Advertisement

Assessing FDG-PET diagnostic accuracy studies to develop recommendations for clinical use in dementia

  • Marina Boccardi
  • Cristina Festari
  • Daniele Altomare
  • Federica Gandolfo
  • Stefania Orini
  • Flavio Nobili
  • Giovanni B. Frisoni
  • for the EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders
Review Article

Abstract

Background

FDG-PET is frequently used as a marker of synaptic damage to diagnose dementing neurodegenerative disorders. We aimed to adapt the items of evidence quality to FDG-PET diagnostic studies, and assess the evidence available in current literature to assist Delphi decisions for European recommendations for clinical use.

Methods

Based on acknowledged methodological guidance, we defined the domains, specific to FDG-PET, required to assess the quality of evidence in 21 literature searches addressing as many Population Intervention Comparison Outcome (PICO) questions. We ranked findings for each PICO and fed experts making Delphi decisions for recommending clinical use.

Results

Among the 1435 retrieved studies, most lacked validated measures of test performance, an adequate gold standard, and head-to-head comparison of FDG-PET and clinical diagnosis, and only 58 entered detailed assessment. Only two studies assessed the accuracy of the comparator (clinical diagnosis) versus any kind of gold−/reference-standard. As to the index-test (FDG-PET-based diagnosis), an independent gold-standard was available in 24% of the examined papers; 38% used an acceptable reference-standard (clinical follow-up); and 38% compared FDG-PET-based diagnosis only to baseline clinical diagnosis. These methodological limitations did not allow for deriving recommendations from evidence.

Discussion

An incremental diagnostic value of FDG-PET versus clinical diagnosis or lack thereof cannot be derived from the current literature. Many of the observed limitations may easily be overcome, and we outlined them as research priorities to improve the quality of current evidence. Such improvement is necessary to outline evidence-based guidelines. The available data were anyway provided to expert clinicians who defined interim recommendations.

Keywords

FDG-PET Positron emission tomography Fluorodeoxyglucose metabolism 18F-FDG PET Evidence assessment Quality of evidence Recommendations Validation Biomarker Alzheimer Dementia Diagnosis 

Notes

Acknowledgements

The procedure for assessing scientific evidence and defining consensual recommendations was funded by the European Association of Nuclear Medicine (EANM) and by the European Academy of Neurology (EAN). We thank the Guidelines working group of EAN, particularly Simona Arcuti and Maurizio Leone, for methodological advice.

Collaborators for this paper are: Federica Agosta7, Javier Arbizu8, Femke Bouwman9, Alexander Drzezga10, Peter Nestor11, Zuzana Walker12.

7Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.

8Department of Nuclear Medicine. Clinica Universidad de Navarra. University of Navarra. Pamplona, Spain.

9Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.

10Department of Nuclear Medicine, University Hospital of Cologne, University of Cologne and German Center for Neurodegenerative Diseases (DZNE), Germany.

11German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Queensland Brain Institute, University of Queensland and at the Mater Hospital Brisbane.

12University College London, Division of Psychiatry & Essex Partnership University NHS Foundation Trust, UK.

Funding

This project was partially funded by the European Association of Nuclear Medicine (EANM) and the European Academy of Neurology (EAN).

Compliance with ethical standards

Conflict of interest

Marina Boccardi has received funds from the European Association of Nuclear Medicine (EANM) to perform the evidence assessment and the global coordination of the present project. Moreover, she has received research grants from Piramal and served as a paid member of advisory boards for Eli Lilly.

Cristina Festari: declares that she has no conflict of interest.

Daniele Altomare was the recipient of the grant allocated by the European Academy of Neurology (EAN) for data extraction and evidence assessment for the present project.

Federica Gandolfo: declares that she has no conflict of interest.

Stefania Orini: declares that she has no conflict of interest.

Flavio Nobili: received personal fees and non-financial support from GE Healthcare, non-financial support from Eli-Lilly and grants from Chiesi Farmaceutici.

Giovanni B Frisoni is principal investigator of industry-sponsored trials funded by AbbVie, Acadia, Altoida, Amoneta, Araclon, Biogen, Janssen, Novartis, Piramal; has received funding for investigator-initiated trials from GE, Piramal, and Avid-Lilly; and has received speaker fees from a number of pharma and imaging companies.

Ethical approval

This is a review article that does not contain any original study with human participants performed by any of the authors. Ethical approval is shown in each of the quoted original papers.

Informed consent

Not applicable to this review article. Informed consent statement is declared in each of the revised papers.

References

  1. 1.
    Frisoni GB, Perani D, Bastianello S, Bernardi G, Porteri C, Boccardi M, et al. Biomarkers for the diagnosis of Alzheimer’s disease in clinical practice: an Italian intersocietal roadmap. Neurobiol Aging. 2017;52:119–31.CrossRefPubMedGoogle Scholar
  2. 2.
    Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol. 2014;13(6):614–29.CrossRefPubMedGoogle Scholar
  3. 3.
    Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207–16.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Boccardi M, Gallo V, Yasui Y, Vineis P, Padovani A, Mosimann U, et al. The biomarker-based diagnosis of Alzheimer’s disease. 2-lessons from oncology. Neurobiol Aging. 2017;52:141–52.CrossRefPubMedGoogle Scholar
  5. 5.
    Leone MA, Brainin M, Boon P, Pugliatti M, Keindl M, Bassetti CL. Guidance for the preparation of neurological management guidelines by EFNS scientific task forces—revised recommendations 2012. Eur J Neurol. 2013;20(3):410–9.CrossRefPubMedGoogle Scholar
  6. 6.
    Leone MA, Keindl M, Schapira AH, Deuschl G, Federico A. Practical recommendations for the process of proposing, planning and writing a neurological management guideline by EAN task forces. Eur J Neurol. 2015;22(12):1505–10.CrossRefPubMedGoogle Scholar
  7. 7.
    Nobili F, Arbizu J, Bouwman FH, Drzezga A, Agosta F, Nestor P, et al. EANM-EAN recommendations for the use of brain 18F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) in neurodegenerative cognitive impairment and dementia: Delphi consensus. Eur J Neurol. 2018; submitted (March 13, 2018), MS: EJoN-18-0310.Google Scholar
  8. 8.
    Reitsma JB, Rutjes AWS, Whiting P, Vlassov VV, Leeflang MMG, Deeks JJ. Chapter 9: assessing methodological quality. In: Deeks JJ, Bossuyt PM, Gatsonis C, editors. Cochrane handbook for systematic reviews of diagnostic test accuracy, Version 1.0.0. The Cochrane Collaboration; 2009. Available from: http://srdta.cochrane.org/.
  9. 9.
    Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Hsu J, Brozek JL, Terracciano L, Kreis J, Compalati E, Stein AT, et al. Application of GRADE: making evidence-based recommendations about diagnostic tests in clinical practice guidelines. Implement Sci. 2011;6:62.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Schunemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, Vist GE, et al. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ. 2008;336(7653):1106–10.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Guyatt GH, Oxman AD, Vist G, Kunz R, Brozek J, Alonso-Coello P, et al. GRADE guidelines: 4. Rating the quality of evidence–study limitations (risk of bias). J Clin Epidemiol. 2011;64(4):407–15.CrossRefPubMedGoogle Scholar
  13. 13.
    Jack CR Jr, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9(1):119–28.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Dubois B, Feldman HH, Jacova C, Cummings JL, Dekosky ST, Barberger-Gateau P, et al. Revising the definition of Alzheimer’s disease: a new lexicon. Lancet Neurol. 2010;9(11):1118–27.CrossRefPubMedGoogle Scholar
  15. 15.
    Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, et al. Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria. Alzheimers Dement. 2016;12(3):292–323.CrossRefPubMedGoogle Scholar
  16. 16.
    McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, et al. Diagnosis and management of dementia with Lewy bodies: fourth consensus report of the DLB consortium. Neurology. 2017;89(1):88–100.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Bossuyt PM, Leeflang MM. Developing criteria for including studies. In: Cochrane handbook for systematic reviews of diagnostic test accuracy, Version 0.4. [updated September 2008]. The Cochrane Collaboration, 2008.Google Scholar
  18. 18.
    Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64(4):383–94.CrossRefPubMedGoogle Scholar
  19. 19.
    Morbelli S, Garibotto V, Van De Giessen E, Arbizu J, Chetelat G, Drezgza A, et al. A Cochrane review on brain [(1)(8)F]FDG PET in dementia: limitations and future perspectives. Eur J Nucl Med Mol Imaging. 2015;42(10):1487–91.CrossRefPubMedGoogle Scholar
  20. 20.
    Matias-Guiu JA, Cabrera-Martin MN, Garcia-Ramos R, Moreno-Ramos T, Valles-Salgado M, Carreras JL, et al. Evaluation of the new consensus criteria for the diagnosis of primary progressive aphasia using fluorodeoxyglucose positron emission tomography. Dement Geriatr Cogn Disord. 2014;38(3–4):147–52.CrossRefPubMedGoogle Scholar
  21. 21.
    Frisoni GB, Boccardi M, Barkhof F, Blennow K, Cappa S, Chiotis K, et al. Strategic roadmap for an early diagnosis of Alzheimer’s disease based on biomarkers. Lancet Neurol. 2017;16(8):661–76.CrossRefPubMedGoogle Scholar
  22. 22.
    Balshem H, Helfand M, Schunemann HJ, Oxman AD, Kunz R, Brozek J, et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol. 2011;64(4):401–6.CrossRefPubMedGoogle Scholar
  23. 23.
    Agosta F, Altomare D, Festari C, Orini S, Gandolfo F, Boccardi M, et al. Clinical utility of FDG-PET in amyotrophic lateral sclerosis and Huntington’s disease. Eur J Nucl Med Mol Imaging. 2018.  https://doi.org/10.1007/s00259-018-4033-0.CrossRefPubMedGoogle Scholar
  24. 24.
    Arbizu J, Festari C, Altomare D, Walker Z, Bouwman FH, Rivolta J, et al. Clinical utility of FDG-PET for the clinical diagnosis in MCI. Eur J Nucl Med Mol Imaging. 2018.  https://doi.org/10.1007/s00259-018-4039-7.CrossRefPubMedGoogle Scholar
  25. 25.
    Bouwman FH, Orini S, Gandolfo F, Altomare D, Festari C, Agosta F, et al. Diagnostic utility of FDG-PET in the differential diagnosis between different forms of primary progressive aphasia. Eur J Nucl Med Mol Imaging. 2018.  https://doi.org/10.1007/s00259-018-4034-z.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Drzezga A, Altomare D, Festari C, Arbizu J, Orini S, Herholz, et al. Diagnostic utility of FDG-PET in asymptomatic subjects at increased risk for Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2018.  https://doi.org/10.1007/s00259-018-4032-1.CrossRefPubMedGoogle Scholar
  27. 27.
    Nestor P, Altomare D, Festari C, Drzezga A, Rivolta J, Walker Z, et al. Clinical utility of FDG-PET for the differential diagnosis among the main forms of dementia. Eur J Nucl Med Mol Imaging. 2018.  https://doi.org/10.1007/s00259-018-4035-y.CrossRefPubMedGoogle Scholar
  28. 28.
    Nobili F, Festari C, Altomare D, Agosta F, Orini S, Van Laere, et al. Automated assessment of FDG-PET for the differential diagnosis in patients with neurodegenerative disorders. Eur J Nucl Med Mol Imaging. 2018  https://doi.org/10.1007/s00259-018-4030-3.CrossRefPubMedGoogle Scholar
  29. 29.
    Walker Z, Gandolfo F, Orini S, Garibotto V, Agosta F, Arbizu J, et al. Clinical utility of FDG-PET in Parkinson’s disease and atypical Parkinsonisms associated to dementia. Eur J Nucl Med Mol Imaging. 2018.  https://doi.org/10.1007/s00259-018-4031-2.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Murphy MK, Black NA, Lamping DL, McKee CM, Sanderson CF, Askham J, et al. Consensus development methods, and their use in clinical guideline development. Health Technol Assess. 1998;2(3):i–iv, 1–88.Google Scholar
  31. 31.
    Barthel H, Sabri O. Clinical use and utility of amyloid imaging. J Nucl Med. 2017;58(11):1711–7.CrossRefPubMedGoogle Scholar
  32. 32.
    Perani D, Schillaci O, Padovani A, Nobili FM, Iaccarino L, Della Rosa PA, et al. A survey of FDG- and amyloid-PET imaging in dementia and GRADE analysis. Biomed Res Int. 2014;2014:785039.CrossRefPubMedGoogle Scholar
  33. 33.
    Smailagic N, Vacante M, Hyde C, Martin S, Ukoumunne O, Sachpekidis C. (1)(8)F-FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev. 2015;1:Cd010632.PubMedGoogle Scholar
  34. 34.
    Beach TG, Monsell SE, Phillips LE, Kukull W. Accuracy of the clinical diagnosis of Alzheimer disease at National Institute on Aging Alzheimer disease centers, 2005–2010. J Neuropathol Exp Neurol. 2012;71(4):266–73.CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Laforce R Jr, Buteau JP, Paquet N, Verret L, Houde M, Bouchard RW. The value of PET in mild cognitive impairment, typical and atypical/unclear dementias: a retrospective memory clinic study. Am J Alzheimers Dis Dement. 2010;25(4):324–32.CrossRefGoogle Scholar
  36. 36.
    Laforce R Jr, Tosun D, Ghosh P, Lehmann M, Madison CM, Weiner MW, et al. Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer’s pathology. NeuroImage Clin. 2014;4:508–16.CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    GRADE handbook for grading quality of evidence and strength of recommendations. 2013.Google Scholar
  38. 38.
    Gopalakrishna G, Mustafa RA, Davenport C, Scholten RJ, Hyde C, Brozek J, et al. Applying grading of recommendations assessment, development and evaluation (GRADE) to diagnostic tests was challenging but doable. J Clin Epidemiol. 2014;67(7):760–8.CrossRefPubMedGoogle Scholar
  39. 39.
    Trenti T, Schunemann HJ, Plebani M. Developing GRADE outcome-based recommendations about diagnostic tests: a key role in laboratory medicine policies. Clin Chem Lab Med. 2016;54(4):535–43.CrossRefPubMedGoogle Scholar
  40. 40.
    Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):270–9.CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, et al. Classification of primary progressive aphasia and its variants. Neurology. 2011;76(11):1006–14.CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):263–9.CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain J Neurol. 2011;134(Pt 9):2456–77.CrossRefGoogle Scholar
  44. 44.
    Hoglinger GU, Respondek G, Stamelou M, Kurz C, Josephs KA, Lang AE, et al. Clinical diagnosis of progressive supranuclear palsy: the movement disorder society criteria. Mov Disord. 2017;32(6):853–64.CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Strong MJ, Abrahams S, Goldstein LH, Woolley S, McLaughlin P, Snowden J, et al. Amyotrophic lateral sclerosis-frontotemporal spectrum disorder (ALS-FTSD): revised diagnostic criteria. Amyotroph Lateral Scler Frontotemporal Degener. 2017;18(3–4):153–74.CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Marina Boccardi
    • 1
    • 2
  • Cristina Festari
    • 2
    • 3
  • Daniele Altomare
    • 2
    • 3
  • Federica Gandolfo
    • 4
  • Stefania Orini
    • 4
  • Flavio Nobili
    • 5
  • Giovanni B. Frisoni
    • 1
    • 2
    • 6
  • for the EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders
  1. 1.LANVIE (Laboratoire de Neuroimagerie du Vieillissement), Department of PsychiatryUniversity of GenevaChene-BourgSwitzerland
  2. 2.LANE – Laboratory of Alzheimer Neuroimaging & EpidemiologyIRCCS S. Giovanni di Dio, FatebenefratelliBresciaItaly
  3. 3.Department of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
  4. 4.Alzheimer Operative Unit; IRCCS Centro S. Giovanni di Dio, FatebenefratelliBresciaItaly
  5. 5.DINOGMI – Department of Neuroscience, University of Genoa and IRCCS Polyclinic San Martino HospitalGenoaItaly
  6. 6.HUG Hopitaux Universitaires de GenèveGenevaSwitzerland

Personalised recommendations