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Cited by 375Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsMedical Imaging Techniques and Applications

The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

Open access
Palmqvist, Sebastian, Zetterberg, Henrik, Mattsson, Niklas, Johansson, Per, For the Alzheimer's Disease Neuroimaging Initiative, Minthon, Lennart, Blennow, Kaj, Olsson, Mattias, For the Swedish BioFINDER study group, Hansson, Oskar, Hansson, Oskar, Minthon, Lennart, Toresson, Håkan, Nägga, Katarina, Palmqvist, Sebastian, Stomrud, Erik, Johansson, Per, Nilsson, Christer, Nilsson, Maria, Mattsson, Niklas, Lindqvist, Daniel, Vestberg, Susanna, Janelidze, Shorena, Zetterberg, Henrik, Blennow, Kaj, Andreasson, Ulf, van Westen, Danielle, Lätt, Jimmy, Mannfolk, Peter, Nilsson, Markus, Strandberg, Olof, Sundgren, Pia, Ståhlberg, Freddy, Lindberg, Olof, Westman, Eric, Wahlund, Lars-Olof, Wollmer, Per, Smith, Ruben, Olsson, Tomas, Weiner, Michael, Aisen, Paul, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R., Jagust, William, Trojanowki, J.Q., Toga, Arthur W., Beckett, Laurel, Green, Robert C., Gamst, Anthony, Saykin, Andrew J., Morris, John, Potter, William Z., Green, Robert C., Montine, Tom, Petersen, Ronald, Aisen, Paul, Gamst, Anthony, Thomas, Ronald G., Donohue, Michael, Walter, Sarah, Jack, Clifford R., Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Jagust, William, Bandy, Dan, Koeppe, Robert A., Foster, Norm, Reiman, Eric M., Chen, Kewei, Mathis, Chet, Morris, John, Cairns, Nigel J., Taylor-Reinwald, Lisa, Trojanowki, J.Q., Shaw, Les, Lee, Virginia M.-Y., Korecka, Magdalena, Toga, Arthur W., Crawford, Karen, Neu, Scott, Beckett, Laurel, Harvey, Danielle, Gamst, Anthony, Kornak, John, Saykin, Andrew J., Foroud, Tatiana M., Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J., Molchan, Susan, Kaye, Jeffrey, Dolen, Sara, Quinn, Joseph, Schneider, Lon, Pawluczyk, Sonia, Spann, Bryan M., Brewer, James, Vanderswag, Helen, Heidebrink, Judith L., Lord, Joanne L., Petersen, Ronald, Johnson, Kris, Doody, Rachelle S., Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S., Bell, Karen L., Morris, John C., Mintun, Mark A., Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, Tang, Cheuk, Marzloff, George, deToledo-Morrell, Leyla, Shah, Raj C., Duara, Ranjan, Varon, Daniel, Roberts CAN, Peggy, Albert, Marilyn S., Kozauer, Nicholas, Zerrate, Maria, Rusinek, Henry, de Leon, Mony J, De Santi, Susan M, Doraiswamy, P. Murali, Petrella, Jeffrey R., Aiello, Marilyn, Arnold, Steve, Karlawish, Jason H., Wolk, David, Smith, Charles D., Given, Curtis A., Hardy, Peter, Lopez, Oscar L., Oakley, MaryAnn, Simpson, Donna M., Ismail, M. Saleem, Brand, Connie, Richard, Jennifer, Mulnard, Ruth A., Thai, Gaby, Mc-Adams-Ortiz, Catherine, Diaz-Arrastia, Ramon, Martin-Cook, Kristen, DeVous, Michael, Levey, Allan I., Lah, James J., Cellar, Janet S., Burns, Jeffrey M., Anderson, Heather S., Laubinger, Mary M., Apostolova, Liana, Silverman, Daniel H.S., Lu, Po H., Graff-Radford, Neill R, Parfitt, Francine, Johnson, Heather, Farlow, Martin, Herring, Scott, Hake, Ann M., van Dyck, Christopher H., MacAvoy, Martha G., Benincasa, Amanda L., Chertkow, Howard, Bergman, Howard, Hosein, Chris, Black, Sandra, Stefanovic, Bojana, Caldwell, Curtis, Robin Hsiung, Ging-Yuek, Feldman, Howard, Assaly, Michele, Kertesz, Andrew, Rogers, John, Trost, Dick, Bernick, Charles, Munic, Donna, Wu, Chuang-Kuo, Johnson, Nancy, Mesulam, Marsel, Sadowsky, Carl, Martinez, Walter, Villena, Teresa, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, Sperling, Reisa A., Rentz, Dorene M., Johnson, Keith A., Rosen, Allyson, Tinklenberg, Jared, Ashford, Wes, Sabbagh, Marwan, Connor, Donald, Jacobson, Sandra, Killiany, Ronald, Norbash, Alexander, Nair, Anil, Obisesan, Thomas O., Jayam-Trouth, Annapurni, Wang, Paul, Lerner, Alan, Hudson, Leon, Ogrocki, Paula, DeCarli, Charles, Fletcher, Evan, Carmichael, Owen, Kittur, Smita, Borrie, Michael, Lee, T-Y, Bartha, Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M., Potkin, Steven G., Preda, Adrian, Nguyen, Dana, Tariot, Pierre, Fleisher, Adam, Reeder, Stephanie, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Hendin, Barry A., Scharre, Douglas W., Kataki, Maria, Zimmerman, Earl A., Celmins, Dzintra, Brown, Alice D., Pearlson, Godfrey, Blank, Karen, Anderson, Karen, Saykin, Andrew J., Santulli, Robert B., Englert, Jessica, Williamson, Jeff D., Sink, Kaycee M., Watkins, Franklin, Ott, Brian R., Stopa, Edward, Tremont, Geoffrey, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Rosen, Howard J., Mintzer, Jacobo, Longmire, Crystal Flynn, Spicer, Kenneth·2015·Neurology
DOI 10.1212/wnl.0000000000001991PMC PMC4607601
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Abstract

OBJECTIVE: To compare the diagnostic accuracy of CSF biomarkers and amyloid PET for diagnosing early-stage Alzheimer disease (AD). METHODS: From the prospective, longitudinal BioFINDER study, we included 122 healthy elderly and 34 patients with mild cognitive impairment who developed AD dementia within 3 years (MCI-AD). β-Amyloid (Aβ) deposition in 9 brain regions was examined with [18F]-flutemetamol PET. CSF was analyzed with INNOTEST and EUROIMMUN ELISAs. The results were replicated in 146 controls and 64 patients with MCI-AD from the Alzheimer's Disease Neuroimaging Initiative study. RESULTS: The best CSF measures for identifying MCI-AD were Aβ42/total tau (t-tau) and Aβ42/hyperphosphorylated tau (p-tau) (area under the curve [AUC] 0.93-0.94). The best PET measures performed similarly (AUC 0.92-0.93; anterior cingulate, posterior cingulate/precuneus, and global neocortical uptake). CSF Aβ42/t-tau and Aβ42/p-tau performed better than CSF Aβ42 and Aβ42/40 (AUC difference 0.03-0.12, p<0.05). Using nonoptimized cutoffs, CSF Aβ42/t-tau had the highest accuracy of all CSF/PET biomarkers (sensitivity 97%, specificity 83%). The combination of CSF and PET was not better than using either biomarker separately. CONCLUSIONS: Amyloid PET and CSF biomarkers can identify early AD with high accuracy. There were no differences between the best CSF and PET measures and no improvement when combining them. Regional PET measures were not better than assessing the global Aβ deposition. The results were replicated in an independent cohort using another CSF assay and PET tracer. The choice between CSF and amyloid PET biomarkers for identifying early AD can be based on availability, costs, and doctor/patient preferences since both have equally high diagnostic accuracy. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that amyloid PET and CSF biomarkers identify early-stage AD equally accurately.

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Figure 1 Sensitivities, specificities, and Youden indices of all possible cutoff points (A, B) The cutoffs have been transformed to z scores (SD) for easier comparison between variables. Near optimal Youden indices are found for a relatively wide range of cutoffs (>1 SD) for all variables except for CSF Aβ42/Aβ40EI, which have a slightly narrower span. The different cutoffs within this near optimal range thus only change the relationship between the sensitivity and specificity, but not the overall classification accuracy. This wide range of near optimal cutoffs suggests that the cutoffs are likely to produce high diagnostic accuracies in other populations. AUC = area under the receiver operating characteristic curve.
Figure 1 Sensitivities, specificities, and Youden indices of all possible cutoff points (A, B) The cutoffs have been transformed to z scores (SD) for easier comparison between variables. Near optimal Youden indices are found for a relatively wide range of cutoffs (>1 SD) for all variables except for CSF Aβ42/Aβ40EI, which have a slightly narrower span. The different cutoffs within this near optimal range thus only change the relationship between the sensitivity and specificity, but not the overall classification accuracy. This wide range of near optimal cutoffs suggests that the cutoffs are likely to produce high diagnostic accuracies in other populations. AUC = area under the receiver operating characteristic curve.CC BY-NC-ND · PubMed Central

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Authors
Palmqvist, S., Zetterberg, H., Mattsson, N., Johansson, P., Initiative, F. T. A. D. N., Minthon, L., Blennow, K., Olsson, M., For the Swedish BioFINDER study group, Hansson, O., Hansson, O., Minthon, L., Toresson, H., Nägga, K., Palmqvist, S., Stomrud, E., Johansson, P., Nilsson, C., Nilsson, M., Mattsson, N., Lindqvist, D., Vestberg, S., Janelidze, S., Zetterberg, H., Blennow, K., Andreasson, U., van Westen, D., Lätt, J., Mannfolk, P., Nilsson, M., Strandberg, O., Sundgren, P., Ståhlberg, F., Lindberg, O., Westman, E., Wahlund, L.-O., Wollmer, P., Smith, R., Olsson, T., Weiner, M., Aisen, P., Weiner, M., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., Gamst, A., Saykin, A. J., Morris, J., Potter, W. Z., Green, R. C., Montine, T., Petersen, R., Aisen, P., Gamst, A., Thomas, R. G., Donohue, M., Walter, S., Jack, C. R., Dale, A., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., Alexander, G., DeCarli, C., Jagust, W., Bandy, D., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Morris, J., Cairns, N. J., Taylor-Reinwald, L., Trojanowki, J. Q., Shaw, L., Lee, V. M.-Y., Korecka, M., Toga, A. W., Crawford, K., Neu, S., Beckett, L., Harvey, D., Gamst, A., Kornak, J., Saykin, A. J., Foroud, T. M., Potkin, S., Shen, L., Kachaturian, Z., Frank, R., Snyder, P. J., Molchan, S., Kaye, J., Dolen, S., Quinn, J., Schneider, L., Pawluczyk, S., Spann, B. M., Brewer, J., Vanderswag, H., Heidebrink, J. L., Lord, J. L., Petersen, R., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Stern, Y., Honig, L. S., Bell, K. L., Morris, J. C., Mintun, M. A., Schneider, S., Marson, D., Griffith, R., Clark, D., Grossman, H., Tang, C., Marzloff, G., deToledo-Morrell, L., Shah, R. C., Duara, R., Varon, D., Roberts CAN, P., Albert, M. S., Kozauer, N., Zerrate, M., Rusinek, H., de Leon, M. J., De Santi, S. M., Doraiswamy, P. M., Petrella, J. R., Aiello, M., Arnold, S., Karlawish, J. H., Wolk, D., Smith, C. D., Given, C. A., Hardy, P., Lopez, O. L., Oakley, M., Simpson, D. M., Ismail, M. S., Brand, C., Richard, J., Mulnard, R. A., Thai, G., Mc-Adams-Ortiz, C., Diaz-Arrastia, R., Martin-Cook, K., DeVous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Laubinger, M. M., Apostolova, L., Silverman, D. H. S., Lu, P. H., Graff-Radford, N. R., Parfitt, F., Johnson, H., Farlow, M., Herring, S., Hake, A. M., van Dyck, C. H., MacAvoy, M. G., Benincasa, A. L., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Robin Hsiung, G.-Y., Feldman, H., Assaly, M., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Munic, D., Wu, C.-K., Johnson, N., Mesulam, M., Sadowsky, C., Martinez, W., Villena, T., Turner, R. S., Johnson, K., Reynolds, B., Sperling, R. A., Rentz, D. M., Johnson, K. A., Rosen, A., Tinklenberg, J., Ashford, W., Sabbagh, M., Connor, D., Jacobson, S., Killiany, R., Norbash, A., Nair, A., Obisesan, T. O., Jayam-Trouth, A., Wang, P., Lerner, A., Hudson, L., Ogrocki, P., DeCarli, C., Fletcher, E., Carmichael, O., Kittur, S., Borrie, M., Lee, T.-Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C. M., Potkin, S. G., Preda, A., Nguyen, D., Tariot, P., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Hendin, B. A., Scharre, D. W., Kataki, M., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G., Blank, K., Anderson, K., Saykin, A. J., Santulli, R. B., Englert, J., Williamson, J. D., Sink, K. M., Watkins, F., Ott, B. R., Stopa, E., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Mintzer, J., Longmire, C. F., & Spicer, K.
Affiliations
Authors' affiliations are provided at the end of the article.
ORCID
Venue
Neurology
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2015-10-06
Volume
85
Issue
14
Pages
1240-1249
ISSN
  • 0028-3878 (ISSN-L)
  • 1526-632X
DOI
10.1212/wnl.0000000000001991
PMC
PMC4607601
OpenAlex
W2173601762
Cited by
375
References
41
Citations by year
2026: 23 · 2025: 41 · 2024: 46 · 2023: 34 · 2022: 25 · 2021: 38 · 2020: 33 · 2019: 41 · 2018: 36 · 2017: 29 · 2016: 28 · 2015: 1
FWCI
25.46
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Neurology (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Lund University Publications (Lund University) (submittedVersion, other-oa)
  • Columbia Academic Commons (Columbia University)
Funders
  • National Institutes of Health (5u01ag024904-10)
  • Canadian Institutes of Health Research
  • National Institute on Aging (U01-AG-024904, P50AG005134)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
Keywords
Alzheimer's disease, early diagnosis, amyloid PET, cerebrospinal fluid biomarkers, amyloid-beta, tau protein, mild cognitive impairment, 18F-flutemetamol, diagnostic accuracy
MeSH terms
Aged, Aged, 80 and over, Alzheimer Disease, Brain, Dementia, Female, Humans, Male, Prospective Studies, Radionuclide Imaging, Biomarkers, Amyloid beta-Peptides, tau Proteins, Cognitive Dysfunction

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