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The Power of Elecsys® in Alzheimer’s disease

Robust, clinically validated results to ensure patients get the care they deserve

Alzheimer’s disease (AD) is a public health crisis.1 The total number of people with dementia is expected to grow to 152 million in 2050 globally.1 60-80 % of the cases are caused by AD.2  

More than 50% of patients with dementia have no formal diagnosis3-6 and, in recent surveys, half of carers have reported that an earlier diagnosis of AD would have been preferred.7

Biomarkers like amyloid and tau are recommended to support a diagnosis of AD and clinical trial enrolment.8,9 Several studies have reinforced that certain imaging tests such as amyloid positron emission tomography (PET) and cerebrospinal fluid biomarkers (CSF) are valid proxies for neuropathological changes of AD.10

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The Elecsys® AD CSF portfolio includes three assays11

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    Elecsys® AD CSF assays can detect amyloid positivity, enhancing diagnostic accuracy and physician confidence.12,13

     

    Amyloid Positron Emission Tomography (PET) detects amyloid pathology in the brain, but has several limitations for clinical routine implementation: expensive technique, requires specialist units equipment and it confers a radioactive burden to the patient.14-17

    Elecsys® AD CSF assays are concordant to amyloid PET and provide an alternative solution for detection of amyloid positivity.11,13

    Distribution of pTau and Abeta42 CSF biomarkers

    Distribution of pTau and Abeta42 CSF biomarkers colored by PET visual read classification on a cohort of patients presenting with mild cognitive symptoms (MCS)11,13

    Elecsys® ratios (pTau/Abeta 42, tTau/Abeta 42) achieve 90% concordance with amyloid PET. A result above the cut-off is consistent with a positive visual read.11,13

     

    Concordance between CSF biomarker test results and amyloid PET visual read was assessed using 277 CSF samples from Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably (BioFINDER) cohort of patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI)11,13

    Performance of CSF biomarkers cut-offs versus amyloid PET visual read11,13

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    Performance of CSF biomarkers cut-offs versus amyloid PET visual read11,13

      Cut-off (+)  
    		 Cut-off (-)    PPA %  NPA %  OPA %
    Elecsys® pTau/ Abeta42  >0.023 ≤ 0.023 90.9 (83.9-95.6)

    89.2 (83.5-93.5) 

    		 89.9 (85.7-93.2)   
    Elecsys® tTau/ Abeta42 > 0.28 ≤ 0.28 90.9 (83.9-95.6)  89.2 (83.5-93.5)  89.9 (85.7-93.2)
    Note: PPA - Positive Percentage Agreement; NPA - Negative Percentage Agreement; OPA - Overall Percentage Agreement. Values in brackets are 95% confidence intervals.
    HCPs at computer

    Elecsys® AD CSF assays enable timely intervention by identifying patients with MCI at risk of progression to AD.13

     

    Identification of disease progression is key for planning patient treatment and care. CSF biomarkers can detect subjects more at risk of progression to AD.18

    Elecsys® AD CSF assays aid to identify adult subjects with MCI at higher vs lower risk of cognitive decline as defined by a change in clinical score (Clinical Dementia Rating scale – Sum of Boxes, CDR-SB; Mini Mental State Exam, MMSE) within a 2 year period.11,13

    Distribution of pTau and Abeta42 CSF biomarkers

    Model-based average +/- standard error in biomarker-negative (blue) and biomarker positive (aqua) CDR-SB for follow up at 0, 6, 12 and 24 months. A higher CDR-SB score implies a worsening of the patient's cognitive function.11,13

    (1) No change in Biomarker-negative patients over two years more than 0,5 and -0,5 units
    (2) Change between biomarker-positive and biomarker-negative groups over 2 years more than 1 and -2,5 units

    Reagent pack loading

    Validated clinical cut-offs help ensure an easier implementation of Elecsys® in your lab.13,19

     

    Universal cut-off is already applied for many biomarkers in clinical routine (i.e. HbA1c in diabetes mellitus). The next step is to apply the same concept for AD biomarkers to help ensure universal interpretation of results.19

    Elecsys® AD CSF assays have clinically validated cut-offs that simplify and standardize worldwide interpretation of the results.13,19

    Elecsys® AD CSF assay cut-offs for concordance with amyloid PET were established using PET visual read and then validated for clinical progression claim.11,13

    Elecsys® AD CSF portfolio cut-offs 10

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    Elecsys® AD CSF portfolio cut-offs 10

          Cut-off (+)    Cut-off (-)   
     Abeta 42  ≤ 1030 pg/mL  > 1030 pg/mL
     pTau  > 27 pg/mL  ≤ 27 pg/mL
     tTau  > 300 pg/mL  ≤ 300 pg/mL
     pTau / Abeta 42   > 0.023 pg/mL  ≤ 0.023 pg/mL
     tTau / Abeta 42  > 0.28 pg/mL ≤ 0.28 pg/mL

    Your results are reliable with Elecsys® 11,20

     

    Elecsys® AD CSF assays achieve highly accurate and precise results. This is supported by internal data11 and confirmed by the Alzheimer’s Association Quality Control rounds, where Elecsys® results outperform other manual and automated assays.

    Elecsys® AD CSF assays intermediate precision11

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    Elecsys® AD CSF assays intermediate precision11

      Coefficient of Variation (CV%)  
    AB42 2 ≤6
    pTau ≤2.5
    tTau ≤2.5
    AAQQ results

    CV% for manual and automated CSF assays in AAQC rounds (2014-2023)20

    Testing of AD parameters becomes fast and fully integrated.11

     

    Once the sample is placed on the analyzer, results are received within 18 minutes, a marked improvement compared to previous manual enzyme-linked immunoabsorbent assays (ELISA).11,19

    Unlike most major vendors that are limited to instrument size, with cobas® e you can run the assays on a cobas® e instrument of your choice, from the smaller to the largest.11,21

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      References

      1. Alzheimers Disease International. (2018). World Alzheimer Report 2018. Available at: https://www.alz.co.uk/research/WorldAlzheimerReport2018.pdf Last accessed September 2023
      2. Alzheimer's Association. 2023 Alzheimer's disease facts and figures. Available at: https://www.alz.org/media/Documents/alzheimers-facts-and-figures.pdf Last accessed September 2023
      3. Lopponen, M. et al. (2003). Diagnosing cognitive impairment and dementia in primary health care - a more active approach is needed. Age Ageing 32(6), 606-12.; 
      4. Boustani M, et al. (2003) Screening for Dementia in Primary Care: A Summary of the Evidence for the U.S. Preventive Services Task Force 2003;138(11):927–37; 
      5. Valcour VG, et al. (2000) The Detection of Dementia in the Primary Care Setting. Arch Intern Med. 2000;160(19):2964–8; 
      6. Lang L, et al.(2017) Prevalence and determinants of undetected dementia in the community: a systematic literature review and a meta-analysis. BMJ Open 
      7. Alzheimer Europe. European carers’ report (2018) Carer’s experiences of diagnosis in five European countries. 2018. Available at https://www.alzheimer-europe.org/sites/default/files/2021-11/04886%20Carers%27%20report_updated%20FINAL.pdf. Last accessed September 2023
      8. FDA (2018). "Early AD: developing drugs for treatment, guidance for industry. Available at: https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM596728.pdf." Last accessed September 2023
      9. EMA (2018). Guidelines on the clinical investigation of medicines for the treatment of AD. Available at: https://www.ema.europa.eu/documents/scientific-guideline/guideline-clinical-investigation-medicines-treatment-Alzheimers-disease-revision-2_en.pdf. Last accessed September 2023
      10. Jack, CR, Jr., et al. (2018). "NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease." Alzheimers Dement 14(4): 535-562.
      11. Elecsys® Method Sheet: ms_08821941500V1.0, ms_08821909500V1.0, ms_08846715500V1.0, ms_08846693500V1.0,  ms_08846634500V1.0, ms_08846685500V1.0
      12. Rabinovici, G.D. et al. (2019). Association of Amyloid Positron Emission Tomography With Subsequent Change in Clinical Management Among Medicare Beneficiaries With Mild Cognitive Impairment or Dementia. JAMA 321(13), 1286-1294.
      13. Hazan J, et al. (2023) Clinical utility of cerebrospinal fluid biomarkers in the evaluation of cognitive impairment: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 94(2):113-120. doi: 10.1136/jnnp-2022-329530. Epub 2022 Sep 12. PMID: 36096664.
      14. Blennow, K, et al. (2015). "Amyloid biomarkers in Alzheimer's disease." Trends Pharmacol Sci 36(5): 297-309.
      15. Arnerić, SP, et al. (2017). "Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: A View of the Regulatory Science Qualification Landscape from the Coalition Against Major Diseases CSF Biomarker Team." J Alzheimers Dis 55(1): 19-35.
      16. Frisoni, GB, et al. (2017). "Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers." Lancet Neurol 16(8): 661-676.
      17. Liu, JL, et al. (2017). Assessing the Preparedness of the U.S. Health Care System Infrastructure for an Alzheimer's Treatment, RAND Corporation.
      18. Blennow, K., Shaw, L.M., Stomrud, E. et al. Predicting clinical decline and conversion to Alzheimer’s disease or dementia using novel Elecsys Aβ(1–42), pTau and tTau CSF immunoassays. Sci Rep 9, 19024 (2019). https://doi.org/10.1038/s41598-019-54204-z
      19. Bittner, T, et al. (2016). "Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of beta-amyloid (1-42) in human cerebrospinal fluid." Alzheimers Dement 12(5): 517-526.
      20. Alzheimer's Association Quality Control: 2014 (Round 14) to 2023 (Round 42)
      21. Internal market research.