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DOI 10.1001/jama.2026.13116

Медицинская библиотека · JAMA · 2026

Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease: An Individual Participant Data Meta-Analysis.

Blazhenets Ganna, Soleimani-Meigooni David N, Chiotis Konstantinos, Allen Isabel E, Rabinovici Gil D, La Joie Renaud, Meta-Centiloid Study Group, Apostolova Liana G, Asken Breton M, Bejanin Alexandre, Benzinger Tammie L S, Betthauser Tobey J, Bluma Marina, Bombois Stephanie, Bourgeat Pierrick, Bouteloup Vincent, Braskie Meredith N, Brendel Matthias, Brickman Adam M, Bryant Natalie, Bullich Santiago, Carrillo Maria C, Casaletto Kaitlin, Cash David M, Chang Chiung-Chih, Chang Hsin-I, Chao Yishu, Chêne Genevieve, Chételat Gaël, Coath William, Collij Lyduine E, Colmant Lise, Corrada Maria M, Craft Suzanne, Dickerson Bradford C, Dubois Bruno, Dufouil Carole, Fajardo Alfonso, Farrar Gill, Fortea Juan, Frings Lars, Frisoni Giovanni B, Gardner Raquel C, Garibotto Valentina, Gnörich Johannes S, Gordon Brian A, Gu Yuna, Guan Yihui, Guo Tengfei, Hanseeuw Bernard J, Hansson Oskar, Harrison Theresa M, Huang Qi, Huang Shu-Hua, Iaccarino Leonardo, Ishii Kazunari, Ishi Kenji, Jagust William J, Johnson Sterling C, Kato Takashi, Katsumi Yuta, Kaye Jeffrey, Koeppe Robert A, Kolinger Guilherme D, Kramer Joel H, Landau Susan M, Landeau Brigitte, Lao Patrick J, Lee Sangwon, Lleó Alberto, Lopresti Brian J, Lowe Val J, Luchsinger Jose A, Malpetti Maura, Mao Xiaoxie, March Andrew, Masters Colin L, Meyer Philipp T, Mezenge Florence, Mormino Elizabeth C, Franquesa-Mullerat Maria, Nakamura Akinori, Nordberg Agneta, O'Brien John T, O'Bryant Sid E, Pappas Ioannis, Peretti Debora E, Quenon Lisa, Rowe Christopher C, Rowe James B, Rudolph Marc D, Salvadó Gemma, Schott Jonathan M, Schwartz Daniel L, Schwarz Christopher G, Seo Sang Won, Shekari Mahnaz, Silbert Lisa C, Smith Ruben, Snyder Heather M, Sokolowski Andrzej, Sperling Reisa A, Sun Pan, Taggett Jacinda Z, Toga Arthur W, Touroutoglou Alexandra, Vaillancourt David E, van de Giessen Elsmarieke, Vijverberg Jort, Vemuri Prashanthi, Villain Nicolas, Villemagne Victor L, Villeneuve Sylvia, Wang Wei-En, Weiner Michael, Woodworth Davis, Xiao Cally, Xie Fang, Yoon Yeojun, Young Christina B, Yun Mijin, A4, ABIDE, ADNI*, ADNI-DoD, AgeWell, AIBL, AMYPAD, BACS, BATON, BIOCARD, BLSA, BioFINDER-2, BrANCH, CPAS, DETECT-AD, GEMS, GHABS, HABS, HABS-HD, IDEAS, IMAP, INSIGHT-preAD, Insight46, K-ROAD, LEADS, MCSA, MULNIAD, MEMENTO, SCAN, PREVENT-AD, SPIN, Severanc

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Аннотация

IMPORTANCE

Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used.

OBJECTIVE

To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads.

DATA SOURCES: PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025).

STUDY SELECTION: Studies were included if they provided Centiloids, radiotracer, age, and sex.

DATA EXTRACTION AND SYNTHESIS: Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis.

MAIN OUTCOMES AND MEASURES: Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available.

RESULTS

This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%).

CONCLUSIONS AND RELEVANCE: In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Для цитирования: Blazhenets Ganna, Soleimani-Meigooni David N, Chiotis Konstantinos, Allen Isabel E, Rabinovici Gil D, La Joie Renaud, Meta-Centiloid Study Group, Apostolova Liana G, Asken Breton M, Bejanin Alexandre, Benzinger Tammie L S, Betthauser Tobey J, Bluma Marina, Bombois Stephanie, Bourgeat Pierrick, Bouteloup Vincent, Braskie Meredith N, Brendel Matthias, Brickman Adam M, Bryant Natalie, Bullich Santiago, Carrillo Maria C, Casaletto Kaitlin, Cash David M, Chang Chiung-Chih, Chang Hsin-I, Chao Yishu, Chêne Genevieve, Chételat Gaël, Coath William, Collij Lyduine E, Colmant Lise, Corrada Maria M, Craft Suzanne, Dickerson Bradford C, Dubois Bruno, Dufouil Carole, Fajardo Alfonso, Farrar Gill, Fortea Juan, Frings Lars, Frisoni Giovanni B, Gardner Raquel C, Garibotto Valentina, Gnörich Johannes S, Gordon Brian A, Gu Yuna, Guan Yihui, Guo Tengfei, Hanseeuw Bernard J, Hansson Oskar, Harrison Theresa M, Huang Qi, Huang Shu-Hua, Iaccarino Leonardo, Ishii Kazunari, Ishi Kenji, Jagust William J, Johnson Sterling C, Kato Takashi, Katsumi Yuta, Kaye Jeffrey, Koeppe Robert A, Kolinger Guilherme D, Kramer Joel H, Landau Susan M, Landeau Brigitte, Lao Patrick J, Lee Sangwon, Lleó Alberto, Lopresti Brian J, Lowe Val J, Luchsinger Jose A, Malpetti Maura, Mao Xiaoxie, March Andrew, Masters Colin L, Meyer Philipp T, Mezenge Florence, Mormino Elizabeth C, Franquesa-Mullerat Maria, Nakamura Akinori, Nordberg Agneta, O'Brien John T, O'Bryant Sid E, Pappas Ioannis, Peretti Debora E, Quenon Lisa, Rowe Christopher C, Rowe James B, Rudolph Marc D, Salvadó Gemma, Schott Jonathan M, Schwartz Daniel L, Schwarz Christopher G, Seo Sang Won, Shekari Mahnaz, Silbert Lisa C, Smith Ruben, Snyder Heather M, Sokolowski Andrzej, Sperling Reisa A, Sun Pan, Taggett Jacinda Z, Toga Arthur W, Touroutoglou Alexandra, Vaillancourt David E, van de Giessen Elsmarieke, Vijverberg Jort, Vemuri Prashanthi, Villain Nicolas, Villemagne Victor L, Villeneuve Sylvia, Wang Wei-En, Weiner Michael, Woodworth Davis, Xiao Cally, Xie Fang, Yoon Yeojun, Young Christina B, Yun Mijin, A4, ABIDE, ADNI*, ADNI-DoD, AgeWell, AIBL, AMYPAD, BACS, BATON, BIOCARD, BLSA, BioFINDER-2, BrANCH, CPAS, DETECT-AD, GEMS, GHABS, HABS, HABS-HD, IDEAS, IMAP, INSIGHT-preAD, Insight46, K-ROAD, LEADS, MCSA, MULNIAD, MEMENTO, SCAN, PREVENT-AD, SPIN, Severanc. Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease: An Individual Participant Data Meta-Analysis.. JAMA. 2026. DOI: 10.1001/jama.2026.13116.
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