U.S. and European centers with MCI (n=750), AD (n=529), and controls (n=304). (20) Those with MCI were followed a minimum of 2 years or to progression. Development of probable AD was associated with lower CSF AB-42, and higher T-tau and P-tau. Using cutoffs defined in the AD and control groups for a diagnostic sensitivity of 85%, combining AB-42/P-tau and T-tau yielded sensitivity for AD conversion of 83% (95% confidence interval [CI]: 78% to 88%), specificity 72% (95% CI: 68% to 76%), positive predictive value 62%; and negative predictive value 88%. Amnestic MCI was not distinguished.

Herukka 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. (21) Seventy-nine 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. Test accuracy was not reported.

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. (22) CSF was also obtained from 39 controls. In the analytical sample (n=137), patients were 50 to 86 years of age at baseline and 55% female. They were followed a median of 5.2 years and 57 (42%) progressed to AD. Using a predictor composed of T-tau and AB-42/P-tau employing optimal cutoffs, sensitivity and specificity for progression to clinical AD were 95% (95% CI: 86% to 98%) and 87% (95% CI: 78% to 93%), respectively. Patients were not categorized by the presence of amnestic MCI conferring increased risk of conversion to AD. (23)

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. (24) 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% (95% CI: 73% to 93%) and 73% (95% CI: 55% to 84%) respectively. It should be noted that the conversion rate to AD in the sample was between 2- and 3-fold the typical 15% found in amnestic MCI.

Andreasen et al. studied 32 controls and 44 patients with MCI who, after a 1-year follow-up, had progressed to probable AD. (25) At the start of the study, the investigators evaluated total and P-tau and AB-42 levels. At baseline, 79.5%, 70.4%, and 77.3% had abnormal levels of total tau, P-tau, and AB-42, respectively. More informative results would have derived from including patients with MCI not progressing to AD.

Bouwman and colleagues followed 59 patients with MCI a mean of 19 months (range, 4 to 45 months), obtaining a baseline of CSF AB-42 and tau. (26) Abnormal AB-42 (<495 pg/mL) and total tau (>356 pg/mL) were accompanied by increased, but imprecise, relative risks for progression to AD—5.0 (95% CI: 1.4 to 18.0) and 5.3 (95% CI: 1.5 to 19.2), respectively.

Parnetti et al. examined 55 patients with MCI. (27) 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 disease, or familial frontotemporal dementia (FTD), 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.

Conclusions. Evidence suggests biomarker testing may identify increased risk of conversion from MCI to AD. Evidence that earlier diagnosis leads to improved health outcomes through delay of AD onset or improved quality of life is lacking.

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 (CSF AB and tau) for diagnosing AD in all participants in the ADNI database who had a lumbar puncture. (28) 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). (29, 30) 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. (29) 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. (30) 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. (31) 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 ADNI. (32) 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). (33) 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.

Lowe et al. evaluated CSF AB-42, amyloid PET, fluorodeoxyglucose-positron emission testing (FDG-PET), and MRI 211 in ADNI patients with at least one detected amyloid biomarker. (34) 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. (35) 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%.

Improved Health Outcomes (Clinical Utility). Although not without controversy because of modest efficacy, cholinesterase inhibitors are used to treat mild-to-moderate AD. (36) Memantine, an N-methyl-d-aspartate (NMDA) receptor antagonist, appears to provide a small benefit in those with moderate-to-advanced disease. (37) 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 AD. (38-40)

A Medline literature search was also conducted regarding heavy metal mercury and revealed no clear relationship with AD. Weil et al. reported no strong correlation between higher blood mercury and neurobehavioral performance (50). A study by Carta and others found inconsistent results when psychological tests were given to patients with different levels of blood mercury (46). Yokoo and colleagues found a relationship between neuropsychological tests results and hair mercury levels but did not correlate the results with AD (48). Mutter suggests that apolipoprotein may moderate mercury related AD but did not provide a direct link with AD (49).

Summary

Evidence that testing for Alzheimer’s disease (AD)-related biomarkers in patients with dementia can improve health outcomes is lacking. A majority of studies derive from select samples and define optimal test cutoffs without validation, thus generalizability of results is unclear. For the diagnosis of AD, evidence does not demonstrate incremental improvement in diagnostic accuracy over clinical testing. For predicting conversion from mild cognitive impairment to AD, limited evidence, including that from the Alzheimer’s Disease Neuroimaging Initiative, 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. Therefore, this testing is considered experimental, investigational and unproven.

Practice Guidelines and Position Statements

In 1984, the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer’s Disease and Related Disorders Association (ADRDA) developed clinical criteria for the diagnosis of AD. (41) While evidence to date has used NINCDS/ADRDA’s AD classification, in 2011, the National Institute on Aging and the Alzheimer’s Association workgroup revised diagnostic criteria for diagnosis of dementia due to Alzheimer’s disease. (1)

The diagnostic categories were defined as follows in the 1984 guidelines:

Possible Alzheimer’s Disease

Clinical diagnosis of possible AD:

  1. 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
  2. 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
  3. 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:

  1. 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;
  2. Deficits in 2 or more areas of cognition;
  3. Progressive worsening of memory and other cognitive functions;
  4. No disturbance of consciousness;
  5. Onset between ages 40 and 90 years, most often after the age of 65 years; and
  6. 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:

  1. Progressive deterioration of specific cognitive functions such as language (aphasia), motor skills (apraxia), and perception (agnosia);
  2. Impaired activities of daily living and altered patterns of behavior;
  3. Family history of similar disorders, particularly if confirmed neuropathologically; and
  4. 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:

  1. Plateaus in the course of progression of the illness;
  2. Associated symptoms of depression, insomnia, incontinence, delusions, illusions, hallucinations, sexual disorders, weight loss, and catastrophic verbal, emotional, or physical outbursts;
  3. Other neurologic abnormalities in some patients, especially with more advanced disease and including motor signs such as increased muscle tone, myoclonus, or gait disorder; and
  4. Seizures in advanced disease CT normal for age

 Features that make the diagnosis of probable AD uncertain or unlikely include:

  1. Sudden apoplectic onset;
  2. Focal neurological findings such as hemiparesis, sensory loss, visual field deficits, and incoordination early in the course of the illness; and
  3. 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:

  1. Clinical criteria for probable Alzheimer’s disease AND
  2. Histopathologic evidence obtained from a biopsy or autopsy.

As of 2011, probable AD is defined by the National Institute on Aging and the Alzheimer’s Association workgroup according to the following diagnostic criteria (1):

“Meets criteria for dementia described (1) ... and in addition, has the following characteristics:

  1. Insidious onset. Symptoms have a gradual onset over months to years, not sudden over hours or days;
  2. Clear-cut history of worsening of cognition by report or observation; and
  3. The initial and most prominent cognitive deficits are evident on history and examination in one of the following categories.
    1. Amnestic presentation: It is the most common syndromic presentation of AD dementia. The deficits should include impairment in learning and recall of recently learned information. There should also be evidence of cognitive dysfunction in at least one other cognitive domain, as defined earlier in the text.
    2. Nonamnestic presentations: Language presentation: The most prominent deficits are in word-finding, but deficits in other cognitive domains should be present. Visuospatial presentation: The most prominent deficits are in spatial cognition, including object agnosia, impaired face recognition, simultanagnosia, and alexia. Deficits in other cognitive domains should be present. Executive dysfunction: The most prominent deficits are impaired reasoning, judgment, and problem solving. Deficits in other cognitive domains should be present.

The diagnosis of probable AD dementia should not be applied when there is evidence of (a) substantial concomitant cerebrovascular disease, defined by a history of a stroke temporally related to the onset or worsening of cognitive impairment; or the presence of multiple or extensive infarcts or severe white matter hyperintensity burden; or (b) core features of Dementia with Lewy bodies other than dementia itself; or (c) prominent features of behavioral variant frontotemporal dementia; or (d) prominent features of semantic variant primary progressive aphasia or nonfluent/agrammatic variant primary progressive aphasia; or (e) evidence for another concurrent, active neurological disease, or a non-neurological medical comorbidity or use of medication that could have a substantial effect on cognition.”

All probable AD by NINCDS-ADRDA criteria are subsumed in the revised probable AD criteria. Revised criteria include a category of “Probable AD dementia with increased level of certainty” due to documented decline or having a causative AD genetic mutation. Additionally, a category “Probable AD dementia with evidence of the AD pathophysiological process” has been added. Evidence of the AD pathophysiologic process is supported by detection of low CSF AB-42, positive positron emission tomography (PET) amyloid imaging, or elevated CSF tau, and decreased 18-F fluorodeoxyglucose uptake on PET in the temporoparietal cortex with accompanying atrophy by magnetic resonance imaging (MRI) in relevant structures. Detection of the “pathophysiological process” is further divided according to when in the disease natural history markers are expected to be detectable.

Note on Revised AD Criteria and Biomarkers

The biomarkers reviewed in this policy are included in a category among revisions to AD diagnostic criteria—“probable AD dementia with evidence of the AD pathophysiological process”. However, the diagnostic criteria workgroup publication noted “we do not advocate the use of AD biomarker tests for routine diagnostic purposes at the present time. There are several reasons for this limitation: 1) the core clinical criteria provide very good diagnostic accuracy and utility in most patients; 2) more research needs to be done to ensure that criteria that include the use of biomarkers have been appropriately designed, 3) there is limited standardization of biomarkers from one locale to another, and 4) access to biomarkers is limited to varying degrees in community settings. Presently, the use of biomarkers to enhance certainty of AD pathophysiological process may be useful in three circumstances: investigational studies, clinical trials, and as optional clinical tools for use where available and when deemed appropriate by the clinician.” (1)

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”. (7)

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)”. (42) Relevant statements to the current policy include the following:

"...no 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 (43)

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

  1. 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.
  2. 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).
  3. 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.
  4. When a decision to obtain CSF biomarkers is made, combined Aß1-42 and P-tau 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.
  5. 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.

Levels of Evidence

A: Good evidence to recommend the clinical preventive action.

B: Fair evidence to recommend the clinical preventive action.

C: Existing evidence is conflicting and does not allow making a recommendation for or against use of the clinical preventive action; however, other factors may influence decision-making.

D: Fair evidence to recommend against the clinical preventive action.

E: Good evidence to recommend against the clinical preventive action.

I: Insufficient evidence (in quantity and/or quality) to make a recommendation; however, other factors may influence decision-making.

I: Evidence from randomized controlled trial(s)

II-1: Evidence from controlled trial(s) without randomization

II-2: Evidence from cohort or case-control analytic studies, preferably from more than one centre or research group

II-3: Evidence from comparisons between times or places with or without the intervention; dramatic results in uncontrolled experiments could be included here

III: Opinions of respected authorities, based on clinical experience; descriptive studies or reports of expert committees

European Federation of Neurological Sciences (EFNS) (44)

2010 Guidelines recommend routine CSF analysis in differential diagnosis for atypical clinical presentations of AD (good practice point). In addition, alterations in CSF T-tau, P-tau, and AB-42 support diagnosis of AD (Level B).

The guidelines also state that “there are considerable differences in absolute concentrations of these markers between laboratories, even when the same kit is used. Before CSF can be widely accepted as a reliable tool a consensus for processing and handling of the samples is needed.”

(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.)

Class II: A prospective study of a narrow spectrum of persons with the suspected condition, or a well- designed retrospective study of a broad spectrum of persons with an established condition (by gold standard) compared to a broad spectrum of controls, where test is applied in a blinded evaluation, and enabling the assessment of appropriate tests of diagnostic accuracy

Class III: Evidence provided by a retrospective study where either persons with the established condition or controls are of a narrow spectrum, and where test is applied in a blinded evaluation.

Coding

Disclaimer for coding information on Medical Policies

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy. They may not be all-inclusive.

The presence or absence of procedure, service, supply, device or diagnosis codes in a Medical Policy document has no relevance for determination of benefit coverage for members or reimbursement for providers. Only the written coverage position in a medical policy should be used for such determinations.

Benefit coverage determinations based on written Medical Policy coverage positions must include review of the member’s benefit contract or Summary Plan Description (SPD) for defined coverage vs. non-coverage, benefit exclusions, and benefit limitations such as dollar or duration caps. 

ICD-9 Codes

Experimental, investigational and unproven for all diagnoses.

ICD-10 Codes

Experimental, investigational and unproven for all diagnoses.

Procedural Codes: 81099, 83015, 83018, 83520, 86849
References
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History
January 2013  New 2013 BCBSMT medical policy.  Considered investigational.
October 2013 Policy updated with routine literature review. Coverage unchanged. Rationale completely revised.  Added CPT codes 81099 and 86849.  Removed CPT codes 83825 and 83912.
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Biochemical Markers of Alzheimers Disease (AD)